Skip to main content

Cooperation Environment For Rapid Design prototyping and New Integration Concepts for Factory of the Future

Final Report Summary - COPERNICO (Cooperation Environment For Rapid Design prototyping and New Integration Concepts for Factory of the Future)

Executive Summary:
In COPERNICO, a novel approach was adopted which looked at all factors of the production system in a holistic manner (machines, humans, environment) and modelled the interactions. We believe that it is only possible to design a virtual manufacturing process by developing a detailed understanding of the system at all levels. COPERNICO was directed at generic issues spanning the interests of all our industrial partners and indeed common to all factories. The problems include optimizing capacity, removing bottlenecks and scheduling. The preplanning stage is an ideal time in the life-cycle of the plant to include human and environmental concerns, safety factors and work-place satisfaction metrics. There were five technical work streams, and one each for demonstration, dissemination and project management. The first technical stream developed a classification system based on ‘cladistics’ which itself is based on evolutionary relationships. Cladistics places emphasis on objective, quantitative analysis and can be used to generate cladograms that represent the evolutionary tree of life. To develop the cladograms it was necessary to identify a range of characteristics, which can be used to describe a company. These included technologies (processes) used, systems used (cells, flow layout, batch, one off), and the type of management systems used. Five hundred manufacturing systems from across the EU were studied.
The challenge of introducing modelling tools to SMEs was a major part of making the COPERNICO system applicable to European companies. COPERNICO identified the relevant and leading commercially off-the-shelf (COTS) modelling tools that are currently available, determined their capability with respect to COPERNICO requirements, and evaluated them for use with the families of manufacturing organisations in the cladogram. The main result of this is the Modelling Tools Recommendation Tool (MTRT), which comprises: i) the Modelling Tool Explorer to visualise the relevant tools linked to the cladogram; ii) the Factory Recipe Tool, which provides detailed information on which COPERNICO tools to use.
The aim of the COPERNICO system was to have an integrated software environment for modelling and virtual prototyping. This was guided by the following objectives: i) Development of lightweight tools as a backbone for SME virtual factory design; ii) Interface with existing factory planning tools; iii) Have a common decision making framework across whole virtual factory development process; and, iv) Multi-vendor engineering tool deployment into the logic sequence of the COPERNICO toolbox (best for a purpose tools). The following key technologies were applied: i) Use of semantic models and architecture; ii) Interface with the advisor system to streamline the development process by using predefined process and factory layouts; and iii) Development of a set of lightweight distributed tools. Models and methods were also developed to enable the convergence of meaning across the whole virtual factory development cycle. This was achieved through a common high-level language, which acted as the communication backbone between the tools in the COPERNICO toolbox and the external expert tools for more detailed analysis. User requirements were linked to the cladogram. This was associated with process maps and resource requirements, which established a clear set of factory requirements for the configuration of appropriate solutions, i.e. a high level integrated Product-Process-Equipment Ontology.
The web-based diagnostic tool guides the interaction of end-users with relevant parts of the COPERNICO software system. The web-based access to the COPERNICO world informs and attracts end users to interact with the methods and people behind COPERNICO. The system is aimed at people currently: i) Facing problems in the domain of factory planning or operation; ii) Planning to work in this field; iii) Wanting to get a broad overview about tools available in this area; and/or, iv) Looking for consultancy in a certain topic.
The COPERNICO system and toolbox have been demonstrated, evaluated and disseminated using three industrial studies (showcases). The full showcase studies were carried out in two SMEs, Footprint Sheffield and Temco, and one large company, Electrolux, in order to demonstrate the application of techniques for a range of companies. The results were very promising. Temco moved production for six parts from the Far East back to Europe to reduce costs and improve efficiency. Footprint gained 500 productive hours a year which they can use to introduce new products and Electrolux have introduced discrete event simulation in other areas of their factory as a result of the increase throughput and reduced part travel times.

Project Context and Objectives:
The manufacturing industry currently accounts for a quarter of the European economy and employs 45 million people. The European manufacturing industries account for approximately 20% of total employment and a turnover of €4,600 billion. In addition to direct employment, with many highly qualified jobs, manufacturing industry supports jobs throughout the supply chain and generates growth in the service sector. European manufacturing is under continued threat from the East. Although generally termed low wage economies this gives a false indication of the threat. Although the East does have low-cost labour economies it also has highly automated factories and there is considerable investment in new capital equipment. To maintain the current level of manufacturing in Europe it will be necessary to focus on high value, low volume products. This will require highly flexible and easily modified manufacturing systems and facilities. Factory layout and supporting systems will need to be optimized quickly as production runs will be shorter and there will not be time to optimize as the facilities are commissioned.
The main objective of COPERNICO (www.copernico.co) was to create a virtual factory populated with integrated models of organisations, processes and systems. This should be made available to companies through a web-based portal and be applicable to the majority of European manufacturing organisations through the use of a novel classification system. The challenge of COPERNICO was to reduce the initial trial production stage and move to full manufacturing capacity as quickly as possible. Thus, COPERNICO had the following set of high-level objectives:
1) Develop integrated models of organisations, processes and systems in a virtual environment;
2) Develop a classification system that encapsulates and represents all manufacturing organisations in the EU, including SMEs, and enables them to be described using a limited number of modules, which can be linked to provide a realistic model of all aspects of the organisation;
3) Make systems tools and techniques available for short periods of time at acceptable cost using web-enabled access.
These three headline objectives were redefined in-terms of SMART objectives (Specific, Measurable, Achievable, Relevant and Time related):
1) Develop a modelling tool capable of developing integrated virtual models of manufacturing organisations, applicable to all types of manufacturing organisations, and demonstrate in one research facility and two case study organisations (two SMEs and one large company) by month 48;
2) Develop a new classification system capable of describing the organisation including market, systems and processes applicable to all manufacturing organisations and demonstrate in one research facility and two case study organisations (two SME and one large company);
3) Develop a web-enabled system to use the classification system and integrated virtual modelling tool and demonstrate in one case study organisation (SME).
To achieve these COPERNICO:
1) Identified and merged a range of mathematical, physical, data driven and knowledge based models with soft data such as worker and environmental considerations to create hybrid forms and create a tool to predict the behaviour of production processes and overall factory environments;
2) Utilised where possible existing and applicable modelling tools;
3) Enhanced existing modelling tools or developed new ones;
4) Used the models to develop optimum processing routes;
5) Developed novel experimental methodologies to validate the models in a research facility;
6) Built upwards from tools to machine tools to cells and factories in a virtual environment to validate the optimum production process using case studies and producing an integrated modular system;
7) Provided the decision maker with the modelling tools required to evaluate options and make the correct management decisions.
A number of research indicators were identified to quantify progress beyond ‘the state of the art’:
1) A classification system based on cladistics that enables manufacturing SMEs to be categorised in relation to their state and modelling requirements.
2) A set of virtual modelling tools which interface with a number of existing systems and mediums.
3) The ability for users to interact through virtual reality.
Virtual reality systems are categorized as one of three main types: non-immersive (desktop), semi-immersive (projection systems) and fully immersive. There are a vast number of virtual reality modelling systems on the market, which can be used to develop VR sub system models or to model a specific item of equipment (robot). Commercial systems are available which allow the positioning of various machines on a factory floor, but these systems are still not integrated with VR. Designing the factory layout in VR would enable the engineer to walk through the facility (either in the virtual facility or through augmented reality operations) and improve/debug plans before implementation. The advanced VR environments would enable people to mimic the motions of the production staff and evaluate the layout for ergonomics, reach, access, safety, etc. The VR system will model complete cells and plants and will include:
Process planning in customized manufacturing: this is made more complex by the need for the system to respond to changes in customer requirements. Process plans need to respond to these changes and can be simulated using VR software. The capability of a VR system to model and simulate at different levels of detail allows management to assess process plans, assembly sequences, operation sequences and time and motion studies.
Operational aspects including loading and unloading work pieces, machine operation, CNC program execution, and other operations: these can be verified and viewed before the machining instructions are initiated. Machining time and operation studies can be performed, allowing detailed assessment of tools for wear and optimum tool selection
Control of manufacturing facilities including running and operating a customized manufacturing facility: this is a complex task due to the very large number of parameters involved. As tasks change frequently, operators are unable to learn or be trained to carry out tasks routinely. VR can help significantly in operation and maintenance of customized facilities. Using VR, the operating staff can receive on-line and off-line training and real-time instructions, and can be guided through new tasks.
Tele-presence: Using VR technology and tele-presence, experts can be used to assist staff to carry out tasks. This could be particularly useful for assembly operations where (for example) aero-engines may be disassembled in repair and maintenance facilities with expert assistance from the OEM.
Tele-operation: Tele-presence can be extended to tele-operation, when the system is not only observed, but controlled from the remote location.
Man-machine interaction: In highly automated systems humans and robots are not allowed in the same location. Using VR it will be possible to operate robots and automated systems from remote and safe locations. This can be achieved by linking the virtual factory to the real factory using sensors and controls.
In other areas VR is not the appropriate medium and either a computer based or web based diagnostic tool will be used. This is particularly relevant to decision support tools and the use of the classification system.
The approach adopted was to integrate knowledge and techniques from different engineering disciplines and merge experimental and modelling work to create a better understanding of the production process. We used hybrid modelling to fuse physical models and tacit knowledge to form integrated models capable of accurately predicting and interpolating the physical and data driven models. To fully encompass the whole factory, six distinct themes were modelled, simulated and validated, before being linked in the over-arching modular software system. The system developed followed the three sub-system model of a manufacturing facility:
The physical sub-system: This comprises the resources and processes. Many of the tools required for modelling at the physical system level were already available but not integrated. These tools include process modellers, plant simulations, etc.
The information sub-system: This provides the information on which decisions are made. There are already a large number of information modelling tools available such as SSDS, GRAI, etc., and these needed to be integrated with the physical modelling tools to provide the relevant information to the decision makers.
The decision sub-system: This is the position within the hierarchy of the organisation where decisions are made. It was important and relevant to differentiate between a decision and an activity. If information is collated and an outcome results automatically (i.e. a reorder level is reached and a reorder quantity is ordered) this is an activity. A decision only occurs when the decision maker has discretion.
Modelling tools are only relevant to decisions as they assist the decision maker to evaluate the options and use discretion to make the correct decisions. COPERNICO had 8 work packages:
WP1: Definition of organisation: the aim of this WP was to develop the organisation classification system up to the point where it can be used to classify and position an organisation relative to other organisations in its sector.
WP2: Identify modelling tools: the aim of this WP was to identify all the relevant tools available and determine their capability with respect to the needs of COPERNICO. This was achieved with reference to the cladograms developed in WP1 and the industrial need identified. Where possible the needs of SMEs were considered and low cost options were adopted.
WP3: Produce new software: where existing software cannot be adopted or modified new software modelling tools were specified and developed.
WP4: Build virtual environment: the work carried out in WPs 1, 2 and 3 was done in the physical environment. The aim of COPERNICO was to transfer this to the virtual environment. This was achieved in WP4.
WP5: Web based diagnostic tool: this WP was closely related to WP4 but translated to a web-based version that will provide short-term access to SMEs.
WP6: Case study evaluation: In this WP, the integrated modelling tools and the web based tools were evaluated in industrial case studies. The initial evaluation was carried out in a laboratory environment but was extended to include both SMEs and large organisations.
WP7: Project management: A complete WP was dedicated to project management. This included the day-to-day operation of the project through to management and reporting.
WP8: Dissemination and training: this WP covered activities such as publications and seminars, workshops and the public website.
The main beneficiaries of this research project were the COPERNICO industrial partners who had the ability to make modifications and reduce the amount of validation and certification required, the ability to develop new production procedures for new components quickly, to ramp up production so as to maximize market share and return on investment and the ability to modify existing machining processes without expensive revalidation and certification. Other companies in the supply chain also benefited through direct involvement with the knowledge partners or through the use of production process guides produced.

Project Results:
Rolls-Royce Case Study
Rolls-Royce used COPERNICO to help plan a new factory by combining different kinds of simulation to create an evolving virtual model. When manufacturing large, complex part, moving these around the factory can take up to a fifth of the manufacturing lead-time. The size of the parts means that they present significant health and safety risks, and often other work has to stop while they're being lifted and moved. These movements can be modelled using discrete event simulation (DES), but the results can be hard to interpret. Rolls-Royce used COPERNICO to combine the DES data with a virtual model of the factory in a fully immersive environment which evolves over time (see Figure 22). Assembly sequences were modelled for each component part, then combined to form a model of the complete factory cycle over many months. The complete simulation can be displayed using Visionary Render.


Figure 22: Visualisation of a DES model

Potential Impact:
Exploitable results
An initial exploitation strategy seminar was conducted early on in the COPERNICO project. During the exploitation strategy seminar, project consortium members learnt about the importance of exploitation, consideration of intellectual property rights (IPR) and risk identification and mitigation/management. All partners found the initial seminar particularly useful and a list of potentially exploitable results were developed and discussed. Since this initial meeting, partners have held regular exploitation strategy seminars to refresh partner knowledge on IPR and risk management as well as revising and discussing developments with exploitable results. In particular, the subsequent exploitation strategy seminars have dedicated a large proportion of time to the discussion of partner input of background, foreground, use of results as well as making or licensing the results. Further discussion of potential risks were also outlined with a focus on any new risks that may have been recently identified. Regular discussions of IPR and potential risks ensured that the project consortium remained engaged with the exploitation process and any potential areas of conflict (particularly surrounding IPR) could be discussed as they occurred in a neutral environment face-to-face. These discussions were particularly fruitful and pertinent due to the large amount of collaboration across partners in developing the exploitable results. With many partners providing background and foreground knowledge in the development of the results, there were a lot of IPR discussions and scenarios that needed to be discussed and agreed.
After the initial exploitation strategy seminar a plan for the use and dissemination of the foreground (PUDF) was developed. This document reported the list of exploitable results, including partner contributions and the potential impact of each result. Considering partner contributions to each potentially exploitable result, allowed the consortium to discuss and document intellectual property rights. A risk matrix was also developed to enable project partners to consider potentially high-risk elements that needed to be noted and discussed further. The PUDF developed at this early stage was considered a working document. At each quarterly project meeting this document was discussed as part of an exploitation strategy seminar refresher. Following each meeting, the PUDF was updated to include any revisions and amendments that arose during the meeting discussions. A final version of the PUDF was developed at the end of the project. The following tables outline key dissemination activities that have been conducted during the COPERNICO project. Furthermore, a list of key exploitable results is outlined in section B. More information concerning each result and its potential impact can be found in the final PUDF.

No Exploitable Results Rapporteur
1 Lightweight distributable stereo 3D viewer VIRT
2 Development of Requirements engineering based resource selection. Factory resource planning based on key requirement characteristics, results from layout design modules and simulation analysis, and supported by deployment planning. UNOTT
3 Improved human modelling for ergonomic analyses of immersed Visionary Render users (previously Ergonomics Module). VIRT
4 Common Interface with existing factory planning tools – for SMEs, web-based interface for factory planning tools (plant simulation, visual components), middleware is ESB GAMAX
5 Cladistics-based high level product process system ontology for factory design – tool/language to support cladistics methodology to support decision-making in factory design. Manufacturing expert system. UNOTT
6 Value added application of discrete event tools for SMEs – linked to previous result, but could be exploited on its own. RRUK
7 Integrated 2D and 3D layout design methods and software tools – the 3D layout configurators for automatic creation and evaluation of 3D layout models (not Web-based), lightweight/heavyweight, and linked to DES, to component library, to cladistics; Web-based 2D conveyor configurator. BME
8 Factory components library. BME
9 Software modules for result presentation of customers’ investigations based on interactive web technology. Giving multiple “non-experts” access to results via standard browsers simultaneously. Technology for web based sharing of COTS for establishment of new business models. FIPA
10 Interactive, web-based training material – distance learning, focused on industry, embedded in MSc / BSc courses, offered in Open University Mode for professionals (creates market opportunity). TEKS
11 Parametric modeling of DES tools for a flexible configuration of manufacturing cells and lines DIMI-UNIBS
12 LDA (Life Data Analysis), R&M (reliability and maintainability) and LCC (Life Cycle Cost) virtual modeling integration - A working environment / methodology customized for maintainability and reliability of machineries CESI
13 Petrinet tool TEKS
14 JT translater to Visionary Render VIRT
15 Diagnostics tool (cladistics and modelling tools recommendation tool) USFD
16 Android Cladistics/Diagnostics Mobile Application USFD
17 Off line integrated DES modelling methods, software tools for the creation and optimisation of DES models (not Web-based), heavyweight, linked to 3D layout design tools, to component library, to cladistics. BME
18 COPERNICO scale models for the layout of factories FPTSHEF
Journal publications and conference proceedings

Aggogeri F. Borboni A. Faglia R. Mazzola M. (2013). A novel logic and approach to speed up simulation and analysis of production systems. Journal of Convergence Information Technology 8, (3), pp. 702-710.

Haraszkó, C, Németh I. (2012). Automatic Creation of Simulation Models of Manufacturing System Layout Variants (in Hungarian). Bitay (ed.), Fiatal Műszakiak Tudományos Ülésszaka XVII. Kolozsvár, (Erdélyi Múzeum-Egyesület), 155-158.

Baldwin, J, Rose-Andersson C and Ridgway K. (2011). Linnaean and Cladistic Classifications of Manufacturing Systems. 4th International Conference on Changeable, Agile, Reconfigurable and Virtual Production, 2-5th October; published in Enabling Manufacturing Competitiveness and Economic Sustainability, pp.29-33.

Rose-Andersson, C, Baldwin J and Ridgway K. (2011). Cladistic Classification of Ancient Manufacturing Forms and Technologies. 4th International Conference on Changeable, Agile, Reconfigurable and Virtual Production, 2-5th October; published in Enabling Manufacturing Competitiveness and Economic Sustainability, pp.551-536.

Németh, I, Püspöki J. (2012). Development of a Manufacturing System 3D Layout Configurator. Paper presented at the 8th International Conference on Mechanical Engineering, 24-25th May, Budapest Hungary.

Baldwin, J, Rose-Andersson C and Ridgway K. (2012). Evolving Manufacturing Systems: Hierarchical and Cladistic Classifications. Paper presented at the European Academy of Management (EURAM), 6-8th June, Rotterdam, Netherlands.

Rose-Andersson, C, Baldwin J and Ridgway K. (2012). The Evolution of Manufacturing Man and his Manufacturing Species. Paper presented at the European Academy of Management (EURAM), 6-8th June, Rotterdam, Netherlands.

Rose-Andersson, C, Baldwin J, Ridgway K, Bottinger F, Kodua K, Brencsics I & Nemeth I. (2012). Methodologies for Practical Applications of Unified Linnaean and Cladistic Classifications of Production Systems. Paper presented at the 6th International Conference on Operations and Supply Chain Management (ICOSCM), 14-18 July, Xi'an, China.

Reddish S, Freeman C. (2012). Discrete Event Simulation using Immersive Virtual Reality for Factory Simulation, Joint Virtual Reality Conference, 17-19th October, Madrid, Spain.

Rose-Andersson, C, Baldwin J and Ridgway K. (2012). Hierarchical and cladistic classification for the improvement of manufacturing systems. Paper presented at the 15th Annual Conference of the Irish Academy of Management, 5-7th September, Limerick, Ireland.

Hughes, RWC, Scott R and Ridgway K. (2012). Challenges of using Discrete Event Simulation for facility planning in SMEs: A Case Study. Paper presented at the European Simulation and Modelling Conference, 22-24th October, Essen, Germany.

Nemeth, I, Puspoki J, Rose-Andersson C, Baldwin J, Haraszko C & Ridgway K. (2012). Cladistic classification and rapid layout design of manufacturing systems. Paper presented at the International Conference on Manufacturing Research, 11-13th September, Aston, UK.

Baldwin, J, Ridgway K, Nemeth I, Rose-Andersson C, Boettinger B & Brencsics. (2012). Applying Classifications to Measure and Achieve Manufacturing System Fitness, Performance and Best Practice. Paper presented at the International Conference on Manufacturing Research, 11-13th September, Aston, UK.

Rose-Andersson, C, Baldwin J, Ridgway K, Boettinger F, Agyapong-Kodua K, Brencsics I, Nemeth I. (2012). Application of Production System Classifications in Rapid Design and Virtual Prototyping. Paper presented at the 14th International Conference on Modern Information Technology in the Innovation Processes of the Industrial Enterprises (MITIP), 24-26th October, Budapest, Hungary.

Haraszkó, C, Németh, I. (2012). Software development for automatic creation of discrete event simulation models of manufacturing system layout variants, Proceedings of the PhD Workshop – organized by the Doctoral School on Computer Science and Information Technologies in the framework of TÁMOP-4.2.2/B-10/1-2010-0009 Budapest, Hungary

Németh I, Püspöki J, Haraszkó C, Baldwin J. (2012). Rapid Layout Design of Manufacturing Systems, 14th International Conference on Modern Information Technology in the Innovation Processes of Industrial Enterprises (MITIP), 24-26 October, Budapest, Hungary

Aggogeri F, Maneia G, Merlo A, Mazzola M. (2012). Adding adaptability to Discrete Event Simulation through parameterisation. Paper presented at the 25th European Conference on Operational Research (EURO 2012), 8-11th July, Vilnius, Lithuania.

Baldwin, J, Rose-Andersson C, Ridgway K, Boettinger F, Michen M, Agyapong-Kodua K, Brencsics I, Nemeth I & Krain R. (2013). The evolution of manufacturing species -
a cladistic analysis and its application. Paper presented at the 46th CIRP Conference on Manufacturing Systems, 29-31st May, Sesimbra, Portugal.

Haraszko, C, Nemeth I, Agyapong-Kodua K & Baldwin J. (2013). DES Configurators and Ontologies for Rapid Virtual Prototyping of Manufacturing Systems. Paper presented at the 46th CIRP Conference on Manufacturing Systems, 29-31st May, Sesimbra, Portugal.

Nemeth, I, Puposki J, Matyasi G, Nagy T, Freemen C, Scott R & Baldwin J. (2013). 3D Design Support for Rapid Virtual Prototyping of Manufacturing Systems. Paper presented at the 46th CIRP Conference on Manufacturing Systems, 29-31st May, Sesimbra, Portugal.

Baldwin J. (2013). Hierarchical and Cladistic Classifications of Manufacturing Systems: A Basis for Applying Generalised Darwinism? Paper presented at the European Academy of Management (EURAM), 26-29th June, Istanbul, Turkey.

F. Aggogeri, G. Maneia, M. Mazzola, A. Merlo, N. Pellegrini, N. Venturi. (2013). An integrated approach in modeling and simulating production and transactional systems. Paper presented at the 26th European Conference on Operational Research, 1-4th July, Rome, Italy.

Haraszko CS, Nemeth I & Baldwin JS. (2013). DES configurators for Rapid Prototyping of Manufacturing Systems. Paper presented at the International Conference on Innovative Technologies, IN-TECH 2013, 10-12th September, Budapest, Hungary.

Mazzola, M, Aggogeri, F, Automating the simulation of SMEs processes through a discrete event parametric model, International Journal of Engineering Business Management (under review).

Agyapong-Kodua K, Haraszkó C, & Németh I. (2014). Resource selection ontologies in support of a recipe-based factory design methodology. International Journal of Production Research (In press and available on-line).


List of Websites:
www.copernico.co