Final Report Summary - PROSECO (Collaborative Environment for Design of AmI enhanced Product-Services Integrating Highly Personalised Innovative Functions with Minimal Ecological Footprint along Life Cycle and of Their Production P)
Executive Summary:
ProSEco provides a novel methodology and a comprehensive ICT solution for collaborative design of product-services (Meta Products) and their production processes.
The effective extension of products with new services in different sectors (automotive, home appliances, automation equipment etc.) will be achieved by means of Ambient Intelligence (AmI) technology, Lean and Eco-design principles and applying Life Cycle Assessment techniques.
New Meta Products using AmI, will be capable of acquiring knowledge in order to add highly personalized innovative functions, and thus enabling new business models. A Cloud Manufacturing approach is used for effective collaborative design of product-services and their production processes, and the effective implementation of innovative services. As a result new eco-innovative Meta Products are offered, which integrate highly personalised innovative functions with minimal environmental footprint along the overall Life Cycle. ProSEco offers a development platform and a set of new engineering tools to support collaborative work (simulation, configuration etc.) on new product-services, enhancing existing tools for product/process design.
The project has been driven by four industrial application scenarios addressing different aspects of service and business building as well as product/process development (complex internal and external supply chains), in order to assure that the means for collaborative service generation and product-service and production process design to be developed in the project will be relevant for industry. The solution will be first applied at 5 manufacturers in the consortium (Desma (DE), Ona (ES), Electrolux (IT), Volkswagen (DE) and Alberdi Mekanizatuak (ES)), serving as demonstrators of the project results.
Project Context and Objectives:
Meta-products comprise physical goods and physical services with emergent personal functionalities, which are based on the automated intelligent collection and processing of personal data as physical goods and services are used. As much of the value of meta-products resides in data in the Cloud, meta-products have great potential for international marketing and sales.
We are immersed in the wave of Factories of the Future. One the main topics is Servitization in industry 4.0. Servitization as a strategy to answer the pressure of the global markets in order to move the competition from costs to sophistication and innovation.
Nowadays manufacturers are forced to shift from their traditional product-manufacturing paradigm to the goods-services continuum by providing integrated combination of products and services. The adoption of service-based strategies is the natural consequence of the higher pressure that these companies are facing in the global markets especially due to the presence of competitors which operate in low wage region
The proliferation of new emerging technologies and paradigms together with a wider dissemination of information technology (IT) can significantly improve the capability of manufacturing companies to infuse services in their own products.
This can be enabled by making use of sensors and actuators already within existing physical goods; by adding them to existing physical goods; and/or by selling new physical goods. Technological developments from the EU ProSEco project enable the fulfilment of the huge marketing potential of meta-products by extending their scope and improving their technical performance.
The effective extension of products with new services in different sectors (automotive, home appliances, automation equipment, etc.) has been achieved by means of Ambient Intelligence (AmI) technology, Lean and Eco-design principles and applying Life Cycle Assessment techniques.
The objective of the ProSEco project has been to provide a novel methodology and a comprehensive ICT solution for collaborative design of product-services (Meta Products) and their production processes
ProSEco focuses on the capture and exploitation of customer side relevant information related to the use of the product or machine and its environment (by means of Ambient Intelligence (AmI) technology, context awareness, eco-impact assessment, etc.) to create better and new services in combination with the product (so-called servitization).This enables the creation of new business model providing more value to the customer, to rapidly response to the competitive economic climate and respecting the environment at the same time.
The Integrated ProSEco Prototype supports industries in collaborative design, development and management of new Product Extension Services (PES). It provides two working environments, the development and the deployment platform that requires different type of knowledge expertise and IT capabilities.
A Meta Product/process development platform has been provided, including a set of new engineering tools to support collaborative work (simulation, configuration, etc.) on new product-services, enhancing existing tools for product/process design. The platform is a set of set of ICT tools:
– Integrated Collaborative Development Environment
• Collaborative Portal, Eco-tool for impact assessment, Market Simulation Tool, Configuration of new Product Extension Services,.AmI Selection Tool, Data Mining Tool, Context Modelling Tool, Security Tool and Service Composition Tool.
– Integrated Runtime Deployment Platform
• to manage the execution of a Product Extension Services (PES) in the Cloud by using the Secure Runtime Infrastructure and a set of core services and application specific services.
A Methodology comprising a set of practical guidelines for organisations on how to develop Product Extension Services and how to prepare their business for introducing the Product Service System paradigm taking into account sustainability and eco-impact of the new services.
it’s described a ProSEco customer journey. It starts with the product virtualization, creating an avatar of the product/process. Then using the ProSEco Collaborative Platform the new PES is designed and created or (updated). The use of the new PES (i.e. Smart monitoring, remote diagnostic, etc.) is possible thanks to the Deployment Platform.
The entry point to design and create new services is the Collaborative Development Platform (Figure 3) that provides access to the product configuration or modelling, the engineering tools, and the workflow to design and create a new PES.
The project has been driven by four industrial application scenarios addressing different aspects of service and business building as well as product/process development (complex internal and external supply chains) in order to assure that the means for collaborative service generation and product-service and production process design developed in the project are relevant for industry.
Business Case scenarios are at:
• Volkswagen with personalised support to drivers to optimise energy use (in classical, hybrid and electrical cars)
• Electrolux with services to support consumer behaviour analysis and preventive maintenance of household appliances
• Desma with support remote condition based maintenance for shoe manufacturing machines
• ONA and Alberdi with lean–based design of eco–driven services around machines
The ProSEco project has adopted a generic approach for building Meta Products and their associated production processes, where the product/process design takes place through collaboration within the product ecosystem, involving multiple companies and actors and applying the Cloud Manufacturing (CMfg) concept.
Meta Products can now be built as a combination of so-called generic core services generic core services (applicable in various sectors) and application specific services, while new engineering tools from the project support product/process design and generation of these PES services involving collaboration of all stakeholders.
Project Results:
Description of main S & T results/foregrounds
The ProSEco project adopted the generic approach for building Meta Products and their associated production processes. The product/process design takes place through collaboration within the product ecosystem, involving multiple companies and actors, applying a Cloud Manufacturing concept.
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ProSEco project provides a methodology and a comprehensive ICT solution for collaborative design of PES, in particular:
• A new Collaborative eco-innovation design methodology to effectively take into account eco-relevant issues using eco-design principles through lifecycle assessment (LCA) techniques and Ambient Intelligent integrated already in the conceptual system design phase of Product Extension Services where lean product/process development principles can also be applied.
• ICT Collaborative environment system that supports industries in the design and creation of Product Extension Services (PES) from idea exploration to service deployment applying cloud computing approach and including a set of new engineering tools to support collaborative work and enhancing the existing tools for the product/process design.
4.1.1.1 Methodology
The methodology provides an innovative approach for using the ProSEco technologies to generate innovative PES solutions and build new business models. The methodology is an advanced composition of different guidelines:
• Methodology for collaborative product services & process design, comprising Methodology for Collaborative Product Services & Process Design, which includes guidelines on how to create and manage Virtual Communities, applying engineering tools developed within ProSEco project and Methodology for organisational / human aspects, including motivational issues to foster knowledge sharing and to overcome knowledge hoarding.
• Methodology for Lean-based ECO-driven Product-service & Process Design, applying the following paradigms:
o The lean principles in the design of Meta Products and production processes providing added value services considering individual demands.
o The eco-design and eco-innovation principles in the design of Meta Products for holistic understanding of enterprise sustainability and competitiveness, reducing environmental impact and the resources consumption during the production and during the overall product life cycle (promoting the use of more environmental-friendly materials).
Methodology for AmI based Context Sensitive Product-Services, defining how to use information from AmI solutions and other sensors embedded in products and other systems to generate various PES, and to provide guidelines on how to define context models needed for context sensitivity and personalisation of Meta Products.
These guidelines were combined into a single Integrated ProSEco Methodology,whose purpose is to serve as a guideline for industrial companies which intend to use for the first time the Integrated ProSEco platform to design new PES.
As it is showed in the following Figure 4, the Methodology for Collaborative Product Services and Process Design supports the whole ProSEco collaborative Platform by linking engineering tools with each specific phase of the development process and by integrating them seamlessly in the portal for the effective exchange of knowledge amongst geographically distributed teams. This methodology also determines actors’ association to their corresponding design activities, configuration of customized workflow process, and visualization of the status of development activities in a user interface.
The rest of the developed methodologies are linked to distinct phases of the development process and are linked to specific engineering tools in the following way:
• The Methodology for Lean-based eco-driven Product Services and Process Design guides the conceptualization and design of new product extended services (PES) by applying lean and eco-innovation principles in order to reduce environmental impact and the resources consumption during the production and during the overall product life cycle. This methodology is linked to the Eco and Configuration tools during the initial identification of environmental hotspots in different product systems configurations.
• The Methodology for AmI systems definition and selection guides the definition and selection of the appropriate sensorial information of the product that can be used to build effective PES, as well as provide basis for product development/enhancement. This methodology is linked to the amISelection tool that it is able to select different sensors from previous identified hotspot components to create an AmI Configuration needed for the new PES.
• The Methodology for Context Modelling and Context Extraction allows to investigate how context sensitivity can be used to achieve a high adaptability of products and PES. The context sensitivity allows for observation of changes in circumstances in which a product/PES is used, which in turn allows for a dynamic adaptation of the product/PES to these varying conditions. This methodology is linked to the context Modeling Tool to define, select and configure the context model which can be used within a PES to make it context sensitive, as well as to identify (extract) in real time the context under which the product/PES is used.
• The Methodology for Data Mining provides the guidelines on how data mining techniques and in particular machine learning algorithms can be integrated and used inside a PES to support the knowledge generation as well as the decision making process. This methodology is linked to the Data Mining Tool to easily enable the creation of data mining services that are responsible to analyze data extracted from the product for generating knowledge for the user in order to support and improve the decision making process.
Figure 4.: Integration of Methodologies and Tools linked to them (On the ProSEco Final Reportv1.doc)
The following sections explain each of the above methodologies by describing the customer experience journey and touch points where these methodologies help industrial companies to easily interact with ProSEco.
These methodologies are also helpful and applicable for companies which do not want to use ProSEco platform neither its components but intend to improve generation of new product extended services for their products.
Methodology for Collaborative Product Services and Process Design – ProSEco Collaborative Portal
Collaboration is the basis for bringing together the knowledge, experience and skills of multi-functional team members to contribute to the development of a new product more effectively than in the case of individual team members performing their narrow tasks in support of product development.
As it has been proven in ProSEco BCs the design, development and deployment of a new PES implies coordination and collaboration among many individuals including developers, designers, marketing staff, customer representatives, etc. therefore, collaboration among these actors is extremely crucial in order to synchronize the various system development activities. Therefore, the Methodology for Collaborative Product Services and Process Design methodology supports the whole collaborative ProSEco Portal by linking engineering tools with each specific phase of the development process and by integrating them seamlessly in the portal for the effective exchange of knowledge amongst geographically distributed teams. The methodology also helps actors from different domains to share ideas and create alliances to ensure convergence on a single PES design.
To do so we will follow the collaboration workflow (see figure below) to understand each phase, steps, tools and methodologies of the collaborative workflow to successfully created a new/updated PES from the discovery of the ProSEco Platform and user creation to the final PES Deployment in the cloud.
Figure 5: Collaboration Workflow (On the ProSEco Final Reportv1.doc)
The ProSEco collaborative portal contains the methodological skeleton to support the collaboration process. These are called Communication Services, Coordination Services and Cooperation Services. The collaborative development platform facilitates the users to either create a PES with a predefined/default workflow process or to configure a customized process. Therefore, to successfully collaborate through the whole ProSEco system an initial configuration setting need to be performed in the ProSEco portal.
Methodology for Lean-based Eco-driven Product Services and Process Design
The aim of this methodology is to provide a framework to facilitate the generation of innovative PES (product extension services) ideas together with the business strategy (business model) based on a combination of the physical product(s) and (in)tangible services(s) that fulfil specific user needs and requirements, taking into account the reduction of the environmental impact together with the competitiveness of the company and stakeholders; provoking a shift of behaviour from consumption (selling product) to use (selling function).
This methodology is supported (management of phases, steps & tools) by the Collaborative ProSEco portal. However, the methodology can also run independently from the ProSEco Portal and components. The following figure summarizes the whole customer experience journey when applying the lean-based eco-driven methodology for creation of new PESs.
Figure 6: ProSEco PES Conceptualization Journey (On the ProSEco Final Reportv1.doc)
Methodology for AmI systems Definition and Selection
This part of the ProSEco methodology is dedicated to the definition/selection of AmI systems within products and PES development. Modern industrial products and processes possess cyber physical features i.e. they are more and more equipped with different intelligent systems such as AmI systems. They normally include a number of sensors that may provide information about the product current state, use, manufacturing process etc. This information in turn can be used to build effective PES, as well as provide basis for product development/enhancement.
The aim of this methodology is to apply AmI systems as powerful source of information needed for PES to:
• Realize its key functionality
• Identify context of product-service use or to identify context under which the product is produced or used – needed to “personalise” product-services and make them context sensitive
• Identify environmental impact aspects
• Provide data for various data mining analysis such as identify usage patterns, environmental impact patterns etc. to be used for improved product/PES design and marketing
The method for definition/selection of AmI systems supports users to select AmI systems that should allow/support implementation of various PES and enhancement of the product itself.
The method specifically supports user in:
• Selection of AmI information for PES from AmI systems which are available at the product and/or processes where it is manufactured or where it is used
• Definition/selection of AmI systems which may be added to the product (and process) to meet the need of PES (and/or to enhance product itself) specification of processing of information from AmI systems for PES, i.e. definition of (low level) processing of data obtained from AmI systems (e.g. grouping, histograms, data binning, correlating of signals etc.)
Methodology for Context Modelling and Context Extraction
The aim of this part of the ProSEco methodology is to define how context sensitivity can be used to achieve a high adaptability of products and PES. The idea is make PES context sensitive. The proposed generic context sensitive solution can be easily adjusted to allow for adaptation of wide scopes of products and PES.
The context sensitivity allows for observation of changes in circumstances in which a product/PES is used, which in turn allows for a dynamic adaptation of the product/PES to these varying conditions. Context sensitivity is useful for products/PES used in dynamically changing conditions and various users (i.e. there is no sense to apply context sensitivity if PES is used under static conditions and/or all the user have same needs).
The assumption is that “normal/nominal” PES must operate without context sensitivity. Context sensitivity “only” improves the PES performance by better adapting it to dynamically changing situation/user current needs. Therefore, the context sensitivity is “only” add-on to PES but not basic functionality of the products/PES. Product/PES must have ‘nominal situation’ under which it operates without context sensitivity. For example, PES must be good for “normal/nominal” user of a refrigerator (e.g. homemaker) without special needs; context sensitivity ’adopts’ a service for “non-normal” user (e.g. a child or a partner who does not cook often).
The methodology (and the tool and the service) supports user (product or PES designer) to define/select/configure context model which can be used within PES to make it context sensitive, as well as to identify (extract) in real time the context under which the product/PES are used.
Methodology for Data Mining Tool
The objective of this part of the ProSEco methodology is to apply data mining techniques and machine learning algorithms to allow advanced services provided by manufacturers, beside the standard products. The analysis of data from the environment is vital from several points of view:
• Customer: the customer is the central point of any business and device. It is crucial to understand how she behaves, respectively to determine the behavioural patterns. Based on this, predictive and preventive maintenance can be done, in a transparent way.
• Supplier: As time is expensive especially nowadays, as well as storage facilities, just in time deliveries are crucial of good profits. Based on the size of the suppliers, their cultural and business habits, they need to be treated in different ways and this becomes very complex when we have to do supply chains.
• Device: the device itself undergoes technical changes and wears out. Although there are system theories determining the possible break outs stochastically, it is clear that each device behaves differently, as it is a blend of more components, each unique in its way. Therefore, variations from the mathematical model always appear. Therefore, it is important to determine the work patterns of the device for predictive and preventive maintenance.
• Environment: environment is not only the nature, but also the external factors. This influences the usage of any device, e.g. a football championship or a hot summer will result in an increase of beer consumption in Western countries.
Therefore the methodology serves as guidelines for companies that intend to apply data mining techniques and machine learning algorithms to their own products/processes - to the data extracted from products/processes – by using the ProSEco system. However, the methodology is also thought to be used by companies that do not want to apply the ProSEco system but intend to provide PESs.
4.1.1.2 ProSEco platform: ICT Collaborative environment system
The ProSEco Platform supports industries in collaborative design, development and management of new Product Extension Services (PES). The ProSEco platform is a fully functional and robust suite. It provides two working environments, each of which requires different type of knowledge expertise:
• Development platform, which is the set of integrated software modules used at PES design and development time.
• Deployment platform, composed by core services and other software modules required at PES deployment and execution time.
Figure 7. ProSEco architecture (On the ProSEco Final Reportv1.doc)
Both the collaborative development environment and deployment platform are integrated into a holistic common ProSEco solution by means of the use of Ontologies, a Knowledge Management Base and a Collaborative Portal all of which support the tasks to be carried out by PES design teams.
While all these software tools and core services can also be used independently and have their own functionality as standalone modules, they have been successfully integrated into a coherent software suite referred to as the ProSEco platform. The main integration pillars on which this integration has been conceptually based are:
• Ontologies: are in the base of many ProSEco software tools design. They are used as a technology-independent way to transmit results PES design related information from one software module to another. In other words, a common ontology shared amongst ProSEco modules ensures coherency when one module’s output is the next module’s input.
• Knowledge Management Base: successfully achieves the goal of empowering data and configuration sharing amongst ProSEco software modules.
• Collaborative Access Portal: is where ProSEco tools are linked and provides the operational environment for collaborations amongst PES design teams. Via this portal, ProSEco access control and PES workflow processes are conveniently integrated within a shared environment for all team members.
ProSEco provides a reference workflow for the development of new Meta Products. However, the solutions developed by ProSEco are also intended to update/upgrade/reconfigure existing Meta Products and PES and are able to adapt to existing workflows within manufacturing organisations, which may be quite different.
Beyond the workflow to create a PES there is a set of engineering tools and core services that are used in each of the workflow steps that enable dynamic composition of core services and application specific services adaptable to the different meta products and associated production processes in order to compose innovative PES solutions.
ProSEco generic workflow provides a sequence of steps that can be followed by PES design and deployment stakeholders to receive assistance in the creation of PES solutions as a combination of the core services and application specific services (development phase), and in the use of the PES services (deployment phase). The steps are briefly described below:
Figure 8. ProSEco generic workflow (On the ProSEco Final Reportv1.doc)
Idea creation: This initial part of the process will start with the analysis of the environmental performance of the current product-system reality (taking into account the whole life cycle perspective) in order identify improvement areas. Once the improvement areas have been identified, it is necessary to look for concrete needs/problems to be solved. With the help of ProSEco methodologies and other engineering tools, the stakeholders will conceptualize a PES solution as an extension to an existing meta-product or process to produce it. This PES solution will, e.g. turn the product-process into a more sustainable meta product, will reduce its time to market, will help the product comply with new environmental constraints, will solve some technical problems associated to the manufacturing process or will add some extra features to the product, such as data pattern analysis to improve future product designs or extended after-sales services, which will unleash innovative business opportunities that may derive in new business models supported by virtualization of meta-products under the Factories of the Future (FoF) frame.
Market Simulation: This step will comprise collaborative activities targeted at estimating the expected social impact derived from the introduction of a PES solution into the market as an extension to a new or an existing product
Knowledge Specification/Data mining: This activity will be leveraged to extract patterns of use, which can be used for the configuration of a PES or to improve future product designs by means of the application of appropriate feedback mechanisms
Data Capture/AmI sensors selection: This activity will configure the available sources of data that will feed the PES
Context Modelling: This step will enable ProSEco users to model the context for the PES using reasoning methods, enhancing AmI sensors monitoring and data contextualization
Security Configuration: This activity will enforce the applicable policies to restrict and protect PES data provision according to users’ data protection rules
PES orchestration: The outcome of the previous activities will be orchestrated so as to build a PES solution around a product / process
PES deployment: The PES will be deployed into a collaborative environment and used in runtime by the end-users as an extended service to an existing meta-product
The Integrated Development Platform is aimed to design and create in a collaborative way new Product Extension Services by using the following engineering tools:
1. Eco-tool for impact assessment
2. Market Simulation Tooll.
3. Configuration of new Product Extension Services
4. Engineering tool for definition/design of AmI solutions (also called AmI Selection tool)
5. Data Mining Tool
6. Context modelling engineering Tool
7. PES development Security Tool
8. Orchestration and Configuration of services: Configuration of Services and Service Composition Engineering Tool
The Deployment Platform to manage the execution of a Product Extension Services in the Cloud by using the following Key modules:
1. Secure Runtime Infrastructure
2. Deployment Platform Configuration Tool
3. Service Registry
4. Core Services
5. Application Specific Services
6. Deployer: Data Access Layer and Service Broker
A description of the above components is given below.
4.1.1.3 Development Platform: engineering tools
1. Eco Tool For Impact Assessment
The Eco-tool takes part in the ProSEco Integrated Development Environment by means of providing lifecycle assessment calculation capabilities so as to leverage the environmental perspective in the Product Extension Services (PES) creation process. In this context, the Eco-tool tool is used to configure the Eco Core Service that will be run by the service broker during the PES deployment phase.
2. Market Simulation Tool
The purpose of the Market Simulation Tool in ProSEco is to enable easy modelling of the complex market contexts of PESs during their design when using the ProSEco Platform.
The Market Simulation Tool is based on extensive critical review of qualitative and quantitative scientific literature related to consumer and market behaviour.
It allows industry partners to simulate the meta product offerings in dynamic business ecosystems in order to explore / test effects of alternative offering designs within different business ecosystems
3. Configuration of new Product Extension Services
One of the key issues regarding Product Extension and Services design and execution is their configuration, that is to say, their parameterization and value-specification required to ensure their correct designing inside the engineering tools and their correct execution inside the deployment platform.
The Configuration Tool enables industry partners to design products and its associated extension services (PES), in a cloud-based collaborative environment, while incorporating eco-design methodologies and rules
4. Engineering tool for definition/design of AmI solutions
This solution supports the user in setup and monitoring of AmI systems / sensors needed to build PES in a simplified way, allowing for a transparent way to select and monitor sensor data from products.
Engineering tool for definition/design of AmI solutions allows effective selection of the AmI systems already integrated (or, to be integrated) in the product, allowing for provision of PES, as well as extraction of context on product-service use following the above explained methodology approach. The tool supports the designer in selecting/designing of AmI and other measurement systems and appropriate extended monitoring.
5. Data Mining Tool
The Data Mining Tool allows the configuration of a data mining process to be integrated in a PES during its design/definition. In particular, it provides the possibility to model a data mining process by first selecting the necessary parameters to be analysed/processed (e.g. data collected from the environment and the context extracted), selecting the processing algorithm, and finally, the target value. The tool enables the building of several PESs such as decision support services (e.g. schedule proactive maintenance activities), PES to provide the consumer behaviour when interacting with the product/process for detecting misuses and/or adapting the internal parameters of the product/process. It provides data mining techniques for analysing AmI data to allow industry partners to understand and detect customer and supplier behaviour that can be used to enhance their offerings
6. Context modelling engineering tool
The engineering tool supports the definition/design of context sensitive PES by allowing to model the product/PES use context. The context model describes circumstances under which a product is currently used, and by this allows adjustments of PES to dynamically meet specific needs of the users of the products. The context model is set of concepts and their relations which describe circumstances under which the product/PES is currently used.
7. PES Development Security Implementation
The security approach is based on the concepts of the Next Generation Access Control (NGAC) standard (INCITS 499, 2013). This entails a functional architecture for access control that localises policy and security decisions and potentially distributes enforcement. In ProSEco, the functional architecture is realised by several components: policy information is stored in the meta-data about PES objects used by the Node.js/Express framework and the PES service composition used by the Service Broker. The ProSEco Portal and Service Broker act as trusted policy enforcement points, and APIs are provided for enforcing security policies for application access requests.
8. Orchestration and configuration of services
PES that are meant to be deployed into the ProSEco Deployment platform are required to be structured and encompassed in a software solution that contains all the information required for the PES execution. This orchestration for deployment encompasses the Configuration of Services and the Service Composition Engineering Tool. the information required for the PES execution. This orchestration for deployment encompasses the Configuration of Services and the Service Composition Engineering Tool.
o Configuration of Services
Along the workflow of a PES development, PES Designers access a set of engineering tools that assist on the idealization and parameterization of the PES. Among these Engineering Tools persist the ones that enable to parameterize each of the Deployable Services selected for the deployment, by means of producing a configuration data structure to be passed and interpreted by the respective service that will be used in the deployment.
In order to make these configuration files reusable by other components, they co-exist in the system has hybrid files, possessing both specific and generic fields. The specific fields contain the parameterization which the service will receives and uses for self-configuration, while the generic fields are used for several tasks of the PES development and deployment, such as recognition of the respective type of service and to incorporate the data model that is associated to the produced results of the service, which is used in the interoperability of the PES execution. This enables the configuration to be read by other components and that it can be forwarded to the tight service on the PES deployment.
o Service Composition Engineering Tool
The Service Composition Tool supplies an easy to use Graphical User Interface, compliant with BPMN standard, allowing the PES Tools. The composition of different ProSEco Core Services and application specific services is representing the PES. ProSEco offers following core service templates for rapid prototyping using the ProSEco engineering tools:
• AmI Monitoring: used for collection and aggregation of AmI systems/sensors (at the product/process) raw data into AmI based data.
• Context Extraction: used for extract context during daily product use operation, and to provide the extracted context to the downstream services.
• Knowledge Provision: enable the gathering of relevant knowledge about costumer that can be used for developing new and more accurate PES solutions.
• Security enforcement: inspects, modifies, and queries the policy database, resource managers for each host that provides protected resources, session managers for each user initiated session, and session initiation functions within the ProSEco platforms
• Eco core service: allows the impact assessment calculation, following the single score approach provided by “endpoint” impact calculation methods.
• Data Mining core service: analyses the behaviour of the providers and customers or to predict future events, such as the proper times for predictive maintenance.
PES designers are able to elaborate the Orchestration/Choreography of the services used on a PES. A Graphical User Interface enables the definition and parameterization of the PES data flows between the operating services in use on the deployment, as well as the ability to combine all features of the PES into a unique software Solution while connecting and sending it into the deployment Environment.
The stored Configuration files are retrieved and used to identify the services in use, as the Tool set up the working environment. Then the user may use the graphic blocks, by means of a Drag & Drop technique, to connect the services in the desired workflow of data portended to occur while the PES is executing.
4.1.1.4 Deployment Platform
In close association to the PES Deployment platform is a software solution which provides the automatized mechanisms to deploy the designed PES. Based on a Service Oriented Architecture, several modules and components have been developed and integrated in the deployment platform, for which the combined functionalities provide a full and comprehensive structure. The main modules that have been developed are:
• Secure runtime infrastructure: Provides an environment for security of services deployment, communication and invocation.
• Deployment Platform Configuration tool, provides a way to specify the physical data for each service effective deployment, such as IP and port.
• Service Registry: provides a registry where all the services/functionalities inside the ProSEco system could register. Therefore, such component is responsible to maintain a list with all the services/functionalities available over the network that can be potentially used in the design and development of PES solutions.
• Core Services: defines a set of services with generic functionality, which can be easily adopted for specific needs and combined to create/update PES solutions, and can be easily adapted to the individual user needs. Core Services are templates of deployable services, easily configurable through ProSEco Engineering
• Deployer: provides the mechanism and the necessary dynamics for enabling the register of all the services/functionalities. It is capable to manage and handle the communication with the Service Registry component whenever a service is started/stopped. Therefore, it is responsible to (un-)publish services/functionalities
o Data Access Layer: provides an isolated and trusted communications link to the several Repositories enabling each of the services/functionalities (core and application specific) to securely store data in the required format along with authentication mechanisms to ensure data integrity for future references by the components of the ProSEco solution.
o Service Broker: represents the mediator that enables the connection between the designed PES solutions: connecting all the resources in use for a PES, while passing all the specifications necessary for the PES execution are made by means of an agent-based system which controls all the PES Setup and Execution processes while a PES is deployed.
Figure 9: Overall picture of the ProSEco runtime environment and communication between components (On the ProSEco Final Reportv1.doc)
Application Specific Services: defines a set of specific functionalities (or processing components), which can be embedded in the products and combined to create/update PES solutions. These functionalities depend on the particular application context meaning that each one of the application scenarios may have one or more applications specific services that make sense only in that particular scenario
4.1.1.5 ProSEco Business Cases
ProSEco prototype development has been driven by four application scenarios lead by the industrial partners that also form the business cases that have been used to validate the project technologies:
• Volkswagen with personalised support to drivers to optimise energy use (in classical, hybrid and electrical cars)
• Electrolux with services to support consumer behaviour analysis and preventive maintenance of household appliances
• Desma with support remote condition based maintenance for shoe manufacturing machines
• ONA and Alberdi with lean–based design of eco–driven services around machines
Each of these is described in the following sections.
4.1.1.5.1 Business case Volkswagen
Volkswagen as an automobile OEM, aims to offer telemetric und online services to their vehicles in order to improve the experience of owing a Volkswagen. A Volkswagen vehicle contains, depending on model, more than 4000 signals exchanged by the ECUs (Electronic Control Units) and communicate over CAN bus every 10ms. Today these signals are used only inside the vehicle to control the functionality and vehicle behaviour but are interesting to pro-vide new telemetric and online services around the vehicle. ProSEco supports the development and provision of such new services about driver and driving behaviour, vehicle and vehicle behaviour and vehicle environment.
ProSEco provides the engineering tools to support Volkswagen in the preparation and selection of the signals that best fit the numerous Product Extension Services that can be obtained and provided with the vehicle signals. Furthermore, it provides core services and facilities for fast deployment of PES.
One important issue is that all data (signals) is owned by the vehicle owner. Therefore, the vehicle owner has to accept and allow the gathering und usage of signals for services. The access and authorization to the data use is also ensured by a ProSEco engineering tool. The PESs developed to demonstrate the ProSEco solution are Eco-Driving Monitor and Pollution Monitor for public administration.
Innovation: Enabling of third party service providers to build apps around vehicle data and possibility of cross sectorial service development (e.g. weather service using vehicles as mobile weather stations)
Benefits—External Business, Participating on new 3rd party business (as part of the value chain) , Internal Rapid prototyping, Short evaluation of service ideas
Figure 10: Example of the Fuel Consumption Eco-Monitor PES (On the ProSEco Final Reportv1.doc)
4.1.1.5.2 Business case ELECTROLUX
The objectives of Electrolux within ProSEco have been to develop services for:
Consumer behaviour analysis — to be able to analyse all data coming from the monitored appliances. This analysis will enable ProSEco to model the customers’ behaviours according to their usage of the devices;
Preventive and Predictive Maintenance — ProSEco will, instead of finding trends in the user’s behaviour, provide historical information on the components behaviour. Ultimately, this analysis will enable ProSEco to find, predict and prevent problems that may occur in a component within the devices.
The environment taken into consideration is:
• Physical — where the actual devices rest. These devices are the source of the data that will be analysed within ProSEco;
• Cyber-Physical — the limbo environment where both the physical and the virtual world meet. It is where the data is received from the devices and pro-cessed into the ProSEco environment;
• Advanced Support — the environment where the PESs run. Here the data is processed, stored and analysed using a mix of core services within the ProSEco environment and specifically developed ones.
In the future Electrolux believes that connected appliances offer a possibility for a lifelong relationship between the company, as a manufacturer and the user of its products. Moving beyond the user’s behaviour understanding and predictive maintenance, connectivity makes it possible to offer personalized, value added services in a way the appliance industry has never seen before.
To that end, Electrolux is taking a holistic approach to developing connected appliances throughout the entire ownership experience, in order to create lifelong relationships with consumers. For example, taking into account relevant user data, it will not just be able to help users cook a meal like a professional, it will be possible to suggest the ingredients and order them according to the preferences.
Figure 11: Connected appliances (On the ProSEco Final Reportv1.doc)
4.1.1.5.3 Business case DESMA
DESMA provides production machines for the shoe industry. Their motivation in ProSEco was a totally improved maintenance service system for their complex production and automation systems that uses as information basis: 1) influencing ambient environment information; 2) data directly from the manufacturing systems (ISA’95 Level 1-3); and 3) data from operators (e.g. technical and maintenance reports). ProSEco was a suitable project to focus these challenges.
The figure below side shows the result of using ProSEco in DESMA: A configured DESMA PES, which is deployable on several production systems and reachable from everywhere. The PES provides classical monitoring, historical data, machine meta data, context information, predicted data, and pattern management, observation and matching information/functionalities from/for their machines. These information and functionalities are further exploited by Service Report Management, Solution Search Support and Remote Diagnostics applications for the improvement of their maintenance service system.
For DESMA ProSEco shows a high business potential of PES for machine builders like DESMA. ProSEco PES development accelerates traditional machine service and cuts down costs by making relevant service mission specific information instantly available to all resources. Avoided international technician travel not only minimizes loss of production and wasted material but also CO2 emission for people transport. ProSEco allows DESMA to fully exploit the meta products concept by lean development, test and management of new PES ideas. DESMA is now in a position to drastically increase the number of PES products combined with shortened time to market.
Figure 11:. Access to new PES (On the ProSEco Final Reportv1.doc)
4.1.1.5.4 Business case ONA and ALBERDI
The current Premium Series of ONA EDM machines are equipped with a new Smart CNC that intends to accomplish the “Industry 4.0” paradigm because some of the most disruptive improvements and changes in the Machine Tool industry are expected to come from the digitalization concept.
The new demands for customized products and flexible production EDM processes have motivated research initiatives in a manufacturing data driven concept that requires converting machines in cyber-physical systems. As running costs of EDM machines over the lifetime can be even higher than the initial investment costs, one of the main targets for ONA in ProSEco was to design new advanced services with the focus on the product usage. In this context, the proposed Eco-driven methodology applied to the life cycle of ONA machines has helped to define two PES:
• A cloud based Smart Monitoring concept service for fleet of machines. The interest here has been to:
o analyse Machine-Cloud infrastructure for SMEs
o check how data analytics could help to improve the product performance and its maintenance.
o extend the machine functionality according to an Industry 4.0 strategy in Manufacturing (new Smart controller concept).
o improve the current capabilities of ONA Turnkey Solutions at SME scale.
o explore new business support services that can be offered to the final customer. This is the case of maintenance service contracts based on machine availability targets or fixed cost requirements. Another opportunity is to support customer in optimizing entire process chain and maximizing OEE.
• A Trace-ability service for the EDM process. The selected manufacturing data define a part signature concept that can be used in quality certification. This information can be the input for data analytics techniques that could make possible to:
o generate new indirect sensors (part thickness estimation, for instance)
o register and quantify quality deviations from a nominal value
o identify potential machine improvements and feed them back to the design teams
o contribute to the LCA and ECO impact assessment of the machinery
o improve consumables management and energy efficiency (sustainability)
Figure 13 Cloud based Smart Monitoring concept service (On the ProSEco Final Reportv1.doc)
The objectives of ALBERDI at ProSEco are:
• To improve the parts production management system by being able to analyse different manufacturing alternatives and to choose the one that best fits the customer preferences, taking into account: mechanical costs, delivery time or environmental impact of each of the manufacturing processes
• To provide a better collaborative service-offer to their customers taking into account customers’ requirements such as geometry, raw material and other characteristics of the part
Figure 14: Alberdi Customer requirements: material, geometry, draws design (On the ProSEco Final Reportv1.doc)
Potential Impact:
Potential impact and main dissemination activities and exploitation results
Potential impact
The application of the ProSEco solutions improves efficiency of creating new business models based on services around products. The ProSEco solution allows imagining and building innovative scenarios for eco-friendly industries and low-carbon economy (e.g. for Full Electric Vehicles (FEV) in BC1 (Volkswagen), reduced energy consumption in BC2 Electrolux etc.).
ProSEco platform (core services and engineering tools, and methodology) provides the following impacts within the specified business case (BC) scenarios:
1. Reduction of time and efforts needed for development/update of Meta Product and associated product processes
2. Increase in number of innovative personalised PES
3. Reduction of time to market
4. Reduction of energy consumption through new PES
5. Cost reduction for Support Services (improvement in relation to currently provide services)
6. Reduction of ramp-up time within the associated manufacturing processes
The communities most likely to benefit from ProSEco results are:
- Manufacturers in different traditional sectors (first target is automotive, machine industry but also other traditional sectors such as metal industry as direct customers/partners of the five industrial partners: VW, ELECTROLUX, DESMA, ONA, ALB). The consortium includes partners from automotive sector and home appliances sector having leading role in developing Meta Products, but also partners from machine sectors (aiming to provide transfer of the advanced approaches into other sectors.
- Manufacturers of industrial installations: equipment, automation and electronic devices (where PES plays an important rule to establish new business models).
- ICT community (SW and service providers – both large and small, where SEM belongs). The project will provide also benefits for ICT vendors involved in product extensions, i.e. provision of services. Especially smaller ICT vendors will get opportunity to provide new/updated services to their customers – manufacturing companies which want to install new PES or improve their existing PES. Based on the proposed approach they will be able to realise faster and more efficient customisation for their clients, thus enabling a smooth transition from the current service provision to new PES which can be cost-effectively applied at the global market
- Customers of industrial partners (i.e. DESMA, ONA).
ProSEco specific impacts within Business Cases:
1. Integrate knowledge from customers and product usage patterns. A way for Understanding:
a. Users (in aggregate way but properly clustered – e.g. ethnographic assessments);
b. Appliances (in aggregate way but properly clustered – e.g. preventive maintenance);
2. A way to provide Hints ( to improved «User Experience»)
a. to Consumers (eco behaviors, preventive maintenance)
b. To the Company (specification of future products)
3. Automated and remote recording and analysis of machine sensor data for evaluation and prediction of machine status
a. early identification of significant problems
b. reduced time/costs for problem solution
c. avoidance of production stops (solve problem prior to becoming critical)
4. To extend the machine functionality according to Industry 4.0 strategy in Manufacturing
5. Exploring business opportunities based on services.
6. Accelerating innovation and design cycles: Rapid prototyping, evaluation of service idea
7. Minimise the environmental burden of production and consumption (towards a eco-industry and circular economy)
Beyond the impact in the industrial community, ProSEco has provided:
- S&T Impact: The project provides solutions on how to apply eco-driven design principles, in combination with lean principles, for collaborative design of Meta Products and their production processes, and on how to extract context from AmI solutions integrated in the product and processes and use it for highly adoptable and reconfigurable services. ProSEco shows how AmI technology and context sensitiveness can be used as an enabler for easy adoption and personalisation of product extension services. Business cases, scientific papers and Exploitable results have been issued to present and support the results of the project (see sections 4.1.4.1 and 4.1.4.2 for the main results, section 0 for more detail information)
- Socio-economic impact: Using the project results to optimise Meta Products design in industry allows for considerably higher productivity and more effective, establishment of new business models, and faster responses to the market requirements (as Industrial partners have stated), thereby improving competitiveness and business development of manufacturing industry. On the other hand, ICT and industrial vendors are able to offer new services to their customers, also enabling European industry to reinforce its major strengths in the innovative PSS solution. This will have on medium and long-term a direct positive benefit for employment, as the companies use the improved competitive position to build up further business.
- Quality of life: The project makes significant contribution to generation of PES for various products, radically improving their usability (based on context sensitive approach). This can be seen in all BC, but especially in B2C Business Cases as in BC2 where the higher quality of PES improves customer experience and hence their satisfaction
- Environmental impact: The environmental impact of Meta Products based on the new platforms, core services and engineering tools, and methodology are a reality as shown in business cases using eco-tool and eco-impact assessment as in BC4
The ProSEco tools and methodologies will be used by partners as an easy to use tool for prototyping new PES. Having a rapid prototyping tool is already something of great value because it allows showing real performances and not a static presentation with hard numbers. Such a demonstrative process can help in taking decisions which is the most critical issue before a production commitment is to be made. This represents a new paradigm in industrial processes: moving from a pure product concept to a PES concept it’s something that it’s not easy to grasp at first but that steers interest once it’s understood or seen in action.
This approach is completely aligned with latest Industry 4.0 trend and therefore ProSEco could and should be marketed as part of Industry 4.0 activities.
Main dissemination activities
During the project execution period, the ProSEco partners performed many dissemination activities for the public in general (both RTD and industrial audiences) in:
- Conferences (e.g. IEEE INDIN 2014, CEC 2015, IPSS 2016, ProVE 2016, Smart Cities Conference 2016, ICE 2017, IEEE INDIN 2017, FedCSIS 2017)
- Workshops in international conferences (some co-organized with other projects ),
- industrial fairs (BIEMH 2014, RTEX 2014, Subcontratación 2015, RTEX 2015, EMO Milano 2015, DESMA house fair 2016, IMTS 2016),
- journal articles (e.g. in Journal of Consumer Culture, IJACSA, Planet Lean, International Journal of Communications, Network and System Sciences, Journal Sensors),
- EC organised events (e.g. project results presentation at Factories of the Future Conference 2016 Materialising Factories 4.0)
- User interest groups (e.g. in Germany, East European countries, Portugal, UK)
- Newsletters (4 ProSEco newsletters as well as articles in Lean Global Network, or the LEI newsletter),
- Others (e.g. presentation to the Steering Committee of the IoT Working Group under the Platform 3.0 Forum or project description and results were introduced in the EFFRA portal)
The complete overview of these activities can be seen in Table 7.
The ProSEco dissemination activities were intensive from the beginning of the project in terms of presenting basic ideas within RTD and industrial communities, followed with results presentation.
Exploitable Results
The main exploitable result of the project is the ProSEco platform, with the main components of this platform having also been identified as exploitable results by themselves.
Exploitable results, which is as follows:
• Result 1 : ProSEco Collaborative Development Platform
• Result 2 : Lean Consultancy
• Result 3 : Eco Tool, Service and Methodology
• Result 4 : Simulation tool
• Result 5 : Data-mining Tool and Services
• Result 6 : AmI Selection tool, monitoring services and Methodology
• Result 7 : Context Modelling tool, extraction services and Methodology
• Result 8 : Knowledge Provision core service
• Result 9 : Security Tool/Enforcement services
• Result 10 : ProSEco Deployment Platform
Table 1: Overview of the ProSEco results
4.1.1.1 Potential impact
The application of the ProSEco solutions improves efficiency of creating new business models based on services around products. The ProSEco solution allows imagining and building innovative scenarios for eco-friendly industries and low-carbon economy (e.g. for Full Electric Vehicles (FEV) in BC1 (Volkswagen), reduced energy consumption in BC2 Electrolux etc.).
ProSEco platform (core services and engineering tools, and methodology) provides the following impacts within the specified business case (BC) scenarios:
1. Reduction of time and efforts needed for development/update of Meta Product and associated product processes
2. Increase in number of innovative personalised PES
3. Reduction of time to market
4. Reduction of energy consumption through new PES
5. Cost reduction for Support Services (improvement in relation to currently provide services)
6. Reduction of ramp-up time within the associated manufacturing processes
The communities most likely to benefit from ProSEco results are:
- Manufacturers in different traditional sectors (first target is automotive, machine industry but also other traditional sectors such as metal industry as direct customers/partners of the five industrial partners: VW, ELECTROLUX, DESMA, ONA, ALB). The consortium includes partners from automotive sector and home appliances sector having leading role in developing Meta Products, but also partners from machine sectors (aiming to provide transfer of the advanced approaches into other sectors.
- Manufacturers of industrial installations: equipment, automation and electronic devices (where PES plays an important rule to establish new business models).
- ICT community (SW and service providers – both large and small, where SEM belongs). The project will provide also benefits for ICT vendors involved in product extensions, i.e. provision of services. Especially smaller ICT vendors will get opportunity to provide new/updated services to their customers – manufacturing companies which want to install new PES or improve their existing PES. Based on the proposed approach they will be able to realise faster and more efficient customisation for their clients, thus enabling a smooth transition from the current service provision to new PES which can be cost-effectively applied at the global market
- Customers of industrial partners (i.e. DESMA, ONA).
ProSEco specific impacts within Business Cases:
1. Integrate knowledge from customers and product usage patterns. A way for Understanding:
a. Users (in aggregate way but properly clustered – e.g. ethnographic assessments);
b. Appliances (in aggregate way but properly clustered – e.g. preventive maintenance);
2. A way to provide Hints ( to improved «User Experience»)
a. to Consumers (eco behaviors, preventive maintenance)
b. To the Company (specification of future products)
3. Automated and remote recording and analysis of machine sensor data for evaluation and prediction of machine status
a. early identification of significant problems
b. reduced time/costs for problem solution
c. avoidance of production stops (solve problem prior to becoming critical)
4. To extend the machine functionality according to Industry 4.0 strategy in Manufacturing
5. Exploring business opportunities based on services.
6. Accelerating innovation and design cycles: Rapid prototyping, evaluation of service idea
7. Minimise the environmental burden of production and consumption (towards a eco-industry and circular economy)
Beyond the impact in the industrial community, ProSEco has provided:
- S&T Impact: The project provides solutions on how to apply eco-driven design principles, in combination with lean principles, for collaborative design of Meta Products and their production processes, and on how to extract context from AmI solutions integrated in the product and processes and use it for highly adoptable and reconfigurable services. ProSEco shows how AmI technology and context sensitiveness can be used as an enabler for easy adoption and personalisation of product extension services. Business cases, scientific papers and Exploitable results have been issued to present and support the results of the project (see sections 4.1.4.1 and 4.1.4.2 for the main results, section 0 for more detail information)
- Socio-economic impact: Using the project results to optimise Meta Products design in industry allows for considerably higher productivity and more effective, establishment of new business models, and faster responses to the market requirements (as Industrial partners have stated), thereby improving competitiveness and business development of manufacturing industry. On the other hand, ICT and industrial vendors are able to offer new services to their customers, also enabling European industry to reinforce its major strengths in the innovative PSS solution. This will have on medium and long-term a direct positive benefit for employment, as the companies use the improved competitive position to build up further business.
- Quality of life: The project makes significant contribution to generation of PES for various products, radically improving their usability (based on context sensitive approach). This can be seen in all BC, but especially in B2C Business Cases as in BC2 where the higher quality of PES improves customer experience and hence their satisfaction
- Environmental impact: The environmental impact of Meta Products based on the new platforms, core services and engineering tools, and methodology are a reality as shown in business cases using eco-tool and eco-impact assessment as in BC4
The ProSEco tools and methodologies will be used by partners as an easy to use tool for prototyping new PES. Having a rapid prototyping tool is already something of great value because it allows showing real performances and not a static presentation with hard numbers. Such a demonstrative process can help in taking decisions which is the most critical issue before a production commitment is to be made. This represents a new paradigm in industrial processes: moving from a pure product concept to a PES concept it’s something that it’s not easy to grasp at first but that steers interest once it’s understood or seen in action.
This approach is completely aligned with latest Industry 4.0 trend and therefore ProSEco could and should be marketed as part of Industry 4.0 activities.
4.1.1.2 Main dissemination activities
During the project execution period, the ProSEco partners performed many dissemination activities for the public in general (both RTD and industrial audiences) in:
- Conferences (e.g. IEEE INDIN 2014, CEC 2015, IPSS 2016, ProVE 2016, Smart Cities Conference 2016, ICE 2017, IEEE INDIN 2017, FedCSIS 2017)
- Workshops in international conferences (some co-organized with other projects ),
- industrial fairs (BIEMH 2014, RTEX 2014, Subcontratación 2015, RTEX 2015, EMO Milano 2015, DESMA house fair 2016, IMTS 2016),
- journal articles (e.g. in Journal of Consumer Culture, IJACSA, Planet Lean, International Journal of Communications, Network and System Sciences, Journal Sensors),
- EC organised events (e.g. project results presentation at Factories of the Future Conference 2016 Materialising Factories 4.0)
- User interest groups (e.g. in Germany, East European countries, Portugal, UK)
- Newsletters (4 ProSEco newsletters as well as articles in Lean Global Network, or the LEI newsletter),
- Others (e.g. presentation to the Steering Committee of the IoT Working Group under the Platform 3.0 Forum or project description and results were introduced in the EFFRA portal)
The complete overview of these activities can be seen in Table 7.
The ProSEco dissemination activities were intensive from the beginning of the project in terms of presenting basic ideas within RTD and industrial communities, followed with results presentation.
4.1.1.3 Exploitable Results
The main exploitable result of the project is the ProSEco platform, with the main components of this platform having also been identified as exploitable results by themselves.
Exploitable results, which is as follows:
• Result 1 : ProSEco Collaborative Development Platform
• Result 2 : Lean Consultancy
• Result 3 : Eco Tool, Service and Methodology
• Result 4 : Simulation tool
• Result 5 : Data-mining Tool and Services
• Result 6 : AmI Selection tool, monitoring services and Methodology
• Result 7 : Context Modelling tool, extraction services and Methodology
• Result 8 : Knowledge Provision core service
• Result 9 : Security Tool/Enforcement services
• Result 10 : ProSEco Deployment Platform
Table 1: Overview of the ProSEco results
LEADER PARTNER NAME
1.ProSEco Collaborative Development Platform
The ProSEco collaborative development platform provides a web-based technical framework that can be used to integrate a variety of dynamic engineering tools and the core services. This facilitates seamless exchange of valuable knowledge across whole network of actors involved in the creation of Product Extended Services (PES).
Depending on the organization’s demands and needs, the ProSEco collaborative development platform is reconfigurable to adopt a new business environment. For instance, only the necessary subset of the tools that are required in a particular enterprise can be provided. The tools that are available in the platform are:
Eco-tool
Customer and Supplier behaviour (Data Mining Tool)
Tool for the simulation of Meta Products
Tool for definition / design of AmI solutions
Context Modelling Tool
Configuration Tool
Security tools
Service Composition Engineering Tool
These set of tools are available with their complementary core services inside the platform. Apart from core services, the ProSEco collaborative development platform is capable for providing a space to configure the available services with application specific services during the design and development phase.
Leader partner name University of Salford (USAL)
2. Lean Consultancy
Gemba Analysis is a method for identifying potential for innovation in terms of functionalities and services that a product contains. It is focused on the user of the product (for example a machine operator for a CNC machine or a driver for a car). Gemba Analysis is a method of observation of the use of the product and its services in the real place (gemba). It is based on mature Lean Management tools like Standardized Work, TWI-Job Methods, Value Stream Mapping, Consumption Stream Mapping, Go-See-Act and A3 Reports.
Leader partner name LEI
3. Eco Tool, Service and Methodology
This result encompasses a software tool – Eco-tool- (Eco monitoring Engineering tool and the optimization core service and a methodology for Lean-based ECO-driven Product-service & Process Design.
The eco-tool provides users with simplified collaborative product system modeling features and provides LCA techniques that facilitate the rapid calculation of environmental impacts.
The methodology provides a new framework to guide the conceptualization and design of new PES solutions (product extension services) together with the business strategy (business model) that fulfill the user needs, taking into account the reduction of the environmental impact together with the competitiveness of the company and stakeholders; provoking a shift of behavior from consumption (selling product) to use (selling function )
Leader partner name TEC
4. Simulation tool
Web-based Market Simulation Tool enables easy modelling of the complex market contexts of PESs during their design when using the ProSEco Platform.
The Market Simulation Tool is based on extensive critical review of qualitative and quantitative scientific literature related to consumer and market behavior.
It allows industry partners to simulate the meta product offerings in dynamic business ecosystems in order to explore / test effects of alternative offering designs within different business ecosystems
Leader partner name VTT
5. Data-mining Tool and Services
The result consists of a service able to do data mining (mainly predictions) on data gathered from a series of sensors (AmI).
The core service can be used for predicting any data/time series based on some previous n-tuples of values and outcomes. The specific service can be created using the engineering tool.
Leader partner name CNU
6.AmI Selection tool, monitoring services and Methodology
The AmI Selection engineering tool supports the PES designer in the selection/definition of which AmI systems/sensors are needed for the PES being created.
The core service support the user of the PES in the collection and aggregation of AmI systems/sensors (at the product/process) raw data into aggregated AmI based data.
The result is accompanied by a methodology to support the user in selection of AmI systems/sensors at the product and process to be used within PES.
Leader partner name ATB
8. Context Modelling tool, extraction services and Methodology
This result supports the Context Modelling and allows to Monitor and Extract the context of the situation where the PES is being used and by this improve the performance of PES (automatically adapt the PES outputs to the specific context under which the PES or product is used).
Leader partner name ATB
9. Knowledge Provision core service
Provides search over several types of repositories such as Wiki, ERP, data repositories which can be integrated in PES Leader partner name ATB/UNINOVA
9. Security Tool/Enforcement services
A security toolset and deployment framework that includes the following:
-Language for the specification of user and resource attributes and security policies
-Tools to build security database of user attributes and access control policies
-Identification and authentication functions
-Building blocks for distributed reference monitors to enforce the specified access control security policies
-Language for the description of the PES security architecture
-Tools to analyse the high-level security architecture of the PES and to identify the appropriate placement of security building blocks to enforce the specified security policies
-Package of cryptographic primitives needed to implement data protection and security protocols
These provide a framework for ensuring the security of new PES systems and providing required levels of privacy of user data and trust in system operations.
Leader partner name TOG
10. ProSEco Deployment Platform
The ProSEco Deployment Platform provides a SOA based SW Solution of independent modules that support both hosting of resources (i.e. WebServices) specifically developed to perform and fulfill the objectives of ProSEco as well as a Service Broker, specifically designed for the runtime of the PES.
The Service Broker module is the core of the PES Deployment Platform & Service Composition specifically it is the runtime engine for the execution of PES applications. It is an agent-based tool compliant with the FIPA standard. It has been designed and implemented to consume BPMN processes and to allocate the necessary resources for the execution of the PES.
The Service Composition Tool enables the parametrization of the relations and runtime specifications between the resources, under BPMN notation. Also it sets the communication point between the Development and Deployment Platforms.
Leader partner name UNI
List of Websites:
ProSEco contact details and project website
A project web site (http://www.proseco-project.eu/) was established at the beginning of the project to provide wide dissemination of the results, papers, and information in general about the project.
The website offers updates on:
• events,
• newsletters (4 newsletters made along the project lifecycle and available at the project website and distributed by the partners at events),
• news,
• publications (information on the conferences and journals publications and access link to the open access publications),
• videos as e.g. https://www.youtube.com/watch?v=vIZgoD1ky2U and the project demonstrator videos (https://www.proseco-project.eu/project-realisation) and
• newest downloads. All public deliverables are available on the website.
-Fundación Tecnalia Ana Arroyo (Proyect Coordinator) (ana.arroyo@tecnalia.com) Spain
-Institut für angewandte Systemtechnik Bremen GmbH Sebastian Scholze (scholze@atb-bremen.de) Germany
-Instituto de Desenvolvimento de Novas Tecnologias José Barata (jab@uninova.pt) Portugal
-Technical Research Centre of Finland - Business from technology Stephen Fox (Stephen.Fox@vtt.fi) Finland
-Universitatea Tehnica din Cluj-Napoca Oliviu Matei (oliviu.matei@holisun.com) Romania
-University of Salford, Manchester Terrence Fernando (T.Fernando@salford.ac.uk) UK
-Lean Enterprise Institute Polska Stanislaw Plebanek (stanislaw.plebanek@lean.org.pl) Poland
-The Open Group Scott Hansen (s.hansen@opengroup.org) UK
-Volkswagen AG Heiko Wichura (heiko.wichura@volkswagen.de) Germany
-Electrolux Italia SpA Claudio Cenenese (claudio.cenedese@electrolux.com) Italy
-KLÖCKNER DESMA Schuhmaschinen GmbH Karsten Stöbener (k.stoebener@desma.de) Germany
-ONA Electroerosión Jose M. Ramos (jramos@onaedm.com) Spain
-SEMANTIC SYSTEMS Eduardo J. González Fuentes (ejg@semantic-systems.com) Spain
-Alberdi Mekanizatuak S.L. Aitzol Alberdi (aitzol@alberdimek.com) Spain
ProSEco provides a novel methodology and a comprehensive ICT solution for collaborative design of product-services (Meta Products) and their production processes.
The effective extension of products with new services in different sectors (automotive, home appliances, automation equipment etc.) will be achieved by means of Ambient Intelligence (AmI) technology, Lean and Eco-design principles and applying Life Cycle Assessment techniques.
New Meta Products using AmI, will be capable of acquiring knowledge in order to add highly personalized innovative functions, and thus enabling new business models. A Cloud Manufacturing approach is used for effective collaborative design of product-services and their production processes, and the effective implementation of innovative services. As a result new eco-innovative Meta Products are offered, which integrate highly personalised innovative functions with minimal environmental footprint along the overall Life Cycle. ProSEco offers a development platform and a set of new engineering tools to support collaborative work (simulation, configuration etc.) on new product-services, enhancing existing tools for product/process design.
The project has been driven by four industrial application scenarios addressing different aspects of service and business building as well as product/process development (complex internal and external supply chains), in order to assure that the means for collaborative service generation and product-service and production process design to be developed in the project will be relevant for industry. The solution will be first applied at 5 manufacturers in the consortium (Desma (DE), Ona (ES), Electrolux (IT), Volkswagen (DE) and Alberdi Mekanizatuak (ES)), serving as demonstrators of the project results.
Project Context and Objectives:
Meta-products comprise physical goods and physical services with emergent personal functionalities, which are based on the automated intelligent collection and processing of personal data as physical goods and services are used. As much of the value of meta-products resides in data in the Cloud, meta-products have great potential for international marketing and sales.
We are immersed in the wave of Factories of the Future. One the main topics is Servitization in industry 4.0. Servitization as a strategy to answer the pressure of the global markets in order to move the competition from costs to sophistication and innovation.
Nowadays manufacturers are forced to shift from their traditional product-manufacturing paradigm to the goods-services continuum by providing integrated combination of products and services. The adoption of service-based strategies is the natural consequence of the higher pressure that these companies are facing in the global markets especially due to the presence of competitors which operate in low wage region
The proliferation of new emerging technologies and paradigms together with a wider dissemination of information technology (IT) can significantly improve the capability of manufacturing companies to infuse services in their own products.
This can be enabled by making use of sensors and actuators already within existing physical goods; by adding them to existing physical goods; and/or by selling new physical goods. Technological developments from the EU ProSEco project enable the fulfilment of the huge marketing potential of meta-products by extending their scope and improving their technical performance.
The effective extension of products with new services in different sectors (automotive, home appliances, automation equipment, etc.) has been achieved by means of Ambient Intelligence (AmI) technology, Lean and Eco-design principles and applying Life Cycle Assessment techniques.
The objective of the ProSEco project has been to provide a novel methodology and a comprehensive ICT solution for collaborative design of product-services (Meta Products) and their production processes
ProSEco focuses on the capture and exploitation of customer side relevant information related to the use of the product or machine and its environment (by means of Ambient Intelligence (AmI) technology, context awareness, eco-impact assessment, etc.) to create better and new services in combination with the product (so-called servitization).This enables the creation of new business model providing more value to the customer, to rapidly response to the competitive economic climate and respecting the environment at the same time.
The Integrated ProSEco Prototype supports industries in collaborative design, development and management of new Product Extension Services (PES). It provides two working environments, the development and the deployment platform that requires different type of knowledge expertise and IT capabilities.
A Meta Product/process development platform has been provided, including a set of new engineering tools to support collaborative work (simulation, configuration, etc.) on new product-services, enhancing existing tools for product/process design. The platform is a set of set of ICT tools:
– Integrated Collaborative Development Environment
• Collaborative Portal, Eco-tool for impact assessment, Market Simulation Tool, Configuration of new Product Extension Services,.AmI Selection Tool, Data Mining Tool, Context Modelling Tool, Security Tool and Service Composition Tool.
– Integrated Runtime Deployment Platform
• to manage the execution of a Product Extension Services (PES) in the Cloud by using the Secure Runtime Infrastructure and a set of core services and application specific services.
A Methodology comprising a set of practical guidelines for organisations on how to develop Product Extension Services and how to prepare their business for introducing the Product Service System paradigm taking into account sustainability and eco-impact of the new services.
it’s described a ProSEco customer journey. It starts with the product virtualization, creating an avatar of the product/process. Then using the ProSEco Collaborative Platform the new PES is designed and created or (updated). The use of the new PES (i.e. Smart monitoring, remote diagnostic, etc.) is possible thanks to the Deployment Platform.
The entry point to design and create new services is the Collaborative Development Platform (Figure 3) that provides access to the product configuration or modelling, the engineering tools, and the workflow to design and create a new PES.
The project has been driven by four industrial application scenarios addressing different aspects of service and business building as well as product/process development (complex internal and external supply chains) in order to assure that the means for collaborative service generation and product-service and production process design developed in the project are relevant for industry.
Business Case scenarios are at:
• Volkswagen with personalised support to drivers to optimise energy use (in classical, hybrid and electrical cars)
• Electrolux with services to support consumer behaviour analysis and preventive maintenance of household appliances
• Desma with support remote condition based maintenance for shoe manufacturing machines
• ONA and Alberdi with lean–based design of eco–driven services around machines
The ProSEco project has adopted a generic approach for building Meta Products and their associated production processes, where the product/process design takes place through collaboration within the product ecosystem, involving multiple companies and actors and applying the Cloud Manufacturing (CMfg) concept.
Meta Products can now be built as a combination of so-called generic core services generic core services (applicable in various sectors) and application specific services, while new engineering tools from the project support product/process design and generation of these PES services involving collaboration of all stakeholders.
Project Results:
Description of main S & T results/foregrounds
The ProSEco project adopted the generic approach for building Meta Products and their associated production processes. The product/process design takes place through collaboration within the product ecosystem, involving multiple companies and actors, applying a Cloud Manufacturing concept.
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ProSEco project provides a methodology and a comprehensive ICT solution for collaborative design of PES, in particular:
• A new Collaborative eco-innovation design methodology to effectively take into account eco-relevant issues using eco-design principles through lifecycle assessment (LCA) techniques and Ambient Intelligent integrated already in the conceptual system design phase of Product Extension Services where lean product/process development principles can also be applied.
• ICT Collaborative environment system that supports industries in the design and creation of Product Extension Services (PES) from idea exploration to service deployment applying cloud computing approach and including a set of new engineering tools to support collaborative work and enhancing the existing tools for the product/process design.
4.1.1.1 Methodology
The methodology provides an innovative approach for using the ProSEco technologies to generate innovative PES solutions and build new business models. The methodology is an advanced composition of different guidelines:
• Methodology for collaborative product services & process design, comprising Methodology for Collaborative Product Services & Process Design, which includes guidelines on how to create and manage Virtual Communities, applying engineering tools developed within ProSEco project and Methodology for organisational / human aspects, including motivational issues to foster knowledge sharing and to overcome knowledge hoarding.
• Methodology for Lean-based ECO-driven Product-service & Process Design, applying the following paradigms:
o The lean principles in the design of Meta Products and production processes providing added value services considering individual demands.
o The eco-design and eco-innovation principles in the design of Meta Products for holistic understanding of enterprise sustainability and competitiveness, reducing environmental impact and the resources consumption during the production and during the overall product life cycle (promoting the use of more environmental-friendly materials).
Methodology for AmI based Context Sensitive Product-Services, defining how to use information from AmI solutions and other sensors embedded in products and other systems to generate various PES, and to provide guidelines on how to define context models needed for context sensitivity and personalisation of Meta Products.
These guidelines were combined into a single Integrated ProSEco Methodology,whose purpose is to serve as a guideline for industrial companies which intend to use for the first time the Integrated ProSEco platform to design new PES.
As it is showed in the following Figure 4, the Methodology for Collaborative Product Services and Process Design supports the whole ProSEco collaborative Platform by linking engineering tools with each specific phase of the development process and by integrating them seamlessly in the portal for the effective exchange of knowledge amongst geographically distributed teams. This methodology also determines actors’ association to their corresponding design activities, configuration of customized workflow process, and visualization of the status of development activities in a user interface.
The rest of the developed methodologies are linked to distinct phases of the development process and are linked to specific engineering tools in the following way:
• The Methodology for Lean-based eco-driven Product Services and Process Design guides the conceptualization and design of new product extended services (PES) by applying lean and eco-innovation principles in order to reduce environmental impact and the resources consumption during the production and during the overall product life cycle. This methodology is linked to the Eco and Configuration tools during the initial identification of environmental hotspots in different product systems configurations.
• The Methodology for AmI systems definition and selection guides the definition and selection of the appropriate sensorial information of the product that can be used to build effective PES, as well as provide basis for product development/enhancement. This methodology is linked to the amISelection tool that it is able to select different sensors from previous identified hotspot components to create an AmI Configuration needed for the new PES.
• The Methodology for Context Modelling and Context Extraction allows to investigate how context sensitivity can be used to achieve a high adaptability of products and PES. The context sensitivity allows for observation of changes in circumstances in which a product/PES is used, which in turn allows for a dynamic adaptation of the product/PES to these varying conditions. This methodology is linked to the context Modeling Tool to define, select and configure the context model which can be used within a PES to make it context sensitive, as well as to identify (extract) in real time the context under which the product/PES is used.
• The Methodology for Data Mining provides the guidelines on how data mining techniques and in particular machine learning algorithms can be integrated and used inside a PES to support the knowledge generation as well as the decision making process. This methodology is linked to the Data Mining Tool to easily enable the creation of data mining services that are responsible to analyze data extracted from the product for generating knowledge for the user in order to support and improve the decision making process.
Figure 4.: Integration of Methodologies and Tools linked to them (On the ProSEco Final Reportv1.doc)
The following sections explain each of the above methodologies by describing the customer experience journey and touch points where these methodologies help industrial companies to easily interact with ProSEco.
These methodologies are also helpful and applicable for companies which do not want to use ProSEco platform neither its components but intend to improve generation of new product extended services for their products.
Methodology for Collaborative Product Services and Process Design – ProSEco Collaborative Portal
Collaboration is the basis for bringing together the knowledge, experience and skills of multi-functional team members to contribute to the development of a new product more effectively than in the case of individual team members performing their narrow tasks in support of product development.
As it has been proven in ProSEco BCs the design, development and deployment of a new PES implies coordination and collaboration among many individuals including developers, designers, marketing staff, customer representatives, etc. therefore, collaboration among these actors is extremely crucial in order to synchronize the various system development activities. Therefore, the Methodology for Collaborative Product Services and Process Design methodology supports the whole collaborative ProSEco Portal by linking engineering tools with each specific phase of the development process and by integrating them seamlessly in the portal for the effective exchange of knowledge amongst geographically distributed teams. The methodology also helps actors from different domains to share ideas and create alliances to ensure convergence on a single PES design.
To do so we will follow the collaboration workflow (see figure below) to understand each phase, steps, tools and methodologies of the collaborative workflow to successfully created a new/updated PES from the discovery of the ProSEco Platform and user creation to the final PES Deployment in the cloud.
Figure 5: Collaboration Workflow (On the ProSEco Final Reportv1.doc)
The ProSEco collaborative portal contains the methodological skeleton to support the collaboration process. These are called Communication Services, Coordination Services and Cooperation Services. The collaborative development platform facilitates the users to either create a PES with a predefined/default workflow process or to configure a customized process. Therefore, to successfully collaborate through the whole ProSEco system an initial configuration setting need to be performed in the ProSEco portal.
Methodology for Lean-based Eco-driven Product Services and Process Design
The aim of this methodology is to provide a framework to facilitate the generation of innovative PES (product extension services) ideas together with the business strategy (business model) based on a combination of the physical product(s) and (in)tangible services(s) that fulfil specific user needs and requirements, taking into account the reduction of the environmental impact together with the competitiveness of the company and stakeholders; provoking a shift of behaviour from consumption (selling product) to use (selling function).
This methodology is supported (management of phases, steps & tools) by the Collaborative ProSEco portal. However, the methodology can also run independently from the ProSEco Portal and components. The following figure summarizes the whole customer experience journey when applying the lean-based eco-driven methodology for creation of new PESs.
Figure 6: ProSEco PES Conceptualization Journey (On the ProSEco Final Reportv1.doc)
Methodology for AmI systems Definition and Selection
This part of the ProSEco methodology is dedicated to the definition/selection of AmI systems within products and PES development. Modern industrial products and processes possess cyber physical features i.e. they are more and more equipped with different intelligent systems such as AmI systems. They normally include a number of sensors that may provide information about the product current state, use, manufacturing process etc. This information in turn can be used to build effective PES, as well as provide basis for product development/enhancement.
The aim of this methodology is to apply AmI systems as powerful source of information needed for PES to:
• Realize its key functionality
• Identify context of product-service use or to identify context under which the product is produced or used – needed to “personalise” product-services and make them context sensitive
• Identify environmental impact aspects
• Provide data for various data mining analysis such as identify usage patterns, environmental impact patterns etc. to be used for improved product/PES design and marketing
The method for definition/selection of AmI systems supports users to select AmI systems that should allow/support implementation of various PES and enhancement of the product itself.
The method specifically supports user in:
• Selection of AmI information for PES from AmI systems which are available at the product and/or processes where it is manufactured or where it is used
• Definition/selection of AmI systems which may be added to the product (and process) to meet the need of PES (and/or to enhance product itself) specification of processing of information from AmI systems for PES, i.e. definition of (low level) processing of data obtained from AmI systems (e.g. grouping, histograms, data binning, correlating of signals etc.)
Methodology for Context Modelling and Context Extraction
The aim of this part of the ProSEco methodology is to define how context sensitivity can be used to achieve a high adaptability of products and PES. The idea is make PES context sensitive. The proposed generic context sensitive solution can be easily adjusted to allow for adaptation of wide scopes of products and PES.
The context sensitivity allows for observation of changes in circumstances in which a product/PES is used, which in turn allows for a dynamic adaptation of the product/PES to these varying conditions. Context sensitivity is useful for products/PES used in dynamically changing conditions and various users (i.e. there is no sense to apply context sensitivity if PES is used under static conditions and/or all the user have same needs).
The assumption is that “normal/nominal” PES must operate without context sensitivity. Context sensitivity “only” improves the PES performance by better adapting it to dynamically changing situation/user current needs. Therefore, the context sensitivity is “only” add-on to PES but not basic functionality of the products/PES. Product/PES must have ‘nominal situation’ under which it operates without context sensitivity. For example, PES must be good for “normal/nominal” user of a refrigerator (e.g. homemaker) without special needs; context sensitivity ’adopts’ a service for “non-normal” user (e.g. a child or a partner who does not cook often).
The methodology (and the tool and the service) supports user (product or PES designer) to define/select/configure context model which can be used within PES to make it context sensitive, as well as to identify (extract) in real time the context under which the product/PES are used.
Methodology for Data Mining Tool
The objective of this part of the ProSEco methodology is to apply data mining techniques and machine learning algorithms to allow advanced services provided by manufacturers, beside the standard products. The analysis of data from the environment is vital from several points of view:
• Customer: the customer is the central point of any business and device. It is crucial to understand how she behaves, respectively to determine the behavioural patterns. Based on this, predictive and preventive maintenance can be done, in a transparent way.
• Supplier: As time is expensive especially nowadays, as well as storage facilities, just in time deliveries are crucial of good profits. Based on the size of the suppliers, their cultural and business habits, they need to be treated in different ways and this becomes very complex when we have to do supply chains.
• Device: the device itself undergoes technical changes and wears out. Although there are system theories determining the possible break outs stochastically, it is clear that each device behaves differently, as it is a blend of more components, each unique in its way. Therefore, variations from the mathematical model always appear. Therefore, it is important to determine the work patterns of the device for predictive and preventive maintenance.
• Environment: environment is not only the nature, but also the external factors. This influences the usage of any device, e.g. a football championship or a hot summer will result in an increase of beer consumption in Western countries.
Therefore the methodology serves as guidelines for companies that intend to apply data mining techniques and machine learning algorithms to their own products/processes - to the data extracted from products/processes – by using the ProSEco system. However, the methodology is also thought to be used by companies that do not want to apply the ProSEco system but intend to provide PESs.
4.1.1.2 ProSEco platform: ICT Collaborative environment system
The ProSEco Platform supports industries in collaborative design, development and management of new Product Extension Services (PES). The ProSEco platform is a fully functional and robust suite. It provides two working environments, each of which requires different type of knowledge expertise:
• Development platform, which is the set of integrated software modules used at PES design and development time.
• Deployment platform, composed by core services and other software modules required at PES deployment and execution time.
Figure 7. ProSEco architecture (On the ProSEco Final Reportv1.doc)
Both the collaborative development environment and deployment platform are integrated into a holistic common ProSEco solution by means of the use of Ontologies, a Knowledge Management Base and a Collaborative Portal all of which support the tasks to be carried out by PES design teams.
While all these software tools and core services can also be used independently and have their own functionality as standalone modules, they have been successfully integrated into a coherent software suite referred to as the ProSEco platform. The main integration pillars on which this integration has been conceptually based are:
• Ontologies: are in the base of many ProSEco software tools design. They are used as a technology-independent way to transmit results PES design related information from one software module to another. In other words, a common ontology shared amongst ProSEco modules ensures coherency when one module’s output is the next module’s input.
• Knowledge Management Base: successfully achieves the goal of empowering data and configuration sharing amongst ProSEco software modules.
• Collaborative Access Portal: is where ProSEco tools are linked and provides the operational environment for collaborations amongst PES design teams. Via this portal, ProSEco access control and PES workflow processes are conveniently integrated within a shared environment for all team members.
ProSEco provides a reference workflow for the development of new Meta Products. However, the solutions developed by ProSEco are also intended to update/upgrade/reconfigure existing Meta Products and PES and are able to adapt to existing workflows within manufacturing organisations, which may be quite different.
Beyond the workflow to create a PES there is a set of engineering tools and core services that are used in each of the workflow steps that enable dynamic composition of core services and application specific services adaptable to the different meta products and associated production processes in order to compose innovative PES solutions.
ProSEco generic workflow provides a sequence of steps that can be followed by PES design and deployment stakeholders to receive assistance in the creation of PES solutions as a combination of the core services and application specific services (development phase), and in the use of the PES services (deployment phase). The steps are briefly described below:
Figure 8. ProSEco generic workflow (On the ProSEco Final Reportv1.doc)
Idea creation: This initial part of the process will start with the analysis of the environmental performance of the current product-system reality (taking into account the whole life cycle perspective) in order identify improvement areas. Once the improvement areas have been identified, it is necessary to look for concrete needs/problems to be solved. With the help of ProSEco methodologies and other engineering tools, the stakeholders will conceptualize a PES solution as an extension to an existing meta-product or process to produce it. This PES solution will, e.g. turn the product-process into a more sustainable meta product, will reduce its time to market, will help the product comply with new environmental constraints, will solve some technical problems associated to the manufacturing process or will add some extra features to the product, such as data pattern analysis to improve future product designs or extended after-sales services, which will unleash innovative business opportunities that may derive in new business models supported by virtualization of meta-products under the Factories of the Future (FoF) frame.
Market Simulation: This step will comprise collaborative activities targeted at estimating the expected social impact derived from the introduction of a PES solution into the market as an extension to a new or an existing product
Knowledge Specification/Data mining: This activity will be leveraged to extract patterns of use, which can be used for the configuration of a PES or to improve future product designs by means of the application of appropriate feedback mechanisms
Data Capture/AmI sensors selection: This activity will configure the available sources of data that will feed the PES
Context Modelling: This step will enable ProSEco users to model the context for the PES using reasoning methods, enhancing AmI sensors monitoring and data contextualization
Security Configuration: This activity will enforce the applicable policies to restrict and protect PES data provision according to users’ data protection rules
PES orchestration: The outcome of the previous activities will be orchestrated so as to build a PES solution around a product / process
PES deployment: The PES will be deployed into a collaborative environment and used in runtime by the end-users as an extended service to an existing meta-product
The Integrated Development Platform is aimed to design and create in a collaborative way new Product Extension Services by using the following engineering tools:
1. Eco-tool for impact assessment
2. Market Simulation Tooll.
3. Configuration of new Product Extension Services
4. Engineering tool for definition/design of AmI solutions (also called AmI Selection tool)
5. Data Mining Tool
6. Context modelling engineering Tool
7. PES development Security Tool
8. Orchestration and Configuration of services: Configuration of Services and Service Composition Engineering Tool
The Deployment Platform to manage the execution of a Product Extension Services in the Cloud by using the following Key modules:
1. Secure Runtime Infrastructure
2. Deployment Platform Configuration Tool
3. Service Registry
4. Core Services
5. Application Specific Services
6. Deployer: Data Access Layer and Service Broker
A description of the above components is given below.
4.1.1.3 Development Platform: engineering tools
1. Eco Tool For Impact Assessment
The Eco-tool takes part in the ProSEco Integrated Development Environment by means of providing lifecycle assessment calculation capabilities so as to leverage the environmental perspective in the Product Extension Services (PES) creation process. In this context, the Eco-tool tool is used to configure the Eco Core Service that will be run by the service broker during the PES deployment phase.
2. Market Simulation Tool
The purpose of the Market Simulation Tool in ProSEco is to enable easy modelling of the complex market contexts of PESs during their design when using the ProSEco Platform.
The Market Simulation Tool is based on extensive critical review of qualitative and quantitative scientific literature related to consumer and market behaviour.
It allows industry partners to simulate the meta product offerings in dynamic business ecosystems in order to explore / test effects of alternative offering designs within different business ecosystems
3. Configuration of new Product Extension Services
One of the key issues regarding Product Extension and Services design and execution is their configuration, that is to say, their parameterization and value-specification required to ensure their correct designing inside the engineering tools and their correct execution inside the deployment platform.
The Configuration Tool enables industry partners to design products and its associated extension services (PES), in a cloud-based collaborative environment, while incorporating eco-design methodologies and rules
4. Engineering tool for definition/design of AmI solutions
This solution supports the user in setup and monitoring of AmI systems / sensors needed to build PES in a simplified way, allowing for a transparent way to select and monitor sensor data from products.
Engineering tool for definition/design of AmI solutions allows effective selection of the AmI systems already integrated (or, to be integrated) in the product, allowing for provision of PES, as well as extraction of context on product-service use following the above explained methodology approach. The tool supports the designer in selecting/designing of AmI and other measurement systems and appropriate extended monitoring.
5. Data Mining Tool
The Data Mining Tool allows the configuration of a data mining process to be integrated in a PES during its design/definition. In particular, it provides the possibility to model a data mining process by first selecting the necessary parameters to be analysed/processed (e.g. data collected from the environment and the context extracted), selecting the processing algorithm, and finally, the target value. The tool enables the building of several PESs such as decision support services (e.g. schedule proactive maintenance activities), PES to provide the consumer behaviour when interacting with the product/process for detecting misuses and/or adapting the internal parameters of the product/process. It provides data mining techniques for analysing AmI data to allow industry partners to understand and detect customer and supplier behaviour that can be used to enhance their offerings
6. Context modelling engineering tool
The engineering tool supports the definition/design of context sensitive PES by allowing to model the product/PES use context. The context model describes circumstances under which a product is currently used, and by this allows adjustments of PES to dynamically meet specific needs of the users of the products. The context model is set of concepts and their relations which describe circumstances under which the product/PES is currently used.
7. PES Development Security Implementation
The security approach is based on the concepts of the Next Generation Access Control (NGAC) standard (INCITS 499, 2013). This entails a functional architecture for access control that localises policy and security decisions and potentially distributes enforcement. In ProSEco, the functional architecture is realised by several components: policy information is stored in the meta-data about PES objects used by the Node.js/Express framework and the PES service composition used by the Service Broker. The ProSEco Portal and Service Broker act as trusted policy enforcement points, and APIs are provided for enforcing security policies for application access requests.
8. Orchestration and configuration of services
PES that are meant to be deployed into the ProSEco Deployment platform are required to be structured and encompassed in a software solution that contains all the information required for the PES execution. This orchestration for deployment encompasses the Configuration of Services and the Service Composition Engineering Tool. the information required for the PES execution. This orchestration for deployment encompasses the Configuration of Services and the Service Composition Engineering Tool.
o Configuration of Services
Along the workflow of a PES development, PES Designers access a set of engineering tools that assist on the idealization and parameterization of the PES. Among these Engineering Tools persist the ones that enable to parameterize each of the Deployable Services selected for the deployment, by means of producing a configuration data structure to be passed and interpreted by the respective service that will be used in the deployment.
In order to make these configuration files reusable by other components, they co-exist in the system has hybrid files, possessing both specific and generic fields. The specific fields contain the parameterization which the service will receives and uses for self-configuration, while the generic fields are used for several tasks of the PES development and deployment, such as recognition of the respective type of service and to incorporate the data model that is associated to the produced results of the service, which is used in the interoperability of the PES execution. This enables the configuration to be read by other components and that it can be forwarded to the tight service on the PES deployment.
o Service Composition Engineering Tool
The Service Composition Tool supplies an easy to use Graphical User Interface, compliant with BPMN standard, allowing the PES Tools. The composition of different ProSEco Core Services and application specific services is representing the PES. ProSEco offers following core service templates for rapid prototyping using the ProSEco engineering tools:
• AmI Monitoring: used for collection and aggregation of AmI systems/sensors (at the product/process) raw data into AmI based data.
• Context Extraction: used for extract context during daily product use operation, and to provide the extracted context to the downstream services.
• Knowledge Provision: enable the gathering of relevant knowledge about costumer that can be used for developing new and more accurate PES solutions.
• Security enforcement: inspects, modifies, and queries the policy database, resource managers for each host that provides protected resources, session managers for each user initiated session, and session initiation functions within the ProSEco platforms
• Eco core service: allows the impact assessment calculation, following the single score approach provided by “endpoint” impact calculation methods.
• Data Mining core service: analyses the behaviour of the providers and customers or to predict future events, such as the proper times for predictive maintenance.
PES designers are able to elaborate the Orchestration/Choreography of the services used on a PES. A Graphical User Interface enables the definition and parameterization of the PES data flows between the operating services in use on the deployment, as well as the ability to combine all features of the PES into a unique software Solution while connecting and sending it into the deployment Environment.
The stored Configuration files are retrieved and used to identify the services in use, as the Tool set up the working environment. Then the user may use the graphic blocks, by means of a Drag & Drop technique, to connect the services in the desired workflow of data portended to occur while the PES is executing.
4.1.1.4 Deployment Platform
In close association to the PES Deployment platform is a software solution which provides the automatized mechanisms to deploy the designed PES. Based on a Service Oriented Architecture, several modules and components have been developed and integrated in the deployment platform, for which the combined functionalities provide a full and comprehensive structure. The main modules that have been developed are:
• Secure runtime infrastructure: Provides an environment for security of services deployment, communication and invocation.
• Deployment Platform Configuration tool, provides a way to specify the physical data for each service effective deployment, such as IP and port.
• Service Registry: provides a registry where all the services/functionalities inside the ProSEco system could register. Therefore, such component is responsible to maintain a list with all the services/functionalities available over the network that can be potentially used in the design and development of PES solutions.
• Core Services: defines a set of services with generic functionality, which can be easily adopted for specific needs and combined to create/update PES solutions, and can be easily adapted to the individual user needs. Core Services are templates of deployable services, easily configurable through ProSEco Engineering
• Deployer: provides the mechanism and the necessary dynamics for enabling the register of all the services/functionalities. It is capable to manage and handle the communication with the Service Registry component whenever a service is started/stopped. Therefore, it is responsible to (un-)publish services/functionalities
o Data Access Layer: provides an isolated and trusted communications link to the several Repositories enabling each of the services/functionalities (core and application specific) to securely store data in the required format along with authentication mechanisms to ensure data integrity for future references by the components of the ProSEco solution.
o Service Broker: represents the mediator that enables the connection between the designed PES solutions: connecting all the resources in use for a PES, while passing all the specifications necessary for the PES execution are made by means of an agent-based system which controls all the PES Setup and Execution processes while a PES is deployed.
Figure 9: Overall picture of the ProSEco runtime environment and communication between components (On the ProSEco Final Reportv1.doc)
Application Specific Services: defines a set of specific functionalities (or processing components), which can be embedded in the products and combined to create/update PES solutions. These functionalities depend on the particular application context meaning that each one of the application scenarios may have one or more applications specific services that make sense only in that particular scenario
4.1.1.5 ProSEco Business Cases
ProSEco prototype development has been driven by four application scenarios lead by the industrial partners that also form the business cases that have been used to validate the project technologies:
• Volkswagen with personalised support to drivers to optimise energy use (in classical, hybrid and electrical cars)
• Electrolux with services to support consumer behaviour analysis and preventive maintenance of household appliances
• Desma with support remote condition based maintenance for shoe manufacturing machines
• ONA and Alberdi with lean–based design of eco–driven services around machines
Each of these is described in the following sections.
4.1.1.5.1 Business case Volkswagen
Volkswagen as an automobile OEM, aims to offer telemetric und online services to their vehicles in order to improve the experience of owing a Volkswagen. A Volkswagen vehicle contains, depending on model, more than 4000 signals exchanged by the ECUs (Electronic Control Units) and communicate over CAN bus every 10ms. Today these signals are used only inside the vehicle to control the functionality and vehicle behaviour but are interesting to pro-vide new telemetric and online services around the vehicle. ProSEco supports the development and provision of such new services about driver and driving behaviour, vehicle and vehicle behaviour and vehicle environment.
ProSEco provides the engineering tools to support Volkswagen in the preparation and selection of the signals that best fit the numerous Product Extension Services that can be obtained and provided with the vehicle signals. Furthermore, it provides core services and facilities for fast deployment of PES.
One important issue is that all data (signals) is owned by the vehicle owner. Therefore, the vehicle owner has to accept and allow the gathering und usage of signals for services. The access and authorization to the data use is also ensured by a ProSEco engineering tool. The PESs developed to demonstrate the ProSEco solution are Eco-Driving Monitor and Pollution Monitor for public administration.
Innovation: Enabling of third party service providers to build apps around vehicle data and possibility of cross sectorial service development (e.g. weather service using vehicles as mobile weather stations)
Benefits—External Business, Participating on new 3rd party business (as part of the value chain) , Internal Rapid prototyping, Short evaluation of service ideas
Figure 10: Example of the Fuel Consumption Eco-Monitor PES (On the ProSEco Final Reportv1.doc)
4.1.1.5.2 Business case ELECTROLUX
The objectives of Electrolux within ProSEco have been to develop services for:
Consumer behaviour analysis — to be able to analyse all data coming from the monitored appliances. This analysis will enable ProSEco to model the customers’ behaviours according to their usage of the devices;
Preventive and Predictive Maintenance — ProSEco will, instead of finding trends in the user’s behaviour, provide historical information on the components behaviour. Ultimately, this analysis will enable ProSEco to find, predict and prevent problems that may occur in a component within the devices.
The environment taken into consideration is:
• Physical — where the actual devices rest. These devices are the source of the data that will be analysed within ProSEco;
• Cyber-Physical — the limbo environment where both the physical and the virtual world meet. It is where the data is received from the devices and pro-cessed into the ProSEco environment;
• Advanced Support — the environment where the PESs run. Here the data is processed, stored and analysed using a mix of core services within the ProSEco environment and specifically developed ones.
In the future Electrolux believes that connected appliances offer a possibility for a lifelong relationship between the company, as a manufacturer and the user of its products. Moving beyond the user’s behaviour understanding and predictive maintenance, connectivity makes it possible to offer personalized, value added services in a way the appliance industry has never seen before.
To that end, Electrolux is taking a holistic approach to developing connected appliances throughout the entire ownership experience, in order to create lifelong relationships with consumers. For example, taking into account relevant user data, it will not just be able to help users cook a meal like a professional, it will be possible to suggest the ingredients and order them according to the preferences.
Figure 11: Connected appliances (On the ProSEco Final Reportv1.doc)
4.1.1.5.3 Business case DESMA
DESMA provides production machines for the shoe industry. Their motivation in ProSEco was a totally improved maintenance service system for their complex production and automation systems that uses as information basis: 1) influencing ambient environment information; 2) data directly from the manufacturing systems (ISA’95 Level 1-3); and 3) data from operators (e.g. technical and maintenance reports). ProSEco was a suitable project to focus these challenges.
The figure below side shows the result of using ProSEco in DESMA: A configured DESMA PES, which is deployable on several production systems and reachable from everywhere. The PES provides classical monitoring, historical data, machine meta data, context information, predicted data, and pattern management, observation and matching information/functionalities from/for their machines. These information and functionalities are further exploited by Service Report Management, Solution Search Support and Remote Diagnostics applications for the improvement of their maintenance service system.
For DESMA ProSEco shows a high business potential of PES for machine builders like DESMA. ProSEco PES development accelerates traditional machine service and cuts down costs by making relevant service mission specific information instantly available to all resources. Avoided international technician travel not only minimizes loss of production and wasted material but also CO2 emission for people transport. ProSEco allows DESMA to fully exploit the meta products concept by lean development, test and management of new PES ideas. DESMA is now in a position to drastically increase the number of PES products combined with shortened time to market.
Figure 11:. Access to new PES (On the ProSEco Final Reportv1.doc)
4.1.1.5.4 Business case ONA and ALBERDI
The current Premium Series of ONA EDM machines are equipped with a new Smart CNC that intends to accomplish the “Industry 4.0” paradigm because some of the most disruptive improvements and changes in the Machine Tool industry are expected to come from the digitalization concept.
The new demands for customized products and flexible production EDM processes have motivated research initiatives in a manufacturing data driven concept that requires converting machines in cyber-physical systems. As running costs of EDM machines over the lifetime can be even higher than the initial investment costs, one of the main targets for ONA in ProSEco was to design new advanced services with the focus on the product usage. In this context, the proposed Eco-driven methodology applied to the life cycle of ONA machines has helped to define two PES:
• A cloud based Smart Monitoring concept service for fleet of machines. The interest here has been to:
o analyse Machine-Cloud infrastructure for SMEs
o check how data analytics could help to improve the product performance and its maintenance.
o extend the machine functionality according to an Industry 4.0 strategy in Manufacturing (new Smart controller concept).
o improve the current capabilities of ONA Turnkey Solutions at SME scale.
o explore new business support services that can be offered to the final customer. This is the case of maintenance service contracts based on machine availability targets or fixed cost requirements. Another opportunity is to support customer in optimizing entire process chain and maximizing OEE.
• A Trace-ability service for the EDM process. The selected manufacturing data define a part signature concept that can be used in quality certification. This information can be the input for data analytics techniques that could make possible to:
o generate new indirect sensors (part thickness estimation, for instance)
o register and quantify quality deviations from a nominal value
o identify potential machine improvements and feed them back to the design teams
o contribute to the LCA and ECO impact assessment of the machinery
o improve consumables management and energy efficiency (sustainability)
Figure 13 Cloud based Smart Monitoring concept service (On the ProSEco Final Reportv1.doc)
The objectives of ALBERDI at ProSEco are:
• To improve the parts production management system by being able to analyse different manufacturing alternatives and to choose the one that best fits the customer preferences, taking into account: mechanical costs, delivery time or environmental impact of each of the manufacturing processes
• To provide a better collaborative service-offer to their customers taking into account customers’ requirements such as geometry, raw material and other characteristics of the part
Figure 14: Alberdi Customer requirements: material, geometry, draws design (On the ProSEco Final Reportv1.doc)
Potential Impact:
Potential impact and main dissemination activities and exploitation results
Potential impact
The application of the ProSEco solutions improves efficiency of creating new business models based on services around products. The ProSEco solution allows imagining and building innovative scenarios for eco-friendly industries and low-carbon economy (e.g. for Full Electric Vehicles (FEV) in BC1 (Volkswagen), reduced energy consumption in BC2 Electrolux etc.).
ProSEco platform (core services and engineering tools, and methodology) provides the following impacts within the specified business case (BC) scenarios:
1. Reduction of time and efforts needed for development/update of Meta Product and associated product processes
2. Increase in number of innovative personalised PES
3. Reduction of time to market
4. Reduction of energy consumption through new PES
5. Cost reduction for Support Services (improvement in relation to currently provide services)
6. Reduction of ramp-up time within the associated manufacturing processes
The communities most likely to benefit from ProSEco results are:
- Manufacturers in different traditional sectors (first target is automotive, machine industry but also other traditional sectors such as metal industry as direct customers/partners of the five industrial partners: VW, ELECTROLUX, DESMA, ONA, ALB). The consortium includes partners from automotive sector and home appliances sector having leading role in developing Meta Products, but also partners from machine sectors (aiming to provide transfer of the advanced approaches into other sectors.
- Manufacturers of industrial installations: equipment, automation and electronic devices (where PES plays an important rule to establish new business models).
- ICT community (SW and service providers – both large and small, where SEM belongs). The project will provide also benefits for ICT vendors involved in product extensions, i.e. provision of services. Especially smaller ICT vendors will get opportunity to provide new/updated services to their customers – manufacturing companies which want to install new PES or improve their existing PES. Based on the proposed approach they will be able to realise faster and more efficient customisation for their clients, thus enabling a smooth transition from the current service provision to new PES which can be cost-effectively applied at the global market
- Customers of industrial partners (i.e. DESMA, ONA).
ProSEco specific impacts within Business Cases:
1. Integrate knowledge from customers and product usage patterns. A way for Understanding:
a. Users (in aggregate way but properly clustered – e.g. ethnographic assessments);
b. Appliances (in aggregate way but properly clustered – e.g. preventive maintenance);
2. A way to provide Hints ( to improved «User Experience»)
a. to Consumers (eco behaviors, preventive maintenance)
b. To the Company (specification of future products)
3. Automated and remote recording and analysis of machine sensor data for evaluation and prediction of machine status
a. early identification of significant problems
b. reduced time/costs for problem solution
c. avoidance of production stops (solve problem prior to becoming critical)
4. To extend the machine functionality according to Industry 4.0 strategy in Manufacturing
5. Exploring business opportunities based on services.
6. Accelerating innovation and design cycles: Rapid prototyping, evaluation of service idea
7. Minimise the environmental burden of production and consumption (towards a eco-industry and circular economy)
Beyond the impact in the industrial community, ProSEco has provided:
- S&T Impact: The project provides solutions on how to apply eco-driven design principles, in combination with lean principles, for collaborative design of Meta Products and their production processes, and on how to extract context from AmI solutions integrated in the product and processes and use it for highly adoptable and reconfigurable services. ProSEco shows how AmI technology and context sensitiveness can be used as an enabler for easy adoption and personalisation of product extension services. Business cases, scientific papers and Exploitable results have been issued to present and support the results of the project (see sections 4.1.4.1 and 4.1.4.2 for the main results, section 0 for more detail information)
- Socio-economic impact: Using the project results to optimise Meta Products design in industry allows for considerably higher productivity and more effective, establishment of new business models, and faster responses to the market requirements (as Industrial partners have stated), thereby improving competitiveness and business development of manufacturing industry. On the other hand, ICT and industrial vendors are able to offer new services to their customers, also enabling European industry to reinforce its major strengths in the innovative PSS solution. This will have on medium and long-term a direct positive benefit for employment, as the companies use the improved competitive position to build up further business.
- Quality of life: The project makes significant contribution to generation of PES for various products, radically improving their usability (based on context sensitive approach). This can be seen in all BC, but especially in B2C Business Cases as in BC2 where the higher quality of PES improves customer experience and hence their satisfaction
- Environmental impact: The environmental impact of Meta Products based on the new platforms, core services and engineering tools, and methodology are a reality as shown in business cases using eco-tool and eco-impact assessment as in BC4
The ProSEco tools and methodologies will be used by partners as an easy to use tool for prototyping new PES. Having a rapid prototyping tool is already something of great value because it allows showing real performances and not a static presentation with hard numbers. Such a demonstrative process can help in taking decisions which is the most critical issue before a production commitment is to be made. This represents a new paradigm in industrial processes: moving from a pure product concept to a PES concept it’s something that it’s not easy to grasp at first but that steers interest once it’s understood or seen in action.
This approach is completely aligned with latest Industry 4.0 trend and therefore ProSEco could and should be marketed as part of Industry 4.0 activities.
Main dissemination activities
During the project execution period, the ProSEco partners performed many dissemination activities for the public in general (both RTD and industrial audiences) in:
- Conferences (e.g. IEEE INDIN 2014, CEC 2015, IPSS 2016, ProVE 2016, Smart Cities Conference 2016, ICE 2017, IEEE INDIN 2017, FedCSIS 2017)
- Workshops in international conferences (some co-organized with other projects ),
- industrial fairs (BIEMH 2014, RTEX 2014, Subcontratación 2015, RTEX 2015, EMO Milano 2015, DESMA house fair 2016, IMTS 2016),
- journal articles (e.g. in Journal of Consumer Culture, IJACSA, Planet Lean, International Journal of Communications, Network and System Sciences, Journal Sensors),
- EC organised events (e.g. project results presentation at Factories of the Future Conference 2016 Materialising Factories 4.0)
- User interest groups (e.g. in Germany, East European countries, Portugal, UK)
- Newsletters (4 ProSEco newsletters as well as articles in Lean Global Network, or the LEI newsletter),
- Others (e.g. presentation to the Steering Committee of the IoT Working Group under the Platform 3.0 Forum or project description and results were introduced in the EFFRA portal)
The complete overview of these activities can be seen in Table 7.
The ProSEco dissemination activities were intensive from the beginning of the project in terms of presenting basic ideas within RTD and industrial communities, followed with results presentation.
Exploitable Results
The main exploitable result of the project is the ProSEco platform, with the main components of this platform having also been identified as exploitable results by themselves.
Exploitable results, which is as follows:
• Result 1 : ProSEco Collaborative Development Platform
• Result 2 : Lean Consultancy
• Result 3 : Eco Tool, Service and Methodology
• Result 4 : Simulation tool
• Result 5 : Data-mining Tool and Services
• Result 6 : AmI Selection tool, monitoring services and Methodology
• Result 7 : Context Modelling tool, extraction services and Methodology
• Result 8 : Knowledge Provision core service
• Result 9 : Security Tool/Enforcement services
• Result 10 : ProSEco Deployment Platform
Table 1: Overview of the ProSEco results
4.1.1.1 Potential impact
The application of the ProSEco solutions improves efficiency of creating new business models based on services around products. The ProSEco solution allows imagining and building innovative scenarios for eco-friendly industries and low-carbon economy (e.g. for Full Electric Vehicles (FEV) in BC1 (Volkswagen), reduced energy consumption in BC2 Electrolux etc.).
ProSEco platform (core services and engineering tools, and methodology) provides the following impacts within the specified business case (BC) scenarios:
1. Reduction of time and efforts needed for development/update of Meta Product and associated product processes
2. Increase in number of innovative personalised PES
3. Reduction of time to market
4. Reduction of energy consumption through new PES
5. Cost reduction for Support Services (improvement in relation to currently provide services)
6. Reduction of ramp-up time within the associated manufacturing processes
The communities most likely to benefit from ProSEco results are:
- Manufacturers in different traditional sectors (first target is automotive, machine industry but also other traditional sectors such as metal industry as direct customers/partners of the five industrial partners: VW, ELECTROLUX, DESMA, ONA, ALB). The consortium includes partners from automotive sector and home appliances sector having leading role in developing Meta Products, but also partners from machine sectors (aiming to provide transfer of the advanced approaches into other sectors.
- Manufacturers of industrial installations: equipment, automation and electronic devices (where PES plays an important rule to establish new business models).
- ICT community (SW and service providers – both large and small, where SEM belongs). The project will provide also benefits for ICT vendors involved in product extensions, i.e. provision of services. Especially smaller ICT vendors will get opportunity to provide new/updated services to their customers – manufacturing companies which want to install new PES or improve their existing PES. Based on the proposed approach they will be able to realise faster and more efficient customisation for their clients, thus enabling a smooth transition from the current service provision to new PES which can be cost-effectively applied at the global market
- Customers of industrial partners (i.e. DESMA, ONA).
ProSEco specific impacts within Business Cases:
1. Integrate knowledge from customers and product usage patterns. A way for Understanding:
a. Users (in aggregate way but properly clustered – e.g. ethnographic assessments);
b. Appliances (in aggregate way but properly clustered – e.g. preventive maintenance);
2. A way to provide Hints ( to improved «User Experience»)
a. to Consumers (eco behaviors, preventive maintenance)
b. To the Company (specification of future products)
3. Automated and remote recording and analysis of machine sensor data for evaluation and prediction of machine status
a. early identification of significant problems
b. reduced time/costs for problem solution
c. avoidance of production stops (solve problem prior to becoming critical)
4. To extend the machine functionality according to Industry 4.0 strategy in Manufacturing
5. Exploring business opportunities based on services.
6. Accelerating innovation and design cycles: Rapid prototyping, evaluation of service idea
7. Minimise the environmental burden of production and consumption (towards a eco-industry and circular economy)
Beyond the impact in the industrial community, ProSEco has provided:
- S&T Impact: The project provides solutions on how to apply eco-driven design principles, in combination with lean principles, for collaborative design of Meta Products and their production processes, and on how to extract context from AmI solutions integrated in the product and processes and use it for highly adoptable and reconfigurable services. ProSEco shows how AmI technology and context sensitiveness can be used as an enabler for easy adoption and personalisation of product extension services. Business cases, scientific papers and Exploitable results have been issued to present and support the results of the project (see sections 4.1.4.1 and 4.1.4.2 for the main results, section 0 for more detail information)
- Socio-economic impact: Using the project results to optimise Meta Products design in industry allows for considerably higher productivity and more effective, establishment of new business models, and faster responses to the market requirements (as Industrial partners have stated), thereby improving competitiveness and business development of manufacturing industry. On the other hand, ICT and industrial vendors are able to offer new services to their customers, also enabling European industry to reinforce its major strengths in the innovative PSS solution. This will have on medium and long-term a direct positive benefit for employment, as the companies use the improved competitive position to build up further business.
- Quality of life: The project makes significant contribution to generation of PES for various products, radically improving their usability (based on context sensitive approach). This can be seen in all BC, but especially in B2C Business Cases as in BC2 where the higher quality of PES improves customer experience and hence their satisfaction
- Environmental impact: The environmental impact of Meta Products based on the new platforms, core services and engineering tools, and methodology are a reality as shown in business cases using eco-tool and eco-impact assessment as in BC4
The ProSEco tools and methodologies will be used by partners as an easy to use tool for prototyping new PES. Having a rapid prototyping tool is already something of great value because it allows showing real performances and not a static presentation with hard numbers. Such a demonstrative process can help in taking decisions which is the most critical issue before a production commitment is to be made. This represents a new paradigm in industrial processes: moving from a pure product concept to a PES concept it’s something that it’s not easy to grasp at first but that steers interest once it’s understood or seen in action.
This approach is completely aligned with latest Industry 4.0 trend and therefore ProSEco could and should be marketed as part of Industry 4.0 activities.
4.1.1.2 Main dissemination activities
During the project execution period, the ProSEco partners performed many dissemination activities for the public in general (both RTD and industrial audiences) in:
- Conferences (e.g. IEEE INDIN 2014, CEC 2015, IPSS 2016, ProVE 2016, Smart Cities Conference 2016, ICE 2017, IEEE INDIN 2017, FedCSIS 2017)
- Workshops in international conferences (some co-organized with other projects ),
- industrial fairs (BIEMH 2014, RTEX 2014, Subcontratación 2015, RTEX 2015, EMO Milano 2015, DESMA house fair 2016, IMTS 2016),
- journal articles (e.g. in Journal of Consumer Culture, IJACSA, Planet Lean, International Journal of Communications, Network and System Sciences, Journal Sensors),
- EC organised events (e.g. project results presentation at Factories of the Future Conference 2016 Materialising Factories 4.0)
- User interest groups (e.g. in Germany, East European countries, Portugal, UK)
- Newsletters (4 ProSEco newsletters as well as articles in Lean Global Network, or the LEI newsletter),
- Others (e.g. presentation to the Steering Committee of the IoT Working Group under the Platform 3.0 Forum or project description and results were introduced in the EFFRA portal)
The complete overview of these activities can be seen in Table 7.
The ProSEco dissemination activities were intensive from the beginning of the project in terms of presenting basic ideas within RTD and industrial communities, followed with results presentation.
4.1.1.3 Exploitable Results
The main exploitable result of the project is the ProSEco platform, with the main components of this platform having also been identified as exploitable results by themselves.
Exploitable results, which is as follows:
• Result 1 : ProSEco Collaborative Development Platform
• Result 2 : Lean Consultancy
• Result 3 : Eco Tool, Service and Methodology
• Result 4 : Simulation tool
• Result 5 : Data-mining Tool and Services
• Result 6 : AmI Selection tool, monitoring services and Methodology
• Result 7 : Context Modelling tool, extraction services and Methodology
• Result 8 : Knowledge Provision core service
• Result 9 : Security Tool/Enforcement services
• Result 10 : ProSEco Deployment Platform
Table 1: Overview of the ProSEco results
LEADER PARTNER NAME
1.ProSEco Collaborative Development Platform
The ProSEco collaborative development platform provides a web-based technical framework that can be used to integrate a variety of dynamic engineering tools and the core services. This facilitates seamless exchange of valuable knowledge across whole network of actors involved in the creation of Product Extended Services (PES).
Depending on the organization’s demands and needs, the ProSEco collaborative development platform is reconfigurable to adopt a new business environment. For instance, only the necessary subset of the tools that are required in a particular enterprise can be provided. The tools that are available in the platform are:
Eco-tool
Customer and Supplier behaviour (Data Mining Tool)
Tool for the simulation of Meta Products
Tool for definition / design of AmI solutions
Context Modelling Tool
Configuration Tool
Security tools
Service Composition Engineering Tool
These set of tools are available with their complementary core services inside the platform. Apart from core services, the ProSEco collaborative development platform is capable for providing a space to configure the available services with application specific services during the design and development phase.
Leader partner name University of Salford (USAL)
2. Lean Consultancy
Gemba Analysis is a method for identifying potential for innovation in terms of functionalities and services that a product contains. It is focused on the user of the product (for example a machine operator for a CNC machine or a driver for a car). Gemba Analysis is a method of observation of the use of the product and its services in the real place (gemba). It is based on mature Lean Management tools like Standardized Work, TWI-Job Methods, Value Stream Mapping, Consumption Stream Mapping, Go-See-Act and A3 Reports.
Leader partner name LEI
3. Eco Tool, Service and Methodology
This result encompasses a software tool – Eco-tool- (Eco monitoring Engineering tool and the optimization core service and a methodology for Lean-based ECO-driven Product-service & Process Design.
The eco-tool provides users with simplified collaborative product system modeling features and provides LCA techniques that facilitate the rapid calculation of environmental impacts.
The methodology provides a new framework to guide the conceptualization and design of new PES solutions (product extension services) together with the business strategy (business model) that fulfill the user needs, taking into account the reduction of the environmental impact together with the competitiveness of the company and stakeholders; provoking a shift of behavior from consumption (selling product) to use (selling function )
Leader partner name TEC
4. Simulation tool
Web-based Market Simulation Tool enables easy modelling of the complex market contexts of PESs during their design when using the ProSEco Platform.
The Market Simulation Tool is based on extensive critical review of qualitative and quantitative scientific literature related to consumer and market behavior.
It allows industry partners to simulate the meta product offerings in dynamic business ecosystems in order to explore / test effects of alternative offering designs within different business ecosystems
Leader partner name VTT
5. Data-mining Tool and Services
The result consists of a service able to do data mining (mainly predictions) on data gathered from a series of sensors (AmI).
The core service can be used for predicting any data/time series based on some previous n-tuples of values and outcomes. The specific service can be created using the engineering tool.
Leader partner name CNU
6.AmI Selection tool, monitoring services and Methodology
The AmI Selection engineering tool supports the PES designer in the selection/definition of which AmI systems/sensors are needed for the PES being created.
The core service support the user of the PES in the collection and aggregation of AmI systems/sensors (at the product/process) raw data into aggregated AmI based data.
The result is accompanied by a methodology to support the user in selection of AmI systems/sensors at the product and process to be used within PES.
Leader partner name ATB
8. Context Modelling tool, extraction services and Methodology
This result supports the Context Modelling and allows to Monitor and Extract the context of the situation where the PES is being used and by this improve the performance of PES (automatically adapt the PES outputs to the specific context under which the PES or product is used).
Leader partner name ATB
9. Knowledge Provision core service
Provides search over several types of repositories such as Wiki, ERP, data repositories which can be integrated in PES Leader partner name ATB/UNINOVA
9. Security Tool/Enforcement services
A security toolset and deployment framework that includes the following:
-Language for the specification of user and resource attributes and security policies
-Tools to build security database of user attributes and access control policies
-Identification and authentication functions
-Building blocks for distributed reference monitors to enforce the specified access control security policies
-Language for the description of the PES security architecture
-Tools to analyse the high-level security architecture of the PES and to identify the appropriate placement of security building blocks to enforce the specified security policies
-Package of cryptographic primitives needed to implement data protection and security protocols
These provide a framework for ensuring the security of new PES systems and providing required levels of privacy of user data and trust in system operations.
Leader partner name TOG
10. ProSEco Deployment Platform
The ProSEco Deployment Platform provides a SOA based SW Solution of independent modules that support both hosting of resources (i.e. WebServices) specifically developed to perform and fulfill the objectives of ProSEco as well as a Service Broker, specifically designed for the runtime of the PES.
The Service Broker module is the core of the PES Deployment Platform & Service Composition specifically it is the runtime engine for the execution of PES applications. It is an agent-based tool compliant with the FIPA standard. It has been designed and implemented to consume BPMN processes and to allocate the necessary resources for the execution of the PES.
The Service Composition Tool enables the parametrization of the relations and runtime specifications between the resources, under BPMN notation. Also it sets the communication point between the Development and Deployment Platforms.
Leader partner name UNI
List of Websites:
ProSEco contact details and project website
A project web site (http://www.proseco-project.eu/) was established at the beginning of the project to provide wide dissemination of the results, papers, and information in general about the project.
The website offers updates on:
• events,
• newsletters (4 newsletters made along the project lifecycle and available at the project website and distributed by the partners at events),
• news,
• publications (information on the conferences and journals publications and access link to the open access publications),
• videos as e.g. https://www.youtube.com/watch?v=vIZgoD1ky2U and the project demonstrator videos (https://www.proseco-project.eu/project-realisation) and
• newest downloads. All public deliverables are available on the website.
-Fundación Tecnalia Ana Arroyo (Proyect Coordinator) (ana.arroyo@tecnalia.com) Spain
-Institut für angewandte Systemtechnik Bremen GmbH Sebastian Scholze (scholze@atb-bremen.de) Germany
-Instituto de Desenvolvimento de Novas Tecnologias José Barata (jab@uninova.pt) Portugal
-Technical Research Centre of Finland - Business from technology Stephen Fox (Stephen.Fox@vtt.fi) Finland
-Universitatea Tehnica din Cluj-Napoca Oliviu Matei (oliviu.matei@holisun.com) Romania
-University of Salford, Manchester Terrence Fernando (T.Fernando@salford.ac.uk) UK
-Lean Enterprise Institute Polska Stanislaw Plebanek (stanislaw.plebanek@lean.org.pl) Poland
-The Open Group Scott Hansen (s.hansen@opengroup.org) UK
-Volkswagen AG Heiko Wichura (heiko.wichura@volkswagen.de) Germany
-Electrolux Italia SpA Claudio Cenenese (claudio.cenedese@electrolux.com) Italy
-KLÖCKNER DESMA Schuhmaschinen GmbH Karsten Stöbener (k.stoebener@desma.de) Germany
-ONA Electroerosión Jose M. Ramos (jramos@onaedm.com) Spain
-SEMANTIC SYSTEMS Eduardo J. González Fuentes (ejg@semantic-systems.com) Spain
-Alberdi Mekanizatuak S.L. Aitzol Alberdi (aitzol@alberdimek.com) Spain
