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Engineering Apps for advanced Manufacturing Engineering

Final Report Summary - APPS4AME (Engineering Apps for advanced Manufacturing Engineering)

Executive Summary:
Today, manufacturing is being shaped by the paradigm shift from mass production to personalized production, engendering tremendous pressure on companies to deliver personalized products and services to customers. In order to compete, companies must excel on different fronts, including production costs and quality. This is ensured by developing product platforms that leverage upon commonality, modularity, standardization across different products, along process platforms that accommodate flexibility and reusability of the production systems. However, due to dynamic and uncertain markets, companies have to regularly renew their product and process platforms through new production technologies and also factory infrastructure in order to fit explicitly requirements of individual customers. As a result, life cycles of products, processes and factories are shorten, engendering in return an increasing complexity of the various life cycles activities. In order to reduce this complexity, new digital tools are required. However, while current digital tools (e.g. Computer Aided Design (CAD), Computer Aided Engineering (CAE), Production Planning Control (PPC), Manufacturing Execution System (MES), and Enterprise Resource Planning (ERP)) offer distinct value such as saving in time and costs to different life cycle activities when solutions have defined roles and are integrated from both data and processes perspectives, they are outperformed in turbulent markets.

The present final report presents the main results gathered over three years of research in the development of new digital tools aiming at addressing the previously listed challenges and mainly decreasing the complexity of activities associated to shortening life cycles and dealing with the increasing flow of data and information across all stakeholders of all life cycles.
Project Context and Objectives:
Since product mass customization became a viable strategy in the mid-1990s, there has been tremendous market pressure on companies to deliver personalized products and services to customers with mass production efficiency, costs and quality. Several studies claim that the more a company is able to deliver customized goods on a mass basis, the greater would be its competitive advantage. This mass production efficiency, costs and quality are, in this paradigm, ensured by developing product platforms that leverage upon commonality, modularity, standardization across different products, along with process platforms that accommodate flexibility and reusability of the production systems. However, this enormous competitive pressure, which is even more influenced by the new emerging manufacturing paradigm called mass personalization, forces companies to regularly renew their product platforms, process platforms through new production technologies and factory infrastructure, resulting in, not only shortening product life cycles, but also factories’ and processes’ life cycles. Shortening life cycles and volatile non-cyclic demands have engendered that companies are subject to a high level of internal and external turbulences, which consistently affects the complexity of the various activities associated to the three previously cited life cycles. Digital tools are not only required to handle this complexity, which can be hardly handled without, but also to deal with the growing flow of data and information across all life cycles.

Different types of large and monolithic software are used in the products’, processes’, and factories’ life cycles, such as e.g. Computer Aided Design (CAD), Computer Aided Engineering (CAE), Production Planning Control (PPC), Manufacturing Execution System (MES), and Enterprise Resource Planning (ERP). Common drawbacks of these solutions are that there is no seamless information exchange between them, their customization level is restricted and thus not adequate for specialized industries, their high direct and indirect costs and their difficult implementation in decentralized organisations. Such drawbacks limit the use of these softwares and often lead to failed implementations. One major challenge here is represented by the serial nature of the product, process and factory decision making along their life cycles. While the product design is generated and stored within a product model, the process plans are generated based on the product features, the production planning, based on the process plan, is generated with order information. However, there is no synchronisation and integration of data between the product, process and factory life cycle.

This implies that any concepts that would have a holistic forward-looking view on synchronized life cycles would allow to drastically decrease the lifecycles. Nevertheless, an alignment of these three life cycles would induce complexity in planning activities and management of data and information, which can hardly be handled without the support of ICT technologies. Since the employment of a single holistic manufacturing engineering system seems to be not feasible, new knowledge-based methods, technologies and tools to model, simulate, optimise and monitor planned and existing manufacturing systems are required. Such new tools should allow changes to be made at early design stages to the product and the corresponding manufacturing systems in order to maximise the system efficiency. These tools must be smooth in their interaction with human workers as well as working in an integrated way on different shop floor levels along the whole engineering life cycle.

The approach of the project was following: supporting holistic forward-looking view on synchronized life cycles with such-called Engineering Apps to enable an integrated product design, process development, factory and production planning and factory operation. This integration is flexible and is achieved through the deployment of a life cycle-oriented platform, based on a core Reference Model for the holistic planning and optimisation of products, processes and factories along their aligned life cycles.

As outcomes, three main points had been identified:
(1) a proof-of-concept on eApps, a Reference Model and concepts for flexible integration, methods and flexible workflows, aiming at significantly increasing interoperability of product design, process development, factory and production planning and factory operation by intensive use of knowledge in the early phases of Manufacturing.
(2) Various domain specific and inter-domain specific eApps which support the alignment and synchronisation of the life cycles, based on the developed core Reference Model and their flexible life cycle-oriented integration based on Cloud and Grid technologies
(3) Powerful industrial Demonstrators, representing the automotive, machining, food production and logistics, which will validate the feasibility of the ambitious vision and goals of industry partners

Project Results:
Aiming at improving the competitiveness of European manufacturing industry by aligning the life cycles of product, process and factories, the Apps4aME project was structured in 8 WPs. The upcoming subchapters will present the main results obtained on WP level.

1) WP1: Continuous State-of-the-art, Demonstrators Definition and Requirements
The main results of this WP include a continuous comparison of state-of-the-art and beyond the state-of-the-art of the areas of reference models, knowledge management and software modules applied to the problems of product design process development, factory planning and factory operation. These results provided necessary input for the development of the reference model, knowledge-based platform, applications and business models that were tackled in WPs 2, 3, 4, and 5 respectively. Indeed, during this WP, an overview of the standard reference models followed during the product design, process development, factory planning and operation mainly through the VDI organization was done.

Drawbacks of these existing reference models pointed out that the integration of engineering knowledge given by all Factory Level Domains in the early stages of product and process design were challenging. Furthermore, additional challenges were identified. Indeed, while current literature is exhaustive in the field of reference models, it appeared that there is currently no reference model partially covering more than one Factory Level Domain and that by comparing the various existing reference models, different levels of detail were found. As consequences, the integration of the various reference models was extremely challenging.

The chapter dedicated to the application of knowledge management discusses the state of the art of the area of semantic data models, ontologies, knowledge repositories and reasoning mechanisms will guide the WP3 developments. It became apparent that the creation of a complete taxonomy of every interpretation of every term through an ontology have practical limitations, while on the other hand, creating an abstract, high-level knowledge scheme may lose its applicability and problem-solving capabilities. Although knowledge management (KM) has become a critical issue for corporations in the field of manufacturing, several challenges persist. Firstly, a framework for KM implementation should be rigorously defined with particular attention on design, engineering, distribution and information systems, assessing also the effect of KM on productivity through carefully defined key performance indicators. Furthermore, in an ever-changing technological environment, the effect and implications of novel technologies on KM ought to be examined. Manufacturing, in contrast to services, has experienced limited applicability of KM practices as it suffers from several information exchanging issues. It is characterised by a lack of specific terminology and a multitude of terms for describing virtually the same entities. Moreover, there is a lack of integration between heterogeneous platforms such as ERP systems and CAD software. Finally, knowledge management is not as widely diffused in manufacturing firms as it may seem, especially in terms of semantics and reasoning mechanisms. Particularly in SME’s, tools for knowledge management are not implemented, leading to the transformation of organisational knowledge into tacit knowledge, making it difficult to be retrieved.

An analysis of the most significant software modules employed for product design up to factory planning was also made. Existing gaps and shortcomings of existing software modules were identified in order to be addressed in the various demonstrators.

Last but not least, mobile apps and cloud technologies, which can enable seamless collaboration and information sharing, and realize ubiquitous information access and sharing, had also been analysed.

Within this WP, and taking into consideration drawbacks identified mostly in the existing software modules, the Apps4aME demonstrators and the Key Performance Indicators (KPI) were defined. For this, workshops at the three industrial partners were made in order to identify the weaknesses in the current processes.

In terms of opportunities and challenges, as it has been stated, the whole eApp concept requires also standards for development. An exhaustive list of requirements from industrial use-cases, available standards adopted to support the development of the eApps and competencies required was also addressed.

2) WP2: Apps4aME Reference Model
As stated before, synchronizing life cycles in order to enable an integrated product design, process development, factory and production planning and factory operation requires the identification of interdependencies and mappings among these life cycles. Furthermore, despite the mapping of interdependencies, the data and knowledge used within the Factory Level Domains were also identified in order to use this information as a base for the continuously and simultaneously data and knowledge management.

To guarantee the development of a clear and well-structured Reference Model, a common and adequate modelling notation had to be selected fulfilling identified requirements. The Deliverable D2.1 present the detailed scope of the developed Reference Model and also a detailed examination of the state of the art of modelling notations, their advantages and drawbacks. As stated in D2.1 the Reference Model has following characteristics:
• Generic: A Reference Model has to be generic enough in order to enable its instantiation in several industrial sectors.
• Environment-dependent: A scope for the Reference Model has to be defined. A Reference Model is developed to assist and clarify things within a given area. In order to develop a useful Reference Model, a clear description of the problem that needs to be solved must be considered. Inputs from the stakeholders (Costumers, Manufacturing Company and its partners) also need to be taken into account.
• Modular: A Reference Model should be as modular as possible. In that way, it allows the fol-lowing points:
o a functional partitioning into scalable and reusable components;
o a rigorous use of well-defined modular interfaces;
o an easy adaptation of those modules to achieve transparency and allow the use of other industry standards for key activities.
• Extensible: A Reference Model has also to be extensible. In that way, the level of effort re-quired to implement the extension is reduced. Extensions can be done through the addition of new elements or through modification of existing ones.
• Technology independent: A Reference Model should not make references to particular technologies. A Reference Model must be a mechanism used to assist in the understanding of new problems and their solutions. As such, it should be independent of the solutions to be chosen, providing a global added value.

The comparison of the four chosen modelling notations, namely IDEF0, BPMN, EPC, and UML can be found in D2.1. The Business Process Modelling Notation (BPMN) was chosen as the most suitable modelling language to model the phases of the Apps4aME Reference Model.

In order to achieve the alignment of the various life cycles, first a reference model for each domain was developed. These reference models are based on the state-of-the-art of reference models for product, processes and factory’s life cycle and required input from industrial partners. In order to stay generic and enable the instantiation of the reference model in various industrial sectors, the processes and information were defined on a high-level. Details to the specific reference models can be found in D2.3.

While the factory operation includes all task necessary for the manufacturing of a product, such as, the production planning, the logistics, the quality, the production processes and the management of resources, it represents the core information source for all information that have been defined in these four different reference models. For this reason, it was used as a core entity to organize all other domains around it.

Based on this alignment, the information interdependencies between the various activities involved in the four Factory Level Domains were identified and the required data and information were classified according to following criteria: (i) critical / non-critical, (ii) intern/extern, (iii) product, (iv) factory relating to production and (v) factory relating to operation.

This alignment of processes and information allowed the Consortium to develop a generic and flexible merged reference model representing the factory’s internal engineering processes from the design of product to manufacturing. The classification and categorization of information according to source, type and context/content were used as the basis for the development of the Knowledge Warehouse.

Through the third WP, a knowledge-based infrastructure for supporting engineering activities throughout the lifecycles of product, factories and processes was developed. The knowledge features are exploited by smart eApps developed in WP4. The creation of the Knowledge Base and the Reasoning Engine along with the Warehouse Infrastructure of Deliverable, as well as the classification of information types and formal knowledge representation consist the main outcomes of this WP.

Initially, the definition of the concept for facilitating the knowledge flow between the selected technologies from a system intelligence perspective was provided (D3.1). The primary objective is to enable the data, information and knowledge flow needed in subsequent stages of the project, through the definition of a knowledge framework and of its components.

Then taking input from D3.1 D3.2 defined the data model requirements, selected the modelling languages, selected the technology and tools to develop the data model (i.e. to generate and characterize classes as well as relationships), defined the available standards for modelling the contents of the data model and/or definition of new classes not following any standard, and formalised the input form the four industrial use cases to provide a support for the validation of the data model.

The next deliverable (D3.3) described and implemented the Knowledge Warehouse Infrastructure (KWI) implementation. The KWI is closely related to a Content Management System, but goes beyond. It uses OWL ontologies (work results by T3.2) to connect resources to a defined vocabulary. It exploits semantic reasoning (work results by T3.4) extends the ontology by making implicit knowledge explicit. This can be used to better locate and reuse digital resources. The D3.3 report provided the details of the architecture, the conceptual results from the planning phase, and the results of the running implementation.

The final deliverable of WP3 is D3.4 that focused on the creation of the Knowledge Base and the Reasoning Engine (KBRE). The work carried out in D3.4 is summarised into the following:
• Definition of the entire architecture and the description of the KBRE components;
• Description of the module for the mapping of the RDBMS-to-Ontology schemas (i.e. mapping of relational database management system to the ontology knowledge representation model);
• Description of the Knowledge Repository formation;
• Description of the Reasoning Engine and explanations of the rules’ structure used;
• Presentation of the tools that were chosen for the development of the modules;
• Formalization of example rules for pilot cases.

4) WP4: Apps4aME Factory Level eApps
Within the project, 22 eApps were developed. The developed classification of Factory Level eApps allow a categorization of which eApps are generic and can be re-used, or adapted and which one are specific. After having compared and analysed already existing Apps classification, mainly various App stores, the Apps4aME eApps classification, composed of criteria such as (i) operation area, (ii) function, (iii) complexity, (iv) platform and (v) end device was developed.
• The documentation function aims at supporting the documentation process. The term documentation has many meanings; the most common processes are related to the documentation of knowledge or product (e.g. software, factories, mechanical products, etc.) documentation in order to keep this information for any read.
• The visualisation is related to processes that aim at converting data in a general way, into a geometric or graphic representation for easy understanding.
• The simulation function is related to the imitation of the operation, behaviours or functions of a real-world physical or abstract system or process and aims at the estimation of its characteristics or solve given problems.
• Execution is related to the act or process of executing something in the factory. It covers all functions required for eApp-assisted execution and machine control. Examples are the implementation of measures in case of a failure of machine or the dispatching and provision of production orders to workers.
• In the analysis function, a systematic examination of data or information is done in order to understand their relationships and provide the basis for taking decision or solving problems.
• The Data Maintenance function has been integrated in such a way that it allows the availability, reliability and administration of the data or information.
• The design is the creation of plans for the construction of an object or a system.
• The data acquisition is the process of collecting data from the real world via sensors as well from the digital world by adaptors to other information systems.

The complexity of an eApp is related to the required computational power. Furthermore, the autonomy indicates whether it is a standalone, a client-server-based, and web-based or cloud-based eApp. Web-based eApps are specialized forms of client-server-based eApps that do not require any other applications except a web-browser. A cloud-based engineering eApp is also a further specification of a server-based eApp due to the scalability of the required computational power and storage space. The integration field shows the forms of data exchange. Indeed, the possible characteristics for this field are: (i) no data exchange, (ii) a file-based data exchange, (iii) the integration over a local computer internal programming interface or (iv) via a web-based application programming interface.
eApps platform:
This category is split into “Operating software” and “Hardware”, and “End device”. The eApps platform field specifies if the eApp is customized for a particular hardware or a specific operating system. The End device specifies for which types of devices the eApp has been developed. The mobile criterion includes smartphones, PDAs, tablets and laptops while the stationary criterion can be used to define eApps only working on desktop.

In this WP, the Core Factory Data Model (CFDM) was defined, a top-level ontology which describes and covers some of the concepts of the knowledge domains identified in the four studied Apps4aME industrial cases. These latter share this common data model, which aggregates and unifies all the information, thus significantly, enhancing the semantic interoperability between different heterogeneous systems under the form of agents, services or applications.

The Core Factory Data Model is expected to reduce the cost and the time required for the conceptualization of specific domains from scratch. Moreover, it is expected to increase the quality of newly implemented ontologies as the reused components have already been validated. Finally, it should be avoided the confusion and the inconsistencies that may be generated from multiple representations of the same domain, strengthening the orchestration and harmonization of knowledge.
The work reported in this task focused on reporting the enhancement of the competencies of Apps4aME partners as a result of their work in the following dimensions: the definition of the four business cases (requirements and specifications), the design of the work that was conducted (planning ahead), the design and implementation of eApps (software design, development and implementation). This enhancement of existing competencies was necessary in order to the high goals of Apps4aME.

The eApps, that were mentioned earlier, were developed in this WP. A number of these eApps were developed from scratch, while others were obtained or in other ways transferred from previous European, or national, or other projects. Nevertheless, none of the apps was taken off-the-shelf or was applied in the Apps4aME business cases as-is. Numerous modifications were carried out to adapt the existing set of technologies or eApps to fit the concept and needs of its respective Apps4aME business case. These are not only able to instruct operators at shop floor but can also collect feedback and general information used in the overall factory and process enhancement methodology. Each of the eApps guides and supports users in various processes or phases of their manufacturing activities, such as planning, ordering and delivering materials, communicating with co-workers or executing work tasks. In the sense of an app-based approach, these apps work independently and can be removed or replaced if the related process changes. Their integration with other apps shows, that they also provide benefits to each other’s and not only directly to the users, aiming for a fully app supported manufacturing production.

As a next step, the functionality and its effectiveness of every app were measured. All eApps have been fully integrated with their use cases. Afterwards, extensive acceptability tests were performed and KPIs were compared to the situation before the projects. All this information will be presented in upcoming subchapters.

Concluding, the improvement of partners’ competencies was achieved in two dimensions: on a technological IT-related knowledge level and on a business / industry knowledge expertise level. The participation in the challenging Apps4aME project supported both experienced partners to further extend and refine their competencies and new partners to develop new competencies and to strengthen their position in the market. Industrial partners were introduced to the disruptive concept of smart engineering eApps. Moreover, academic partners that were involved in the definition of the pilot cases were acquainted with the true industrial practice and witnessed the gaps that need bridging first-hand. Finally, academic partners and technology providers that were involved in the design, development, and implementation of the eApps widened their IT competencies, constituting them among the first institutions to develop manufacturing-oriented eApps that support the shop-floor, factory, and supply chain functions.

5) WP5: Apps4aME Best Practices and Business Model
The main objective of this WP was to define and develop Best Practices and a Business Model for the exploitation of project results, such as the core reference model (WP2) and the developed eApps (WP3 and WP4).

The work package followed a methodology that consists of 5 tasks, as described in the following points:
1. Analysis of as-Is manufacturing design and engineering business processes of the industrial stakeholders
2. Design and validation of best practices representing the TO-BE business process based on the application of the proposed concepts
3. Definition and measurement of Key Performance Indicators (KPI) for the evaluation of the benefits introduced by Apps4aME
4. Evaluation of the eApps maturity in order to define the TRL level and further developments that may be needed as well identification of benefits; costs and effort for introduction of the developed eApps in industry
5. Elaboration of a Global Business Model in order to demonstrate the creation and delivery of value to all stakeholders involved in the project

The purpose of the analysis of manufacturing design and engineering business processes of the industrial stakeholders is to reach a structured understanding of the As-Is situation, as well as issues and improvement opportunities. The three industrial sectors (automotive, machining and food) were constructed and customized in WP1 where value areas had been identified. In this WP, the as-Is process of these value areas has been further detailed and mapped using the notation selected in 2.1 BPMN.

In the Volkswagen Autoeuropa Use Case, the as-Is process is related with the product development process which has a very difficult and time-consuming monitoring process. To overcome this e-Apps, 3 eApps were developed in order to change the as-Is process from a passive into a pro-active approach.

The Bazigos As-Is process is associated with Costumer Service and with Production and Planning Monitoring. The e-Apps developed improved the standardization of the product requirement collection, the accuracy of the short-time scheduling and allow a real-time production monitoring accurately estimating the product deliverable time.

The CarmOlimp As-Is process was addressed in D1.3 and the e-Apps developed improved the control of the product delivery in order to fulfil the legal food regulations.

Siemens Use Case As-Is process is associated with the logistics process (Inbound and Inhouse). The current improvements are related with the interdependencies that exist and are not automatically synchronized between the different disciplines. The e-Apps developed will aim an integrated logistics planning solution that will support cross sectional planning, synchronization and collaboration with other planning departments.

D5.1 presents a detailed description of the As-Is business process identified in the deliverable D1.3 with the aim of aligning the factory level domains through the use of eApps, in order to maximise the system efficiency. The issues and improvements opportunities have also been identified and were used in the following task D5.2 for mapping the future state. Additionally, the current status of the KPIs was measured having a baseline for achieving the Apps4aME vision and being the starting point for building up D5.3.

The second outcome of WP5 was to identify future best practices resulting from the To-Be business processes of the Apps4aME research project. The work started with the identification of process improvements to potentiate the elimination of the barriers between product, process and factory domains. Additionally, in order to support organizations into the adoption of the new manufacturing processes, the manufacturing benefits were indicated, as well as, recommendations for change management.

This deliverable identifies four potential best practices:
• Flexible process management
• Holistic logistics and production planning
• Supply chain optimization and
• Engineering to order mould design and manufacturing process automation.

Regarding Volkswagen Autoeuropa Use Case 3 areas of improvement were identified: monitoring of the product development process and the associated knowledge reuse and the communication and collaboration process which being supported by the e-apps developed will enable a much faster and efficient product development process. Here the best practice proposed was a flexible process management based on rules, which provides the level of flexibility expected to guide employees to follow companies’ rules and standards but in a creative and dynamic way. This means that employees are able to tackle well-defined tasks in the right sequence but using the suitable methods and tools depending on the problems and context that can arise.

Another mould industry although not in the automotive area is the Bazigos use case where also communication and collaboration processes will be improved. Here the stakeholders are customers and internal departments of Bazigos when developing and manufacturing a new product in which significant amount of information and data flow between them. From this use case the following best practice arose: engineering to order mould design and manufacturing process automation. To support this best practice five e-Apps were developed: Requirement Communication App, Delivery Time Estimation App, Project Core App, Scheduling App and Production Monitoring App.

The CarmOlimp Use Case is focus on the food industry logistics process. Here the process improvements are to ensure the shortest lead time in delivering the product to the customers to ensure the best quality requirements. Three improvements being supported by ICT technologies were described: Temperature tracking, monitoring and analysis, truck allocation and route planning and product packaging.

Siemens Use Case being related with inbound and in-house logistics the process improvement identified is related with the optimization of the logistics planning which requires high synchronization between vertical and horizontal departments.

Regarding change management several methodologies were described that can be used to support organizations in adopting the developed technologies.

The third outcome of this WP was the identification and the main Key Performance Indicators (KPIs) for apps4aME project demonstrators, applied to the characteristics and scope of each specific case. The Key Performance Indicators (KPI) for the processes of Manufacturing Design and Engineering were collected from WP1 and improved taking into account the new methods and eApps developed in the scope of each demonstrator. In some cases, new KPIs were created, following the data that can be collected from the new methods and eApp.

The Key Performance Indicators (KPI) for the processes of Manufacturing Design and Engineering were collected from WP1 and improved taking into account the new methods and eApps developed in the scope of each demonstrator. In some cases, new KPIs were created, following the data that can be collected from the new methods and eApp.

Taking into consideration the defined Key Performance Indicators, a comprehensive Cockpit for the monitoring of these KPIs was designed and implemented. Despite the fully functional cockpit for the monitoring of KPIs, due to the lack of reliable raw data, it was not possible to present final values for all KPIs, however, the industrial partners’ expectations and forecasting, taking into account the real use of eApps in real environments, it was possible to gather figures for all defined KPIs. The results are also presented in deliverable D6.3: Results Evaluation and Action Plan for continuous improvement.

Last but not least, the economics and maturity of eApps were addressed. Methods in the field have been investigated, that are currently in use when important questions of investment into new technologies – specifically ICT – were considered. It has been found, that currently, there are no methods available that fulfil the requirements. Fortunately, in another context, a method for a similar industrial project has been derived and published that has the potential to be adapted.

It has also become clear, that the maturity of eApps is automatically considered if the technical analysis is done in depth. The maturity consists mainly of the maturity of personnel (i.e. qualification) and of the technical surroundings. Both are evaluated in depth in the method.

The method that was created by adoption within this task is a tool for the Apps4aME partners to evaluate the eApps when they are fully introduced. If used for verification, the data gathering should be initiated after the learning processes in the beginning of their introduction. A full documentation of the method is available. The effort for the complete method is significant, especially considering eApps usually are small and very specific solutions. Within the context of Apps4aME the effort can be reduced drastically, as the conception of the eApps has been properly carried out so there is documentation on the functionalities and interfaces that are relevant. Still, the efforts are significant, if a reliable evaluation is required.

The last outcome of this WP is the definition of the Business model describing the exploitation routes identified by partners to monetize the different outcomes of the Apps4aME project. The work started from the analysis of the literature on Business and Revenue models currently implemented in the mobile and digital market in order to understand which are the most suitable ones, in particular for what concerns enterprise mobile applications.

A survey and a questionnaire were then developed to create awareness among the eApps developers and users on the diffusion and profitability of these models and support them in the identification of the most proper according to each specific use case. On the basis of the feedbacks provided by questionnaire results and the refinement of preliminary Business Models defined in WP7, the Apps4aME Business Model has been established integrating the four Business Model Canvas in a unique one.

The implementation of Enterprise eApps calls in fact for the development of new business models enabling to exploit in the mobile market the potential involved. Most of Business models used in the mobile sector are targeted for consumer app developers while manufacturing Apps address B2B with customized application developed for specific needs.

The survey and questionnaire administrated to project partners involved as users and developers of the eApps highlighted the need to create a Business Model with diversified options for specific building blocks according to the different characteristics of each use case eApp group. A unique Business Model including four different Value Propositions, as hereafter summarized, has been developed integrating the models initially developed in Task 7.2.

The CarmOlimp Use Case eApps enable to face the growing demand for product variety, lower prices and high-quality force within the food industry enabling groceries and logistic companies to run, control and monitor their processing and logistic processes as well as handle all the necessary information and documentation.

Thanks to the VW Use Case eApps the manufacturing ETO based companies will be able to run, control and monitor their project and product development processes as well as handle all the information, documentation and interaction (email and messages) leading to higher quality of their product, more punctual and effective deliveries and costs savings.

The Bazigos Use Case eApps will support manufacturers to organize orders, retrieve and exploit stored knowledge, manage product life cycle, schedule production and monitor progress.

Finally a standardized logistic planning application in an open and connected environment to assure higher planning efficiency and improved results with shorter lead time, less storage and transportation costs is made available through the Logistics Use Case eApps.

In conclusion, taking in account the specific requirements expresses by partners, a combination of different streams has been defined in order to generate revenues from the exploitation of eApps and related services.

6) WP6: Demonstration, Acceptability and Evaluation
The WP6 aimed at realizing the Apps4aME demonstrators based on the time-plan defined earlier in WP1. At stated before, four demonstrators were created for respectively: (i) automotive, (ii) machining, (iii) food and (iv) supply chain.

This WP aimed at assessing the performance of the various developed eApps and also their acceptance in the industry. The next tables will show the various KPIs improvement obtained through the use of eApps.

Despite quantifiable KPIs that have been presented, the eApps suite enabled to improve the competitive advantages by increasing the flexibility of direct and indirect processes. Furthermore, eApps provide an easy access to information. Last but not least, they also enabled to eliminate paperwork. Among quantifiable KPIs, the use of eApps also improved the accuracy of data, improved resource utilization, and increased the time required to collect information. Additionally, the company improved its flexibility and reactivity regarding internal and external turbulences.

A technology acceptance model (TAM), which is a version of the Theory of Reasoned Action specially tailored for modelling user acceptance of technology, was developed. Many empirical studies have demonstrated that TAM is a parsimonious and robust model of technology acceptance behaviour. The influence of different factors had been studied through a questionnaire sent to the end-users of the eApps. Factors such as:
 The perceived usefulness, which is defined as the extent to which a person believe that the technology under study will enhance their productivity or job performance. In the end user's view, it is the perceived likelihood that the technology will benefit him in performing a specific task.
 The perceived ease of use, which is defined as the extent to which a person believes that us-ing a technology will be simple. It is a construct tied to an individual’s assessment of the effort involved in learning and using a technology.
 The perceptions of risks, which is defined as a consumer’s perceptions of the uncertainty and the possible undesirable consequences of adopting a new technology.
 The subjectivity, which is defined as the past experiences with mobile devices and the readi-ness for innovation
 The attitude is defined as a person’s inclination to exhibit a certain response towards a con-cept or object

The results indicate that the direct relationships between respectively the perceived ease of use, the perceived usefulness and the attitude are respectively positive. The same can be stated for the path between the attitude and the behavioural intention to adopt the eApps (β_(A→BI)=0,79). Having a look at the three constructs having a direct influence on the adoption of eApps, it seems that the perceived risks and the attitude regarding developed concept have the most important impact. Indeed, while the perceived risk has a negative influence on the behavioural intention to use the eApps, it can be stated that, since there is no path between PR and A, the perceived risk do not influence the attitude regarding the whole concept. The subjectivity has also several influences, direct and indirect, on the adoption of eApps. The subjectivity, representing past experiences with mobile devices, plays an important role in the behavioural intention to adopt the concept. Trust plays an important role in increasing the usability of eApps.

Subjectivity and trust are key factors in the adoption of eApps in manufacturing environment. Taking the results and the questionnaire into consideration, it can be stated that the eApps concept had been adopted by end-users and that the technology acceptance model aims at pointing out which factors may play an important role in the decision of adopting eApps. 92% of the end-users intend to use the eApps on a permanent basis, 98% expect to continue using eApps in the future and 90% expect to purchase other eApps in the future.

Potential Impact:
The transition from mass production to personalised, customer-oriented, and eco-efficient manufacturing is considered to be a promising approach to improve and secure the competitiveness of the EU manufacturing industries. Focusing on the first transition, one condition is the availability of agile IT systems supporting this level of flexibility on different layers, namely: (i) production network, (ii) factory, and (iii) process. The development of Internet, communication techniques and new generations of computers trigger the transformation from traditional production-oriented manufacturing to service-oriented networked manufacturing as well as cloud computing. Over the past few years, attention has been given to the use of ICT technology through mobile manufacturing applications. While 79% of consumers use mobile device for games and social networking, more and more manufacturers are slowly adopting eApps designed for specific business and plant operations. Cloud-based applications including e-business, e-commerce, on-demand collaboration, event-driven decision support systems are emerging. Despite the significant costs of requisite initial capital investment in hardware, software, manpower development, and business process, the adoption of these technologies is growing slowly. While a couple of manufacturing engineering eApps had been developed, the exploitation of them is still in its infancy. Indeed, while a few applications have been reported, many core activities of products’, processes’ and factories’ life cycle have not been covered yet.

The Apps4aME project proposed a framework, in which, eApps access, update and use the contents of the life cycle-oriented data model, which provides a consistent information interchange between all processes and stakeholders involved and makes related information understandable, reusable, and changeable through the entire production system life cycle.

In terms of opportunities and challenges, the development of eApps requires manufacturing-specific frameworks and standards, e.g. life cycle-oriented data model developed in the Apps4aME project. Also, a unified device management and centralized method for the distribution and update of eApps is required. Last but not least, the use of eApps poses, however, new requirements on the enterprise IT architecture. As stated before, back-end-integrated eApps need a unified and easy access to a central data management. This engenders the need to integrate eApps in a coherent, scalable, and manageable fashion requiring a new IT landscape based on service-oriented architectures, paradigm integrating heterogeneous IT systems as unified services, mostly based on web services technologies. Shortening life cycles will also decrease the life cycle of eApps and thus this service-oriented architecture also need to be flexible in order to quickly define and install new eApps. eApps also require an eApps store in order to deploy and manage eApps across multiple platforms. Since all eApps have to be deployed there, their reliability with respect to security and privacy plays an important role. As consequences, three major topics need to be addressed, namely the back-end integration, mobile device, and communication channel security. Authorization and authentication mechanism to access internal data in the central data management through back-end systems are required in order to prevent illegal use of resources. Mobile devices and their operating systems also need precautions to not only ensure the confidentiality of used data regarding typical malicious software but also additional security systems in case of stolen or lost devices. Communication, e.g. through Wi-Fi or UMTS, between the various eApps and the central data management, also need to be encrypted to prevent security and privacy issues during data exchange. Corresponding protocols, such as Transport Layer Security (TLS), which are well established, have to be consequently used for all communication activities. Anonymity of end users is also an important requirement. The disclosure of a mobile user’s identification allows unauthorized entities to track e.g. his/her moving history or current location. Security is one important requirement for the whole requirement. Indeed, the number of global users for mobile devices has crossed the number of users for stationary devices in 2014, and mobile devices become more and more interesting for data thieves.

While it has been shown with that eApps offer succeeded efficiently and offer better alternative compared to the current digital tools and the concept had been accepted within the consortium; the question of acceptance outside the consortium can arise. Indeed, these are first results about manufacturing eApps that are promising. Speaking about eApps, two major points have not reached maturity, namely the security and privacy of the whole concept. As consequences, three main issues still need to be addressed to fully use the power of eApps and revolutionize the manufacturing industry, namely the back-end integration, mobile device and communication channel security. Authorization and authentication mechanism to access internal data in the central data management through eApps are required in order to prevent illegal use of this information. Mobile devices and their operating software also need additional security systems in case of stolen or lost devices. Communication between eApps, through Wi-Fi or UMTS, also needs to be encrypted to prevent security and privacy issues during data exchange. Last but not least, privacy of end-users also needs to be addressed by allowing them to avoid unauthorized entities to track private information, e.g. moving history or current location.

Taking into account potential impact, when the privacy and security issues will be solved, eApps will not only provide better alternatives than current digital tools but also be accepted in manufacturing environment. This phenomenon is represented by the correlation of cloud and non-cloud enterprise applications market worldwide. While the market share for license and maintenance of classical digital tools will decrease, the cloud subscriptions are currently increasing. However, revenues are based on estimation from 2015 to 2019. Using the good impact of eApps on the use-cases of the Apps4aME project and the full potential of eApps in manufacturing environment, the cloud subscription is expected to increase exponentially while security and privacy issues will be addressed.

This is conjugated with the paradigm transition based on Industrie 4.0 paradigm in which virtual and physical worlds are combined together to create a truly networked world in which intelligent objects communicate and interact with each other. Cyber-physical systems represent the next evolutionary step from existing embedded systems. Together with the internet and the data and services available online, embedded systems join to form cyber-physical systems, which can also be seen as services. This will give birth to “smart factory” concept, which requires high level of automation, flexible network of cyber-physical system-based production processes. These production systems will able to respond in almost real-time conditions.

Coming back to the requirements engendered by eApps, one open platform, where diverse IT suppliers could upload their eApp according to specific interfaces, would enhance the eApp concept. This would also generate new revenues.

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