Final Report Summary - VFF (Holistic, extensible, scalable and standard Virtual Factory Framework)
Executive Summary:
Manufacturing is a dynamic socio-technical system, which is operating in a turbulent environment. Changes are normal and continuous at all levels and the competition is forcing manufacturers to improve the quality, reduce the delivery time and lower the cost. The approach presented in VFF supports the manufacturing enterprises to face these challenges. The project uttermost objective is to foster and strengthen the primacy of Future European Manufacturing by defining the next generation Virtual Factory Framework. The VFF will promote major time and cost savings while increasing performance in the design, management, evaluation and reconfiguration of new or existing facilities, supporting the capability to simulate dynamic complex behaviour over the whole life cycle of Factory, approached as a complex long living Product. Thus the project will research and implement the underlying models and ideas at the foundation of a new conceptual framework designed to implement the next generation Virtual Factory, also meant to lay the basis for future applications in this research area.
VFF is a research project that aims to the Holistic, extensible, scalable and standard Virtual Factory Framework.
VFF promotes major time and cost savings increasing performance in the design, management, evaluation and reconfiguration of new or existing facilities, supporting the capability to simulate dynamic complex behavior over the whole life cycle of Factory, approached as a complex long living Product.
VFF supports the deployment of a next generation Virtual Factory promoting the EU manufacturing competitiveness. It’s based on four pillars which collaboration leads to the realization of the Virtual Factory concepts.
In VFF project (n° 228595, funded by the EC) perspective, the extended enterprise is called Virtual Factory Framework (VFF). It can be defined as “An integrated collaborative platform aimed at facilitating the sharing of resources, manufacturing information and knowledge, while supporting the design and management of all the factory entities, from a single product to networks of companies, along all the phases of the their lifecycles”
The main idea is related to the possibility to realise in parallel to a physical plant also its virtual representation in order to have a place for making all kind of tests before the real plant is completed and, then, without interfering with its operations.
The Virtual Factory (VF) concept has various definitions depending on viewpoints and perspectives, in this paper VF is defined as a VR environment (VRE) that provides, trough the integration of other IT tools, a transparent description and simulations of a real factory to users who could even be separate in time or space by the real entity. In literature such environments are also called Digital Factory or Virtual Manufacturing.
The VF can support the design and management of a production environment by addressing various key issues like:
(a) Reduction of production times and material waste thanks to the analysis of virtual mock-ups,
(b) Development of a knowledge repository where people can find stored information in different versions, with both advisory role and support to the generation of new knowledge,
(c) Improvement of workers efficiency and safety through training and learning on virtual production systems,
(d) Creation of a collaboration network among people concurrently working on the same project in different places.
In order to orchestrate and synchronise the whole amount of data and knowledge produced by the factory applications and to provide them to the VF interoperability platform is needed.
Jointly with introduction of software tools in the Factory the problem of interoperability among various tools is arisen. Several example of framework are available. Since not just the data have to be exchanged by the applications but, where possible, also the knowledge, in the last year the interoperability framework are more and more looking to the potentiality offered by the semantic web technology.
Project Context and Objectives:
Manufacturing has to cope with a more and more complex and evolving market environment: on the one hand the world crisis breaks the balance between demand and production, on the other hand the globalised market pushes for a continuous change. In this context, the ManuFuture technology platform has already proposed some activities to enable the transformation of European Manufacturing Industry into a knowledge based sector capable of competing successfully in the globalized marketplace (ManuFuture 2006). The ManuFuture vision identify the following priorities to reach future competitiveness and sustainability: development of new high-added-value products and services, new business models, new manufacturing engineering, emerging manufacturing science and technologies and transforming R&D and educational infrastructures. Herein the presentation of the new research project titled “Holistic, extensible, scalable and standard Virtual Factory Framework” - VFF (FP7-NMP-2008-3.4-1) highlights its answers to these requirements.
The market proposes new software tools to help the enterprises in facing new market needs (e.g. Siemens PLM solutions and Delmia), but usually only big companies can afford the large investments required by these tools. Therefore, small and medium enterprises (SMEs) are still looking for successful customised and less expensive solutions, which are more suitable for their size and needs.
Innovative methodologies and technologies should influence enterprise strategies, product development and production processes. The Virtual Factory (VF) paradigm, can assist to answer to this need for innovation by addressing several key issues:
• Collaboration among people working on the same project in different places but at the same time.
• Reduction of production times and material waste thanks to the analysis of virtual mock-ups of new products.
• Development of a knowledge repository that is a common place where people can find any kind of stored material (designs or documents) in different versions.
• Creation of a common working place for collaborating in remote situation where members of a network act and operate on various stages of the same production chain.
• Improvement of workers efficiency and safety through training and learning on virtual production systems.
In achieving these objectives new and innovative methods, technologies and tools have to be employed in planning and permanently optimizing the factory operations and its corresponding manufacturing processes. The previous experiences, both from the research and industrial side, result to be not fully efficient because they aim only at partially innovating the factory processes and the integration with the pre-existent ones is difficult. Information Technology infrastructures or new technologies are too expensive for SMEs because of investment and/or management costs. On one hand, there is need for more and more complex production systems with diverging target systems requiring extensive upstream production planning at the highest resolution; on the other hand, the time frame for the planning process is decreasing and existing tools are complex and expensive.
The Virtual Factory consists in an integrated simulation environment that considers the factory as a whole and provides an advanced planning, decision support and validation capability. The Virtual Factory Framework (VFF) implements the framework for an object oriented collaborative virtualised environment, representing a variety of factory activities meant to facilitate the sharing of factory resources, manufacturing information and knowledge. The VFF promotes major time and cost savings while improving collaborative design, management, evaluation and reconfiguration of new or existing facilities. This requires the capability to simulate dynamic complex behavior over the whole life cycle of the Factory that is considered as a complex and long living product. The VFF approach identifies four key research pillars that must be addressed:
I. Reference Model. The Reference Model for factory planning is based on the development of two key concepts: the “factory as a product” and the “non-linear non-deterministic planning methodology”. The Reference Model establishes a coherent standard extensible data-model at the base of the common representation of Factory Objects.
II. VF manager. The VF manager handles the common space of abstract objects representing the Factory. This representation is based on the standard data model.
III. VF modules. The VF modules are the decoupled functional modules that implement the various tools and services for the Factory design, evolution, evaluation, management, etc. They all operate on the same common space of abstract objects.
IV. Knowledge. Knowledge is the engine for the VFF Concept and it has to support the modelling of a wider range of complex systems and provide greater comprehension of modelled the phenomenon.
The collaboration of the four pillars leads to the realization of the Virtual Factory concepts. The Factory Data Model formalises the information generating an overall picture of the factory together with its characteristics, allowing the modelling and handling of data on real-time. The data used for the development of the Data Model is stored in the Knowledge Repository, where it can be further exploited. The VF Manager Core supervises the common space of the framework, ensuring that all pillars, together with their respective components and actors, interact smoothly.
The Virtual Factory, deployed according to the VFF concept, will be permanently synchronised with the Real Factory to achieve time and cost savings in the design, ramp-up, management, evaluation and reconfiguration of the Real Production itself. The Real Factory, interacting in terms of feedbacks and of data needed to set-up and up-date the simulation system, closes the loop. The need of verifying the impact of the VFF approach on the Real Factory asks for the cooperation of industrial partners to define demonstration scenarios that aim at testing and validating the proposed framework. Within the project four demonstration scenarios have been formulated by pairing different factory planning processes and industrial sectors:
1. The first scenario deals with the Factory Design and Optimisation in the machining sector. The VFF tools will be used to design (or re-design) the factory, aiming at higher solution efficiency and effectiveness, and to optimize the configuration of the production systems. This scenario is developed with the cooperation of the industrial partners Compa S.A. and Ficep S.p.A.
2. The second scenario addresses the Factory Ramp-up and Monitoring in the automotive and aerospace sectors.
The VFF tools will enhance the capability to monitor the real factory and improve the set-up activities during the ramp-up phase. Volkswagen Autoeuropa and Alenia Aeronautica S.p.A. are the industrial partner involved in the second scenario.
3. The third scenario faces the Factory Reconfiguration and Logistics in the Automotive and white-goods sectors.
The factory reconfiguration decisions can be supported by simulation and optimization tools, whereas logistics decisions need VFF tools to efficiently face variable demand by means of flexible networked operations. This scenario will be developed with the support of the industrial partners Audi Hungaria Motor Kft. and Frigoglass S.A.I.C.
4. The final scenario called “Next Factory” aims at demonstrating the applicability of the VFF on the entire factory life-cycle. This integrated scenario focuses on the wood-working sectors thanks to the contribution of Homag AG.
Project Results:
The schema in the annex called VFF Framework Brochure shows the architecture of the main result of the project.
Since digital manufacturing technology has become the most important tool for companies to enhance the competitiveness of their products, the Virtual Factory Framework aims at create a standard able to connect different layers of a factory, probably the most effective path to be followed to enhance manufacturing productivity.
Data and Knowledge coming from different industrial domains and processes converge in the shared Data and Knowledge Repository. The common Virtual Factory Data Model assures a comprehensive vision of the information and the possibility to share it with different actors along the factory life-cycle.
The shared Data and Knowledge Repository is governed by the Semantic Virtual Factory Manager (VFM) that provides an open integration platform representing a common and shared communication layer between already existing and newly developed software tools to support the factory design and management. It provides the functionalities of access control, data versioning and selective data query.
The Decoupled Virtual Factory modules are software tools and applications used to support specific activities in the product/process/factory life-cycles. They are listed here below and in pdf in Annex called VFF Modules. These modules are integrated in the framework and can access and modify the shared factory data thanks to the services provided by the VFM.
Finally, the shared data repository can be synchronized with the Real Factory thanks to the Factory Image module, thus closing the loop with the External Data & Knowledge.
Dysfunction Analysis Module – DAM UTCN
This module aims at gathering, filtering, analyzing and elaborating data related to machine failures and repair activities. The main objective of DAM is to support the performance improvement of a production system, in particular during the ramp-up phase.
BENEFITS
• Automated process for failure analysis
• Enable concurrent work
• Integrated failure results accessible by one tool
• Easy and fast chart/report generation, no manual work
• More accurate MTTR, MTBF as well as other production indicators
• Drastically reduced time for the entire analysis process
• Improved production system performance
• Indirectly improve also the future proposal phases
DSM – Decision Support Module LMS, CASP
DSM: Development of a new model supporting the decision making of production line alternatives.
DSM Key functionalities:
• Systematic evaluation of production line alternative configurations employing utility theory
• User Friendly Interface allows the presentation of complex and numerous data in an effective way.
• Integrated with the VF Manager that allows to exchange data with other modules.
Design Synthesis Module – DSM UTCN
The main objective of this module is to improve the Proposal and Design&Development processes and at the same time to facilitate and fasten up the work of the departments involved in these business phases.
BENEFITS
• Avoid using the existing heavy spreadsheet files
• Avoid having so many manual computations
• Parallelization of the work for several departments
• Enable concurrent design, integration with other tools
• Speed up the definition/evaluation of the production resources
• Enable quick reuse of data (other solutions, other projects),
• Easy adjustments of pre-existing proposals
• Shorten the time needed today for proposal phase
EUVEDES – Discrete Event Simulator EUVE
EUVEDES is a module for easy and simple simulation of production sequences in serial production. It is integrated on to the VF Manager, downloading production planning.
New EUVEDES developed key functionalities:
• Calculation and evaluation of KPI: o Production –throughput-
• Energy consumptions –working and idle-
• Taking into account different cycle times per product and per machine
• Taking into account machines MTTR and MTBF.
• Permitting several products in the same machine at the same time
• Connected with PSI FPS production planning
Factory Image FATRONIK, ITIA, UTCN, COMAU
FACTORY IMAGE: VFF-Module that provides real factory data to be used on the factory performance simulations and calculations
FACTORY IMAGE key functionalities:
• Generic Factory data acquisition
• Generic Factory Data Processing scripts independent of the Data source
• Local Storage of Factory Data
• Data feeding to the Virtual Factory Manager
Offered Benefits:
• Factory Performance Measurements are independent of the evolution of the Factory hardware, process characteristics and workload, as they are conceptually managed in the semantic database and then they mapped in real time to the factory reality.
FLP – Factory Layout Planner SUPSI-ICIMSI
The Factory Layout Planner is a multi-client - server application that supports collaborative remote factory layout planning an runs on classic devices (e.g. a PC with mouse and keyboard) as well as on innovative multi-touch devices. FLP is meant to be used in the phase of configuration and reconfiguration of production plants, allowing easy arranging of 3D elements on 3D layouts, simplified guided construction of the 3D model of the building that will host the real production plant, and support to “what if” analysis of the system performances using the embedded discrete events simulation (DES) engine.
FP³ Factory Performance and Process Planning Module
IPA
FP³: New VFF-Module as enhancement and VFF VFM integration of the commercial process planning system „Process Designer“ from Siemens Industry Software.
FP³ - VFM implemented Siemens Process Designer key functionalities:
• Planning and optimization of technical production processes (process times, process plans, process graphs, associated products…).
• Planning and optimization of the production resource structure.
New FP³ developed key functionalities:
• Calculation, visualization and evaluation of:
• Technical performance indicators (capacity, loading, etc.)
• Economical performance indicators (production costs, maintenance or material costs, etc.)
FPS – Production Fine Planning System PSI
FPS is a module for fine planning production sequences in serial production. It is implemented as extension of PSI’s Control Station for Production Fine Planning using the integration to the VF Manager.
New FPS developed key functionalities:
Calculation and evaluation of:
• Integration to VFM-environment
• Calculation of production sequences
• Calculation of technical performance indicators (“cycle time”)
Factory Templates – FT INESC
Scope and Goals
This tool can be seen as an intuitive Knowledge Management system, which allows not only seeking information, consistent with the context in study, but also reusing this information. Moreover, it supports the improvement of the activities that are considered the bottlenecks of the processes and finally stores the changes made in Knowledge Repositories Systems oriented to factory life-cycle structuring, in order to make it available to all workers and partners of the company.
Due to the capability of continuously monitor the behaviour of the factory and project the future performance of the system in study, the Factory Template Framework make it possible to analyse if the factory performance is in the desired direction. If not, it enables managers to understand the reasons why it is not, and the corrective actions that should be done.
Approach
To allow the achievement of this significant advantage, Factory Templates architecture is divided into two main modelling perspectives, static and dynamic. The static perspective enables the application of the “Factory as a Product” paradigm (simultaneous/concurrent engineering). On the other hand, the dynamic perspective has as main advantage the continuous factory life-cycle evaluation. With this component, the Factory Templates make it possible to follow and improve processes, detecting bottlenecks.
Benefits
By the implementation of the PMD, companies become capable of :
• Reduction of Design and implementation times, increasing overall Manufacturing performance;
• Guarantee Concurrent/Simultaneous Engineering in order to improve the Factory and Products processes integration;
• Decision support, regarding processes design, deployment and continuous monitoring and improvement.
GIOVE Virtual Factory
ITIA-CNR
GIOVE Virtual Factory (GIOVE-VF) is a virtual reality collaborative tool to support the design, visualization and exploration of a factory.
Developed by ITIA-CNR onto the C++ library GIOVE (Graphics and Interaction for OpenGL-based Virtual Environments).
Design functionalities
Creation of objects, import of object libraries, placement of objects in the factory (Direct object placement, 3D widget manipulation, Movement constraints, Tape measure tool, Distance editing), Object properties editing, Layout drawing import (DXF 2D), Multi user shared Virtual Environment, Visualization of process plans, Visualization of simulation result
Visualization functionalities
Free navigation, Viewpoints definition, Stereoscopic 3D visualization, Customizable background
Benefits
Delivered for free; simple to use and to install; it can run on a simple notebook as well as in immersive VR systems; it provides a shared virtual environment where users can collaborate on the same activity; it can exchange data with other tools thanks to standard input/output file formats (.xml, .rdf, .owl).
iDecisionSupport – iDS ROPARDO
iDS is a Collaborative Working Environment where team members attend to different types of meetings (work sessions).
It facilitates Decision Making processes for both groups and individuals.
Features
• Reduces the Decision Process’ time
• Remote work (via Internet)
• E-mail notifications for easily tracking the Decision Process
• Synchronous and asynchronous collaboration
• Common framework for Decision Support tools’ integration
• Common language for Decision Support tools information exchange
• Easy to use
IMPACT – Intelligent Manufacturing Planning And Control Tool LMS & CASP
IMPACT: Integration of IMPACT module for supporting short term scheduling of factories.
IMPACT Key functionalities:
• Short Term Scheduling of Manufacturing Systems optimizing time, cost, utilization and quality performance measures.
• User Friendly Interface allowing to model easily and quickly factory resources and configuration, product orders. Schedule’s Gantt chart and key performance indicators are provided.
• Offers a list of dispatching rules (FIFO, LIFO, SPT) for scheduling, while new performance measures to be optimized can be added.
• It has been used in various industrial sectors such as, automotive, shipyards, refineries and food industry.
• Integrated with the VF Manager that allows to exchange data with other modules.
iPORTAL Virtual Factory – ROPARDO
iPORTAL – VF it is a virtual location with a dashboard-like interface integrating different modules and therefore offering the user a central information point.
Features
• Track the status of the projects (integrated with VFM)
• Documents’ management
• Manage the agenda & email
• Track the news and announcements
• Manage the meetings where the user is involved
• Access the external databases (catalogues, standards)
• Easy customization of users’ environment look and feel
• Access to other web tools (third party)
• Efficient and effective management of (structured and unstructured) data
• Knowledge Repository - unstructured info (wiki technology)
• Supports collaborative work
• Single Sign On technology
Interactive Projection System (IPS) CEIT
Interactive Projection System (IPS) represents an integrated concept for intuitive team-oriented factory planning, which enables planners to accelerate and optimize the planning process. It contains tools for layout design and optimization, material flow and transport routes optimization.
Module functionalities
• 3D visualization of buildings, factory equipment, AGV systems and logistic trajectories
• Detailed design and optimization of production layout
• Analyses of material flows
• Check for compliance of safety margins
• Definition of safety margins of the object
• Manual and semi-automatic design of trajectories for AGV systems
• Real-time simulation and testing of AGV systems implementation
Main benefits of the module
• Acceleration and optimization of the planning process (layout planning)
• Layout and material flow optimization
• 3D visualization
• Physics simulation
• Collision detection
The main innovation and the enhancement of IPS with respect to software solutions available on the market is its intuitive user interface for untrained users and the support of team oriented work, what guarantees effective and fast solution of the problem. The modularity of the IPS module ensures its accessibility also for small and medium enterprises. Another significant innovation is using physics simulation in the IPS module. IPS is also focused on real-time simulation and testing of AGV systems implementation; other competitor software does not support this functionality.
KAE - Knowledge Association Engine
LMS & CASP
KAE: New VFF-Development for supporting Knowledge Management for factories.
KAE Key functionalities:
• Capturing, Storage and Retrieval of Knowledge in terms of Past Projects supporting the Design and Planning of Manufacturing Systems
• Past Projects Knowledge concerning Processes, Resources, Products, System’s Configuration and Key Performance Indicators
• Knowledge Capturing employing ontological modeling of the manufacturing systems domain enhanced with “IF-Then” Rules
• Knowledge Retrieval utilizing similarity measurements and inference rules execution. Past Production Lines with characteristics close to the requirements of the new line are identified.
• Implemented as a web based tool with a user friendly interface
• Integrated with the VF Manager that allows to exchange data with other modules and capture Knowledge related to all the factory lifecycle phases.
PAD Process Automation Designer based on HIL TECNALIA
PAD: New VFF-Module based on a Hardware in the loop simulation of the production sequence on a critical machine (Angular transfer machine) presented in the HOMAG production line.
PAD key functionalities:
• Closed loop simulation of the production sequence using the machine and controller dynamics in order to calculate real cycle-times.
• Interaction with the time-GAP between pieces and the velocity of the machine.
New PAD developed key functionalities:
Calculation, visualization and evaluation of technical performance indicators (Cycle time of the Angular Transfer machine) with collision detection. Adaptation of the production sequence time.
Potential failure modes and Effects Analysis – PEA ROPARDO
PEA is a FMEA-driven software tool for the improvement of product engineering quality of any manufactured product.
Features
• Contains catalogs ensuring nomenclature standardization
• Automatically calculates Risk Priority Numbers (RPNs)
• Supports multi-user environments
• Tracks actions’/tasks’ deadlines
• Automatically generates the FMEA form
• Displays the hierarchy of all FMEA structure from the first level (product or process and their functions) down to the lowest levels (recommended actions)
• Enters and views FMEA data in the traditional worksheet format, an intuitive hierarchical tree view, or filtered lists.
• Reuses information from existing analysis by importing FMEA information from Excel, copying/pasting portions of another analysis, or selecting descriptions from existing FMEAs
• Transfers data to other Windows applications such as text editors, spreadsheets, databases, and more
Steel-Projects PLM SPF
Steel-Projects PLM is a software suite designed to control production at a factory level on a production job basis.
Steel construction seldom dealing with standard parts, Steel-Projects PLM is able to import entire CAD files for buildings or bridges and grind them down to elementary parts to fabricate.
Parts are grouped into bars to optimize raw material usage. Then, a second level of optimization occurs for creating work batches that will increase machine tool saturation and overall factory throughput.
Actual factory data are collected to enhance the optimization algorithms.
Being a standard commercial software, Steel Projects PLM is connected to the VF Manager via a connector module that will allow bidirectional transfers of information between the VF repository and its internal database.
The connector modules can retrieve manufacturing system equipments and organisation and write production batches description.
Performance Measurement Dashboard – PMD INESC
Scope
Nowadays, companies have a huge amount of data stored within different sources along the factory. Hence, Performance Measurement Systems (PMSs) have been developed aiming to support decision-makers by gathering, processing and analysing quantified information on performance and presenting it in a succinct format.
Goals
PMD was designed not only to measure the performance of complex manufacturing systems but also to be generic enough to be easily integrated within the production system environment, integrating data from multi-sources in a user-friendly way, interpreting the production system structure, calculating indicators in a dynamic way according to the formula specified and comparing the values obtained with the expected ones.
In order to simplify the KPIs metrics definition, the PMD solution allows the manufacturing system manager to build and store the different KPIs using Drag and Drop functions. With this innovative solution it is possible to quickly analyse the system performance, drill-down problems, detect which are the causes that are negatively affecting the system performance and apply the corrective actions necessary in a more efficient way.
Benefits
By the implementation of the PMD, companies become capable of decreasing:
• Time constraints: the time needed to calculate each indicator and broadcast a performance report by the different stakeholders.
• Effort need: the number of resources needed during the calculation and assessment process
• Learning curve: time needed to train a new performance measurement technician.
Production Simulation module – PS SZTAKI
PS module is based on Java client that is responsible for VFM connection, ontology translation, simulation control
The simulation engine is based on SIEMENS Tecnomatix Plant Simulation running in background. For the ProdSim module the Plant Simulation 10.1 license is required. In the PS module the focus is not on layout but on process analysis, bottleneck identification and optimization of process parameters and execution control
Main benefits
• The simulation models are built and parameterized upon a totally automated way
• Enables off-line analysis in the design phase
• Enables on-line analysis during the operational phase
RDV - Report and Data Visualization SZTAKI
The main functionality is to visualize and report the main KPI-s of a simulation project .
Provide a user friendly interface for the control, initialization and input data provision of the PS module.
The module can be also used in other scenarios as it requires standard input.
In the case of larger amount of data (e.g. time series) the input is provided from data base or txt file
RMP- Requirements Management and KPI Planning ETHZ, NOVA
RMP: New VFF-Module for supporting Requirements Management and KPI Planning for factories.
RMP Key functionalities:
• Acquisition of all function requirements coming from strategic goals, future needs, product specification and sustainability issues in a structured and formalized way from different sources
• Allow refining and improvement of the existing function requirements
• Storage of the functional requirements, their dependencies and the identified KPIs in a formal model to allow data export and different views for supporting exploitation
• Offers integration and connection with the VF Manager and is able to exchange data with it in order to utilize the integration with other modules in the scenarios
• Additionally the fulfillment of the functional requirement can be traced and monitored by mapping/assigning KPIs to it. Therefore KPIs may be newly defines or simply be re-used from a library.
• For each KPI-mapping a target value can be specified and thus represents a performance goal that has to be achieved be the envisioned production system.
Requirements Management Workflow – RMW ROPARDO
Web application which guides the user during the various development phases or during the changes of a project (factory line).
Features
• Speeds up the decisions based on quick vizualization of the status
• Executes workflow definitions (templates)
• Reduces the hardware resources for each member
• Access to the newest version of documents
• Easy to check/track the status of started projects
• Integration with MS Office tools
• Increases collaborative work
• Manages the templates
• Notifications for involved departments
• Authorized access to project information
• Real time status
SIMIO SimX
Main innovative features:
• Full DES with 2D-3D visualisation
• Reusable catalogue of components
• Combined object-oriented and process-oriented modelling capabilities
• Risk-based Planning and Scheduling (RPS) in Experimentation Mode
SVCP - Site and value-added chain planning RWTH – WZL
Functionalities SVCP-Module
• Analysis and evaluation of dynamic production networks and production configurations
• Site and cost optimized distribution of the value added on various resources
Main activities:
o Modeling, simulation and configuration of complex, dynamic production networks
o Consideration of the dynamic development regarding various indicators, e.g. personnel, machine, material, transport costs and lead times
o Simulation-supported evaluation and comparison of dynamic production networks against qualitative criteria (flexibility, delivery reliability, ... ) as well as quantitative criteria (number of resources, costs, manufacturing lead time, initial investment, resource utilization)
WITNESS INTEGRATION LMS & CASP
WITNESS INTEGRATION: Integration of Witness Discrete Event Simulation tool
WITNESS INTEGRATION Key functionalities:
• Integration of a commercial Discrete Event Simulation tool.
• Development of simulation models for commercial refrigerators production facilities and machining work centers.
• Detailed assessment of key performance indicators such as flowtime, production cost, throughput, work in progress.
• Integrated with the VF Manager that allows to exchange data with other modules. Data such as resources and their characteristics, bill of materials, bill of processes.
Potential Impact:
VFF outcomes of the project will have substantial impact on the promotion of strategic targets of the European Economy and Society. These targets regard mainly the competitiveness of European industry, the employment, the environment and the quality of life.
The main output of the project is a fully functional platform, which will be developed upon a completely novel paradigm using the semantic web approach to store the data of the entire Factory in a unique repository with a common data model.
In this economic crisis period the companies that are in danger are mainly the small and medium ones. If the big companies can rely on diversification of investment and consequently possibility of facing difficulties, the SMEs normally cut the innovation amount focusing on the production as it is.
But Factory is a complex system including many different activities. Nowadays each activity along the entire product life cycle inside the factory is handled one by one with different applications each one developed by different ICT company, using his own language and platform for saving data. Information generated by a department must be treated by the following production step and it’s crucial that all the software and tools inside the factory can access to the information.
Despite Interoperability in a factory is essential, it’s still a vision.
The impact on SME is two-fold. On one side, the democratization of the VF will open the access to those tools for manufacturing SMEs, making them benefit from the mentioned advantages. On the other side, the main goal is also to bring new and dynamic KI-SME (Knowledge Intensive SMEs), which are IT solution providers, from “high-tech” to “high-impact”, that also imply a rapid transformation of science results to markets applications
Challenge of the VFF consists in the innovative integration of product, process and factory domains and related data in a unique Data Repository, using a common Data Model. This can empower the productivity of the enterprise lowering the costs for treating the entire cycle.
The use of new technologyes and in particoular Virtual Reality linked with simulation, facilitate the design of a new production line optimizing the row materials flow avoiding possible bottle necks among different machines.
A VIRTUAL representation of the FACTORY can empower the synchronization with the real one. It can promote cost savings in the implementation of new manufacturing sites or reconfiguration of existing ones thanks to the effective virtual representation of building, resource, process, and product.
Impact and avantages of the VFF results are listed below:
Reduction of adaptation and reconfiguration time: The virtual factory framework will provide consistency over the planning and design process by providing a mutually accessible “information market place” for results and assumptions of all planning objects, synchronizing both services and virtual model via a generic modelling language. This information market place will overcome the isolation of the individual planning tasks and simulation tools, reducing adaption and reconfiguration time.
Reduction of ramp-up phase: Project's virtual factory framework and applications target at improving the simulation of real factory activities. This has a beneficial impact to the ramp-up phase since production processes and logistics will have been previously virtually evaluated and validated, consequently, ramp-up phase will become shorter in time.
Time to market: The time to market of a new product is highly dependent upon different factors such as product and process design, supplier selections, commissioning and ramp-up. VFF framework and his different modules aims at improving all the factors mentioned above able to reduce the time to market (because of synchronisation and parallelisation of process steps). Furthermore management of complex automation data within the virtual factory will provide further support of New Product Development and thus reducing time to market.
Customer satisfaction and market share: Customer satisfaction has been increased by improving product quality by optimizing the production processes (reducing costs by avoiding rework, speed up the ramp up and increased flexibility and reactivity) and by reducing delivery times through improved management of the suppliers and production network (especially in the case of complex products such as vehicles).
Beside the framework and its advantages, results of the project also a number of software modules and tools able to intervene on specific steps of the production. The tools are listed above and we proved their efficacy using them in the industrial scenarios.
The industrial partners and the technology provider in VFF are recognized key global players and leaders in their respective sectors, as described in the following paragraph. Thus, the Consortium will have a clear cross-national and worldwide character and impact.
List of Websites:
http://www.stiima.cnr.it/siti_progetti/vff/index.html
Mail: info@vff-project.eu
coordinator: marco.sacco@itia.cnr.it
Manufacturing is a dynamic socio-technical system, which is operating in a turbulent environment. Changes are normal and continuous at all levels and the competition is forcing manufacturers to improve the quality, reduce the delivery time and lower the cost. The approach presented in VFF supports the manufacturing enterprises to face these challenges. The project uttermost objective is to foster and strengthen the primacy of Future European Manufacturing by defining the next generation Virtual Factory Framework. The VFF will promote major time and cost savings while increasing performance in the design, management, evaluation and reconfiguration of new or existing facilities, supporting the capability to simulate dynamic complex behaviour over the whole life cycle of Factory, approached as a complex long living Product. Thus the project will research and implement the underlying models and ideas at the foundation of a new conceptual framework designed to implement the next generation Virtual Factory, also meant to lay the basis for future applications in this research area.
VFF is a research project that aims to the Holistic, extensible, scalable and standard Virtual Factory Framework.
VFF promotes major time and cost savings increasing performance in the design, management, evaluation and reconfiguration of new or existing facilities, supporting the capability to simulate dynamic complex behavior over the whole life cycle of Factory, approached as a complex long living Product.
VFF supports the deployment of a next generation Virtual Factory promoting the EU manufacturing competitiveness. It’s based on four pillars which collaboration leads to the realization of the Virtual Factory concepts.
In VFF project (n° 228595, funded by the EC) perspective, the extended enterprise is called Virtual Factory Framework (VFF). It can be defined as “An integrated collaborative platform aimed at facilitating the sharing of resources, manufacturing information and knowledge, while supporting the design and management of all the factory entities, from a single product to networks of companies, along all the phases of the their lifecycles”
The main idea is related to the possibility to realise in parallel to a physical plant also its virtual representation in order to have a place for making all kind of tests before the real plant is completed and, then, without interfering with its operations.
The Virtual Factory (VF) concept has various definitions depending on viewpoints and perspectives, in this paper VF is defined as a VR environment (VRE) that provides, trough the integration of other IT tools, a transparent description and simulations of a real factory to users who could even be separate in time or space by the real entity. In literature such environments are also called Digital Factory or Virtual Manufacturing.
The VF can support the design and management of a production environment by addressing various key issues like:
(a) Reduction of production times and material waste thanks to the analysis of virtual mock-ups,
(b) Development of a knowledge repository where people can find stored information in different versions, with both advisory role and support to the generation of new knowledge,
(c) Improvement of workers efficiency and safety through training and learning on virtual production systems,
(d) Creation of a collaboration network among people concurrently working on the same project in different places.
In order to orchestrate and synchronise the whole amount of data and knowledge produced by the factory applications and to provide them to the VF interoperability platform is needed.
Jointly with introduction of software tools in the Factory the problem of interoperability among various tools is arisen. Several example of framework are available. Since not just the data have to be exchanged by the applications but, where possible, also the knowledge, in the last year the interoperability framework are more and more looking to the potentiality offered by the semantic web technology.
Project Context and Objectives:
Manufacturing has to cope with a more and more complex and evolving market environment: on the one hand the world crisis breaks the balance between demand and production, on the other hand the globalised market pushes for a continuous change. In this context, the ManuFuture technology platform has already proposed some activities to enable the transformation of European Manufacturing Industry into a knowledge based sector capable of competing successfully in the globalized marketplace (ManuFuture 2006). The ManuFuture vision identify the following priorities to reach future competitiveness and sustainability: development of new high-added-value products and services, new business models, new manufacturing engineering, emerging manufacturing science and technologies and transforming R&D and educational infrastructures. Herein the presentation of the new research project titled “Holistic, extensible, scalable and standard Virtual Factory Framework” - VFF (FP7-NMP-2008-3.4-1) highlights its answers to these requirements.
The market proposes new software tools to help the enterprises in facing new market needs (e.g. Siemens PLM solutions and Delmia), but usually only big companies can afford the large investments required by these tools. Therefore, small and medium enterprises (SMEs) are still looking for successful customised and less expensive solutions, which are more suitable for their size and needs.
Innovative methodologies and technologies should influence enterprise strategies, product development and production processes. The Virtual Factory (VF) paradigm, can assist to answer to this need for innovation by addressing several key issues:
• Collaboration among people working on the same project in different places but at the same time.
• Reduction of production times and material waste thanks to the analysis of virtual mock-ups of new products.
• Development of a knowledge repository that is a common place where people can find any kind of stored material (designs or documents) in different versions.
• Creation of a common working place for collaborating in remote situation where members of a network act and operate on various stages of the same production chain.
• Improvement of workers efficiency and safety through training and learning on virtual production systems.
In achieving these objectives new and innovative methods, technologies and tools have to be employed in planning and permanently optimizing the factory operations and its corresponding manufacturing processes. The previous experiences, both from the research and industrial side, result to be not fully efficient because they aim only at partially innovating the factory processes and the integration with the pre-existent ones is difficult. Information Technology infrastructures or new technologies are too expensive for SMEs because of investment and/or management costs. On one hand, there is need for more and more complex production systems with diverging target systems requiring extensive upstream production planning at the highest resolution; on the other hand, the time frame for the planning process is decreasing and existing tools are complex and expensive.
The Virtual Factory consists in an integrated simulation environment that considers the factory as a whole and provides an advanced planning, decision support and validation capability. The Virtual Factory Framework (VFF) implements the framework for an object oriented collaborative virtualised environment, representing a variety of factory activities meant to facilitate the sharing of factory resources, manufacturing information and knowledge. The VFF promotes major time and cost savings while improving collaborative design, management, evaluation and reconfiguration of new or existing facilities. This requires the capability to simulate dynamic complex behavior over the whole life cycle of the Factory that is considered as a complex and long living product. The VFF approach identifies four key research pillars that must be addressed:
I. Reference Model. The Reference Model for factory planning is based on the development of two key concepts: the “factory as a product” and the “non-linear non-deterministic planning methodology”. The Reference Model establishes a coherent standard extensible data-model at the base of the common representation of Factory Objects.
II. VF manager. The VF manager handles the common space of abstract objects representing the Factory. This representation is based on the standard data model.
III. VF modules. The VF modules are the decoupled functional modules that implement the various tools and services for the Factory design, evolution, evaluation, management, etc. They all operate on the same common space of abstract objects.
IV. Knowledge. Knowledge is the engine for the VFF Concept and it has to support the modelling of a wider range of complex systems and provide greater comprehension of modelled the phenomenon.
The collaboration of the four pillars leads to the realization of the Virtual Factory concepts. The Factory Data Model formalises the information generating an overall picture of the factory together with its characteristics, allowing the modelling and handling of data on real-time. The data used for the development of the Data Model is stored in the Knowledge Repository, where it can be further exploited. The VF Manager Core supervises the common space of the framework, ensuring that all pillars, together with their respective components and actors, interact smoothly.
The Virtual Factory, deployed according to the VFF concept, will be permanently synchronised with the Real Factory to achieve time and cost savings in the design, ramp-up, management, evaluation and reconfiguration of the Real Production itself. The Real Factory, interacting in terms of feedbacks and of data needed to set-up and up-date the simulation system, closes the loop. The need of verifying the impact of the VFF approach on the Real Factory asks for the cooperation of industrial partners to define demonstration scenarios that aim at testing and validating the proposed framework. Within the project four demonstration scenarios have been formulated by pairing different factory planning processes and industrial sectors:
1. The first scenario deals with the Factory Design and Optimisation in the machining sector. The VFF tools will be used to design (or re-design) the factory, aiming at higher solution efficiency and effectiveness, and to optimize the configuration of the production systems. This scenario is developed with the cooperation of the industrial partners Compa S.A. and Ficep S.p.A.
2. The second scenario addresses the Factory Ramp-up and Monitoring in the automotive and aerospace sectors.
The VFF tools will enhance the capability to monitor the real factory and improve the set-up activities during the ramp-up phase. Volkswagen Autoeuropa and Alenia Aeronautica S.p.A. are the industrial partner involved in the second scenario.
3. The third scenario faces the Factory Reconfiguration and Logistics in the Automotive and white-goods sectors.
The factory reconfiguration decisions can be supported by simulation and optimization tools, whereas logistics decisions need VFF tools to efficiently face variable demand by means of flexible networked operations. This scenario will be developed with the support of the industrial partners Audi Hungaria Motor Kft. and Frigoglass S.A.I.C.
4. The final scenario called “Next Factory” aims at demonstrating the applicability of the VFF on the entire factory life-cycle. This integrated scenario focuses on the wood-working sectors thanks to the contribution of Homag AG.
Project Results:
The schema in the annex called VFF Framework Brochure shows the architecture of the main result of the project.
Since digital manufacturing technology has become the most important tool for companies to enhance the competitiveness of their products, the Virtual Factory Framework aims at create a standard able to connect different layers of a factory, probably the most effective path to be followed to enhance manufacturing productivity.
Data and Knowledge coming from different industrial domains and processes converge in the shared Data and Knowledge Repository. The common Virtual Factory Data Model assures a comprehensive vision of the information and the possibility to share it with different actors along the factory life-cycle.
The shared Data and Knowledge Repository is governed by the Semantic Virtual Factory Manager (VFM) that provides an open integration platform representing a common and shared communication layer between already existing and newly developed software tools to support the factory design and management. It provides the functionalities of access control, data versioning and selective data query.
The Decoupled Virtual Factory modules are software tools and applications used to support specific activities in the product/process/factory life-cycles. They are listed here below and in pdf in Annex called VFF Modules. These modules are integrated in the framework and can access and modify the shared factory data thanks to the services provided by the VFM.
Finally, the shared data repository can be synchronized with the Real Factory thanks to the Factory Image module, thus closing the loop with the External Data & Knowledge.
Dysfunction Analysis Module – DAM UTCN
This module aims at gathering, filtering, analyzing and elaborating data related to machine failures and repair activities. The main objective of DAM is to support the performance improvement of a production system, in particular during the ramp-up phase.
BENEFITS
• Automated process for failure analysis
• Enable concurrent work
• Integrated failure results accessible by one tool
• Easy and fast chart/report generation, no manual work
• More accurate MTTR, MTBF as well as other production indicators
• Drastically reduced time for the entire analysis process
• Improved production system performance
• Indirectly improve also the future proposal phases
DSM – Decision Support Module LMS, CASP
DSM: Development of a new model supporting the decision making of production line alternatives.
DSM Key functionalities:
• Systematic evaluation of production line alternative configurations employing utility theory
• User Friendly Interface allows the presentation of complex and numerous data in an effective way.
• Integrated with the VF Manager that allows to exchange data with other modules.
Design Synthesis Module – DSM UTCN
The main objective of this module is to improve the Proposal and Design&Development processes and at the same time to facilitate and fasten up the work of the departments involved in these business phases.
BENEFITS
• Avoid using the existing heavy spreadsheet files
• Avoid having so many manual computations
• Parallelization of the work for several departments
• Enable concurrent design, integration with other tools
• Speed up the definition/evaluation of the production resources
• Enable quick reuse of data (other solutions, other projects),
• Easy adjustments of pre-existing proposals
• Shorten the time needed today for proposal phase
EUVEDES – Discrete Event Simulator EUVE
EUVEDES is a module for easy and simple simulation of production sequences in serial production. It is integrated on to the VF Manager, downloading production planning.
New EUVEDES developed key functionalities:
• Calculation and evaluation of KPI: o Production –throughput-
• Energy consumptions –working and idle-
• Taking into account different cycle times per product and per machine
• Taking into account machines MTTR and MTBF.
• Permitting several products in the same machine at the same time
• Connected with PSI FPS production planning
Factory Image FATRONIK, ITIA, UTCN, COMAU
FACTORY IMAGE: VFF-Module that provides real factory data to be used on the factory performance simulations and calculations
FACTORY IMAGE key functionalities:
• Generic Factory data acquisition
• Generic Factory Data Processing scripts independent of the Data source
• Local Storage of Factory Data
• Data feeding to the Virtual Factory Manager
Offered Benefits:
• Factory Performance Measurements are independent of the evolution of the Factory hardware, process characteristics and workload, as they are conceptually managed in the semantic database and then they mapped in real time to the factory reality.
FLP – Factory Layout Planner SUPSI-ICIMSI
The Factory Layout Planner is a multi-client - server application that supports collaborative remote factory layout planning an runs on classic devices (e.g. a PC with mouse and keyboard) as well as on innovative multi-touch devices. FLP is meant to be used in the phase of configuration and reconfiguration of production plants, allowing easy arranging of 3D elements on 3D layouts, simplified guided construction of the 3D model of the building that will host the real production plant, and support to “what if” analysis of the system performances using the embedded discrete events simulation (DES) engine.
FP³ Factory Performance and Process Planning Module
IPA
FP³: New VFF-Module as enhancement and VFF VFM integration of the commercial process planning system „Process Designer“ from Siemens Industry Software.
FP³ - VFM implemented Siemens Process Designer key functionalities:
• Planning and optimization of technical production processes (process times, process plans, process graphs, associated products…).
• Planning and optimization of the production resource structure.
New FP³ developed key functionalities:
• Calculation, visualization and evaluation of:
• Technical performance indicators (capacity, loading, etc.)
• Economical performance indicators (production costs, maintenance or material costs, etc.)
FPS – Production Fine Planning System PSI
FPS is a module for fine planning production sequences in serial production. It is implemented as extension of PSI’s Control Station for Production Fine Planning using the integration to the VF Manager.
New FPS developed key functionalities:
Calculation and evaluation of:
• Integration to VFM-environment
• Calculation of production sequences
• Calculation of technical performance indicators (“cycle time”)
Factory Templates – FT INESC
Scope and Goals
This tool can be seen as an intuitive Knowledge Management system, which allows not only seeking information, consistent with the context in study, but also reusing this information. Moreover, it supports the improvement of the activities that are considered the bottlenecks of the processes and finally stores the changes made in Knowledge Repositories Systems oriented to factory life-cycle structuring, in order to make it available to all workers and partners of the company.
Due to the capability of continuously monitor the behaviour of the factory and project the future performance of the system in study, the Factory Template Framework make it possible to analyse if the factory performance is in the desired direction. If not, it enables managers to understand the reasons why it is not, and the corrective actions that should be done.
Approach
To allow the achievement of this significant advantage, Factory Templates architecture is divided into two main modelling perspectives, static and dynamic. The static perspective enables the application of the “Factory as a Product” paradigm (simultaneous/concurrent engineering). On the other hand, the dynamic perspective has as main advantage the continuous factory life-cycle evaluation. With this component, the Factory Templates make it possible to follow and improve processes, detecting bottlenecks.
Benefits
By the implementation of the PMD, companies become capable of :
• Reduction of Design and implementation times, increasing overall Manufacturing performance;
• Guarantee Concurrent/Simultaneous Engineering in order to improve the Factory and Products processes integration;
• Decision support, regarding processes design, deployment and continuous monitoring and improvement.
GIOVE Virtual Factory
ITIA-CNR
GIOVE Virtual Factory (GIOVE-VF) is a virtual reality collaborative tool to support the design, visualization and exploration of a factory.
Developed by ITIA-CNR onto the C++ library GIOVE (Graphics and Interaction for OpenGL-based Virtual Environments).
Design functionalities
Creation of objects, import of object libraries, placement of objects in the factory (Direct object placement, 3D widget manipulation, Movement constraints, Tape measure tool, Distance editing), Object properties editing, Layout drawing import (DXF 2D), Multi user shared Virtual Environment, Visualization of process plans, Visualization of simulation result
Visualization functionalities
Free navigation, Viewpoints definition, Stereoscopic 3D visualization, Customizable background
Benefits
Delivered for free; simple to use and to install; it can run on a simple notebook as well as in immersive VR systems; it provides a shared virtual environment where users can collaborate on the same activity; it can exchange data with other tools thanks to standard input/output file formats (.xml, .rdf, .owl).
iDecisionSupport – iDS ROPARDO
iDS is a Collaborative Working Environment where team members attend to different types of meetings (work sessions).
It facilitates Decision Making processes for both groups and individuals.
Features
• Reduces the Decision Process’ time
• Remote work (via Internet)
• E-mail notifications for easily tracking the Decision Process
• Synchronous and asynchronous collaboration
• Common framework for Decision Support tools’ integration
• Common language for Decision Support tools information exchange
• Easy to use
IMPACT – Intelligent Manufacturing Planning And Control Tool LMS & CASP
IMPACT: Integration of IMPACT module for supporting short term scheduling of factories.
IMPACT Key functionalities:
• Short Term Scheduling of Manufacturing Systems optimizing time, cost, utilization and quality performance measures.
• User Friendly Interface allowing to model easily and quickly factory resources and configuration, product orders. Schedule’s Gantt chart and key performance indicators are provided.
• Offers a list of dispatching rules (FIFO, LIFO, SPT) for scheduling, while new performance measures to be optimized can be added.
• It has been used in various industrial sectors such as, automotive, shipyards, refineries and food industry.
• Integrated with the VF Manager that allows to exchange data with other modules.
iPORTAL Virtual Factory – ROPARDO
iPORTAL – VF it is a virtual location with a dashboard-like interface integrating different modules and therefore offering the user a central information point.
Features
• Track the status of the projects (integrated with VFM)
• Documents’ management
• Manage the agenda & email
• Track the news and announcements
• Manage the meetings where the user is involved
• Access the external databases (catalogues, standards)
• Easy customization of users’ environment look and feel
• Access to other web tools (third party)
• Efficient and effective management of (structured and unstructured) data
• Knowledge Repository - unstructured info (wiki technology)
• Supports collaborative work
• Single Sign On technology
Interactive Projection System (IPS) CEIT
Interactive Projection System (IPS) represents an integrated concept for intuitive team-oriented factory planning, which enables planners to accelerate and optimize the planning process. It contains tools for layout design and optimization, material flow and transport routes optimization.
Module functionalities
• 3D visualization of buildings, factory equipment, AGV systems and logistic trajectories
• Detailed design and optimization of production layout
• Analyses of material flows
• Check for compliance of safety margins
• Definition of safety margins of the object
• Manual and semi-automatic design of trajectories for AGV systems
• Real-time simulation and testing of AGV systems implementation
Main benefits of the module
• Acceleration and optimization of the planning process (layout planning)
• Layout and material flow optimization
• 3D visualization
• Physics simulation
• Collision detection
The main innovation and the enhancement of IPS with respect to software solutions available on the market is its intuitive user interface for untrained users and the support of team oriented work, what guarantees effective and fast solution of the problem. The modularity of the IPS module ensures its accessibility also for small and medium enterprises. Another significant innovation is using physics simulation in the IPS module. IPS is also focused on real-time simulation and testing of AGV systems implementation; other competitor software does not support this functionality.
KAE - Knowledge Association Engine
LMS & CASP
KAE: New VFF-Development for supporting Knowledge Management for factories.
KAE Key functionalities:
• Capturing, Storage and Retrieval of Knowledge in terms of Past Projects supporting the Design and Planning of Manufacturing Systems
• Past Projects Knowledge concerning Processes, Resources, Products, System’s Configuration and Key Performance Indicators
• Knowledge Capturing employing ontological modeling of the manufacturing systems domain enhanced with “IF-Then” Rules
• Knowledge Retrieval utilizing similarity measurements and inference rules execution. Past Production Lines with characteristics close to the requirements of the new line are identified.
• Implemented as a web based tool with a user friendly interface
• Integrated with the VF Manager that allows to exchange data with other modules and capture Knowledge related to all the factory lifecycle phases.
PAD Process Automation Designer based on HIL TECNALIA
PAD: New VFF-Module based on a Hardware in the loop simulation of the production sequence on a critical machine (Angular transfer machine) presented in the HOMAG production line.
PAD key functionalities:
• Closed loop simulation of the production sequence using the machine and controller dynamics in order to calculate real cycle-times.
• Interaction with the time-GAP between pieces and the velocity of the machine.
New PAD developed key functionalities:
Calculation, visualization and evaluation of technical performance indicators (Cycle time of the Angular Transfer machine) with collision detection. Adaptation of the production sequence time.
Potential failure modes and Effects Analysis – PEA ROPARDO
PEA is a FMEA-driven software tool for the improvement of product engineering quality of any manufactured product.
Features
• Contains catalogs ensuring nomenclature standardization
• Automatically calculates Risk Priority Numbers (RPNs)
• Supports multi-user environments
• Tracks actions’/tasks’ deadlines
• Automatically generates the FMEA form
• Displays the hierarchy of all FMEA structure from the first level (product or process and their functions) down to the lowest levels (recommended actions)
• Enters and views FMEA data in the traditional worksheet format, an intuitive hierarchical tree view, or filtered lists.
• Reuses information from existing analysis by importing FMEA information from Excel, copying/pasting portions of another analysis, or selecting descriptions from existing FMEAs
• Transfers data to other Windows applications such as text editors, spreadsheets, databases, and more
Steel-Projects PLM SPF
Steel-Projects PLM is a software suite designed to control production at a factory level on a production job basis.
Steel construction seldom dealing with standard parts, Steel-Projects PLM is able to import entire CAD files for buildings or bridges and grind them down to elementary parts to fabricate.
Parts are grouped into bars to optimize raw material usage. Then, a second level of optimization occurs for creating work batches that will increase machine tool saturation and overall factory throughput.
Actual factory data are collected to enhance the optimization algorithms.
Being a standard commercial software, Steel Projects PLM is connected to the VF Manager via a connector module that will allow bidirectional transfers of information between the VF repository and its internal database.
The connector modules can retrieve manufacturing system equipments and organisation and write production batches description.
Performance Measurement Dashboard – PMD INESC
Scope
Nowadays, companies have a huge amount of data stored within different sources along the factory. Hence, Performance Measurement Systems (PMSs) have been developed aiming to support decision-makers by gathering, processing and analysing quantified information on performance and presenting it in a succinct format.
Goals
PMD was designed not only to measure the performance of complex manufacturing systems but also to be generic enough to be easily integrated within the production system environment, integrating data from multi-sources in a user-friendly way, interpreting the production system structure, calculating indicators in a dynamic way according to the formula specified and comparing the values obtained with the expected ones.
In order to simplify the KPIs metrics definition, the PMD solution allows the manufacturing system manager to build and store the different KPIs using Drag and Drop functions. With this innovative solution it is possible to quickly analyse the system performance, drill-down problems, detect which are the causes that are negatively affecting the system performance and apply the corrective actions necessary in a more efficient way.
Benefits
By the implementation of the PMD, companies become capable of decreasing:
• Time constraints: the time needed to calculate each indicator and broadcast a performance report by the different stakeholders.
• Effort need: the number of resources needed during the calculation and assessment process
• Learning curve: time needed to train a new performance measurement technician.
Production Simulation module – PS SZTAKI
PS module is based on Java client that is responsible for VFM connection, ontology translation, simulation control
The simulation engine is based on SIEMENS Tecnomatix Plant Simulation running in background. For the ProdSim module the Plant Simulation 10.1 license is required. In the PS module the focus is not on layout but on process analysis, bottleneck identification and optimization of process parameters and execution control
Main benefits
• The simulation models are built and parameterized upon a totally automated way
• Enables off-line analysis in the design phase
• Enables on-line analysis during the operational phase
RDV - Report and Data Visualization SZTAKI
The main functionality is to visualize and report the main KPI-s of a simulation project .
Provide a user friendly interface for the control, initialization and input data provision of the PS module.
The module can be also used in other scenarios as it requires standard input.
In the case of larger amount of data (e.g. time series) the input is provided from data base or txt file
RMP- Requirements Management and KPI Planning ETHZ, NOVA
RMP: New VFF-Module for supporting Requirements Management and KPI Planning for factories.
RMP Key functionalities:
• Acquisition of all function requirements coming from strategic goals, future needs, product specification and sustainability issues in a structured and formalized way from different sources
• Allow refining and improvement of the existing function requirements
• Storage of the functional requirements, their dependencies and the identified KPIs in a formal model to allow data export and different views for supporting exploitation
• Offers integration and connection with the VF Manager and is able to exchange data with it in order to utilize the integration with other modules in the scenarios
• Additionally the fulfillment of the functional requirement can be traced and monitored by mapping/assigning KPIs to it. Therefore KPIs may be newly defines or simply be re-used from a library.
• For each KPI-mapping a target value can be specified and thus represents a performance goal that has to be achieved be the envisioned production system.
Requirements Management Workflow – RMW ROPARDO
Web application which guides the user during the various development phases or during the changes of a project (factory line).
Features
• Speeds up the decisions based on quick vizualization of the status
• Executes workflow definitions (templates)
• Reduces the hardware resources for each member
• Access to the newest version of documents
• Easy to check/track the status of started projects
• Integration with MS Office tools
• Increases collaborative work
• Manages the templates
• Notifications for involved departments
• Authorized access to project information
• Real time status
SIMIO SimX
Main innovative features:
• Full DES with 2D-3D visualisation
• Reusable catalogue of components
• Combined object-oriented and process-oriented modelling capabilities
• Risk-based Planning and Scheduling (RPS) in Experimentation Mode
SVCP - Site and value-added chain planning RWTH – WZL
Functionalities SVCP-Module
• Analysis and evaluation of dynamic production networks and production configurations
• Site and cost optimized distribution of the value added on various resources
Main activities:
o Modeling, simulation and configuration of complex, dynamic production networks
o Consideration of the dynamic development regarding various indicators, e.g. personnel, machine, material, transport costs and lead times
o Simulation-supported evaluation and comparison of dynamic production networks against qualitative criteria (flexibility, delivery reliability, ... ) as well as quantitative criteria (number of resources, costs, manufacturing lead time, initial investment, resource utilization)
WITNESS INTEGRATION LMS & CASP
WITNESS INTEGRATION: Integration of Witness Discrete Event Simulation tool
WITNESS INTEGRATION Key functionalities:
• Integration of a commercial Discrete Event Simulation tool.
• Development of simulation models for commercial refrigerators production facilities and machining work centers.
• Detailed assessment of key performance indicators such as flowtime, production cost, throughput, work in progress.
• Integrated with the VF Manager that allows to exchange data with other modules. Data such as resources and their characteristics, bill of materials, bill of processes.
Potential Impact:
VFF outcomes of the project will have substantial impact on the promotion of strategic targets of the European Economy and Society. These targets regard mainly the competitiveness of European industry, the employment, the environment and the quality of life.
The main output of the project is a fully functional platform, which will be developed upon a completely novel paradigm using the semantic web approach to store the data of the entire Factory in a unique repository with a common data model.
In this economic crisis period the companies that are in danger are mainly the small and medium ones. If the big companies can rely on diversification of investment and consequently possibility of facing difficulties, the SMEs normally cut the innovation amount focusing on the production as it is.
But Factory is a complex system including many different activities. Nowadays each activity along the entire product life cycle inside the factory is handled one by one with different applications each one developed by different ICT company, using his own language and platform for saving data. Information generated by a department must be treated by the following production step and it’s crucial that all the software and tools inside the factory can access to the information.
Despite Interoperability in a factory is essential, it’s still a vision.
The impact on SME is two-fold. On one side, the democratization of the VF will open the access to those tools for manufacturing SMEs, making them benefit from the mentioned advantages. On the other side, the main goal is also to bring new and dynamic KI-SME (Knowledge Intensive SMEs), which are IT solution providers, from “high-tech” to “high-impact”, that also imply a rapid transformation of science results to markets applications
Challenge of the VFF consists in the innovative integration of product, process and factory domains and related data in a unique Data Repository, using a common Data Model. This can empower the productivity of the enterprise lowering the costs for treating the entire cycle.
The use of new technologyes and in particoular Virtual Reality linked with simulation, facilitate the design of a new production line optimizing the row materials flow avoiding possible bottle necks among different machines.
A VIRTUAL representation of the FACTORY can empower the synchronization with the real one. It can promote cost savings in the implementation of new manufacturing sites or reconfiguration of existing ones thanks to the effective virtual representation of building, resource, process, and product.
Impact and avantages of the VFF results are listed below:
Reduction of adaptation and reconfiguration time: The virtual factory framework will provide consistency over the planning and design process by providing a mutually accessible “information market place” for results and assumptions of all planning objects, synchronizing both services and virtual model via a generic modelling language. This information market place will overcome the isolation of the individual planning tasks and simulation tools, reducing adaption and reconfiguration time.
Reduction of ramp-up phase: Project's virtual factory framework and applications target at improving the simulation of real factory activities. This has a beneficial impact to the ramp-up phase since production processes and logistics will have been previously virtually evaluated and validated, consequently, ramp-up phase will become shorter in time.
Time to market: The time to market of a new product is highly dependent upon different factors such as product and process design, supplier selections, commissioning and ramp-up. VFF framework and his different modules aims at improving all the factors mentioned above able to reduce the time to market (because of synchronisation and parallelisation of process steps). Furthermore management of complex automation data within the virtual factory will provide further support of New Product Development and thus reducing time to market.
Customer satisfaction and market share: Customer satisfaction has been increased by improving product quality by optimizing the production processes (reducing costs by avoiding rework, speed up the ramp up and increased flexibility and reactivity) and by reducing delivery times through improved management of the suppliers and production network (especially in the case of complex products such as vehicles).
Beside the framework and its advantages, results of the project also a number of software modules and tools able to intervene on specific steps of the production. The tools are listed above and we proved their efficacy using them in the industrial scenarios.
The industrial partners and the technology provider in VFF are recognized key global players and leaders in their respective sectors, as described in the following paragraph. Thus, the Consortium will have a clear cross-national and worldwide character and impact.
List of Websites:
http://www.stiima.cnr.it/siti_progetti/vff/index.html
Mail: info@vff-project.eu
coordinator: marco.sacco@itia.cnr.it
