- Email: [email protected]
A PLATFORM PROVIDING INFORMATION PROVISION IN ENGINEERING
7th IFAC Conference on Manufacturing Modelling, Management, and Control International Federation of Automatic Control June 19-21, 2013. Saint Petersburg, Russia
978-3-902823-35-9/2013 © IFAC
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10.3182/20130619-3-RU-3018.00525
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
Kerr et al. (2006), and Lacy (2005). For this reason, not only the “document”, i.e. the ontology, is beneficial as an up-todate type of a project glossary but its joint formulation based on discussions and cooperation by the involved parties. The benefit of ontology-based approaches to advance the common understanding in the context of engineering-related activities has been researched in relation to requirements by Kerr et al. (2006) and to manufacturing by Lin et al. (2004), showing its appropriateness for the support of the co-operation of engineers along the processes for product and production engineering, resulting in lower efforts and shorter time-tomarkets for new products by enhanced communication. The second essential reason for the ontology-based approach of the platform, besides its usefulness as common vocabulary to support a documented understanding, is its benefit for systems integration, i.e. to realise an integrated but open system. For this purpose, the platform builds on work as the ontology-based approaches for the support of data and information integration by Wache et al. (2001), for enterprise integration by Izza et al. (2005), for interoperability in the manufacturing area by Knutilla et al. (1998), and the comprehensive engineering-related work by Spath and Lentes (2009). In addition, the standard-related work concerning enterprise-control system integration is considered by Chen (2005), amongst others. To support systems integration, i.e. the continuous flow of data and information from one software system or module to another, the ontology realises a semantic data model with concepts, relation, and their respective attributes. The ontology is formulated in the quasistandard notation OWL (Web Ontology Language, cf. McGuinness and van Harmelen (2004)), enabling the usage of existing tools and libraries to work with the ontology as well as to implement interfaces for reading and writing data and operating on it. See the work of McBride (2002) for an example programming library. The application of an ontology as semantic data model enables the derivation of specific concepts of the application domain of a knowledge-based system from generic concepts that are independent of the domain and supports the reuse of the implemented problem solving methods. Although work concerning ontologies and problem solving methods is done since more than a dozen years, for an example please refer to Goméz Pérez and Benjamins (1999), not much work has been done to implement this promising approach to the engineering domain. Spath et al. (2005) introduced the ontology-based usage of domain-neutral problem solving methods in the specific context of production systems planning. E.g. the modelling of a production system as directed graph with the system element as nodes and material flow as edges enables the application of generic analysis methods from graph theory on the production system without further adaption. Eckstein (2010) presented the EC-funded project SWOP addressing the application of ontologies and problem solving methods to develop optimized combinations for products and production systems, even when these come from different suppliers, in order to obtain individual solutions to customer-specific problems.
An essential advantage of the application of ontologies in product development is knowledge sharing. Bradfield and Gao (2007) determined three main problem categories for knowledge sharing in the new product development (NPD) process of a manufacturing company: inappropriate information about the knowledge in the NPD process, multilingualism as well as multidisciplinarity, and insufficient information provision to users. By means of an ontology-based approach, knowledge sharing in NPD may be facilitated. Lutters et al. (2000) work to apply information management based on an ontological approach on design and engineering processes under special consideration of manufacturing, i.e. process planning and cost estimation. Young et al. (2007) show the benefits of applying ontologies to support knowledge sharing in PLM with a focus on manufacturing processes. By using a product ontology as pivotal element, Panetto et al (2012) introduce an approach to support interoperability in Product Data Management (PDM). Matsokis and Kiritsis (2010) developed an ontology of concepts and rules to support PLM, emphasizing the product and its role in closed-loop PLM. This shows advantages of the application of ontologies for PLM like automatically (rule-based) handling of multiple data from multiple physical products and of concept equivalencies-inconsistencies, supporting system interoperability and data integration. Slimani et al. (2006) presented an approach to support conflict management in collaborative design by means of an ontology-based approach. To summarize, a comprehensive approach leveraging the usage of an ontology as joint vocabulary, as integrative semantic data model and to implement information provision and the application of neutral problem-solving methods for the integrated development of products and production systems could not be identified in scientific work nor as commercially available software system, but partial solutions exist. 4. SOLUTION APPROACH 4.1 Principal Architecture To tackle the resulting challenges for engineering in manufacturing companies the platform is, as motivated in chapter 3, based on an ontology that serves as an interoperable model and integrating element for an open engineering system (the Platform). Second main element of overall solution are methods implemented as modules to realize tools to assist in product and process development, analysis, virtual testing, and optimization based on heuristic methods and simulation that operate on knowledge represented by information, which is structured by means of an ontology. The usage of an ontology-based approach enables the application of domain-neutral problem solving methods to specific engineering activities. Third building block of the solution is an open engineering platform laid on existing tools and libraries, specifically on Open Source Software systems. The resulting principal architecture of the overall solution is briefly shown in Fig. 2.
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
inter- or intranets. Along the entities in the ontology, a semantic search will be constructed and federated over distributed sources.
and PLM), funded by the European Commission as part of the “Factories-of-the-Future” Programme, contract number 285171.
After first approaches using existing open source and commercial tools like Protégé, Semantic MediaWiki and OntoStudio/OntoBroker, currently a second version completely based on open source technology is developed, based on the framework for building Semantic Web applications Jena (Jena, 2012). To support the presentation of the potential and benefits of the approach, a simple frontend has been developed, which enables the unobtrusive information provision while editing text documents in Microsoft® Word, e.g. during the definition of product requirements.
The consortium of the project consists in alphabetical order of Aerogen Ltd, Association pour la Recherche et le Developpement des Methodes et Processus Industriels, Fraunhofer IAO, Intel Performance Learning Solutions Limited, MBtech Group GmbH & Co KGaA, Ontoprise GmbH, Politecnico di Torino, R.T.T., Shannon Coiled Springs Limited, Universita degli Studi di Trieste, Universität Stuttgart, University of Limerick, University of Nottingham.
6. CONCLUSIONS In this paper, an integrative open platform supporting engineers in the integrated development of products and the related production systems has been presented. Besides the neutral software platform itself, essential elements of the overall solution are modules representing methods as well as interfaces to software systems that have already existed in industrial companies, and engineering models. This is a set of ontologies as semantic data model and documented common vocabulary facilitating communication among humans and software systems. Main advantages to be leveraged by the solution presented are reduced times to search data and information during engineering activities, support by means of problem solving methods, capturing and re-use of knowledge and experience as well as integrated access to information distributed in different software systems by the interoperability aspect of the solution. Focus of the paper is the semantic backend as an essential part of the platform. The semantic backend acts as “long-term memory” of the solution. Moreover, the backend enables the retrieval of information from external sources as the file system, databases, or legacy systems. The development of first prototypes has been done in two steps. At first, the base for the development was commercial available technology. To push the usage and advancement of the developed solution prevent a vendor lock-in with the according risks, emphasis has been put on open source software, resulting in the current usage of Jena as essential base technology for the semantic backend. Further work concerning the backend will concentrate on the implementation of software agents to support semantic information retrieval in the file system, intranet and extranet as well as interfacing towards databases and legacy systems in the real-world pilot cases. In addition, the solution that is prototypically developed will be advanced to a system that is scalable and robust enough to be applied in daily work of practitioners in real industrial settings. ACKNOWLEDGEMENT The work presented in this paper is part of the project amePLM (advanced Platform for manufacturing engineering
REFERENCES Bradfield, D. J., Gao J. X. (2007): A methodology to facilitate knowledge sharing in the new product development process. International Journal of Production Research 45 (7), 1489–1504. Chen, D. (2005). Enterprise-control system integration—an international standard. International Journal of Production Research 43 (20), 4335–4357. Eckstein, H. (2010). Self-Optimized, Individual Product and Production Solutions. Product Data Journal, 17 (1), 5458. Goméz Pérez, A., Benjamins, V.R. (1999). Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem Solving Methods. In Proceedings of the IJCAI-99 workshop on Ontologies and Problem Solving Methods, 1.1-1.15. Stockholm, Sweden. Gruber, T. (1993). A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5 (2), 199-220. Izza, S.; Vincent, L.; Burlat, P. (2005). A Unified Framework for Enterprise Integration: An Ontology-Driven ServiceOriented Approach. In Proceedings of Interop-ESA ’05. Geneva, Switzerland. Jasper, R., Uschold, M. (1999). A Framework for Understanding and Classifying Ontology Applications. In Twelfth Workshop on Knowledge Acquisition Modeling and Management KAW'99. Banff, Alberta, Canada. JADE (2012) JADE (Java Agent DEvelopment Framework. WWW-Page: (22nd November 2012): http:// http://jade.tilab.com. Jena (2012) Apache Jena: WWW-Page. (24th November 2012): http://jena.apache.org.JESS (2012). Jess, the Rule Engine for the Java Platform: WWW-Page. (24th November 2012): http://herzberg.ca.sandia.gov. Kerr, C. I. V., Roy, R. and Sackett, P. J. (2006). Requirements management: an enabler for concurrent e automotive industry. International Journal of Production Research, 44 (9), 1703-1717. Knutilla, A.; Schlenoff, C.; Ivester, R. (1998). A Robust Ontology for Manufacturing Systems Integration. In Proceedings of the Second International Conference on Engineering Design and Automation. Maui, Hawaii, USA. Lacy, L. (2005). OWL: representing information using the web ontology language. Trafford , Victoria, B.C., USA.
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
Light, J., and Miller, J. D. (2002). Miramar: a 3D Workplace. In Proceedings of the IEEE Professional Communication Conference 2002, 271-282. Portland, Oregon, USA. Lin, H. -K., Harding, J. A. and Shahbaz, M.(2004) Manufacturing system engineering ontology for semantic interoperability across extended project teams, International Journal of Production Research, 42 (24), 5099-5118. Lutters, E., Brinke, E. T., Streppel, T., Kals, H. (2000). Information management and design & engineering processes. International Journal of Production Research, 38 (17), 4429-4444. Matsokis, A.; Kiritsis, D. (2010). An ontology-based approach for Product Lifecycle Management. Computers in Industry, 61 (8), 787-797. McBride, B. (2002), Jena: a semantic Web toolkit. IEEE Internet Computing, 6 (6), 55-59. McGuinness, D., van Harmelen, F. (2004). OWL Web Ontology Language Overview, http://www.w3.org/TR/owl-features/. Panetto, H., Dassistib, M., Tursia, A. (2012) ONTO-PDM: Product-driven ONTOlogy for Product Data Management interoperability within manufacturing process environment. Advanced Engineering Informatics. Slimani, K., Silva, C. Ferreira Da, Médini, L. and Ghodous, P. (2006). Conflict mitigation in collaborative design. International Journal of Production Research, 44 (9), 1681-1702. Smith, C.A.P., Kisiel, K., Morrison, J. (2009). Working through synthetic worlds. Ashgate, Farnham, Surrey, UK. Spath, D.; Lentes, H.-P.; Lentes, J. (2005). Towards an ontology supporting the planning of production systems. Production Engineering: Research and development in Germany - Annals of the German Academic Society for Production Engineering, 12 (2), 117-120. Spath, D., Lentes, J. (2009). Ontology-based linking of product development and production planning. In Proceedings of International Conference on Production Research ICPR20. Wache, H.; Vögele, T.; Visser, U.; Stuckenschmidt, H.; Schuster, G.; Neumann, H.; Hübner, S. (2001). Ontology-Based Integration of Information – A Survey of Existing Approaches. In Proceedings of IJCAI-01, Seventh International Joint Conference on Artificial Intelligence. Young, R. I. M., Gunendran, A. G., Cutting-Decelle, A. F., Gruninger, M. (2007). Manufacturing knowledge sharing in PLM: a progression towards the use of heavy weight ontologies. International Journal of Production Research, 45 (7), 1505-1519.
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978-3-902823-35-9/2013 © IFAC
1768
10.3182/20130619-3-RU-3018.00525
2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
Kerr et al. (2006), and Lacy (2005). For this reason, not only the “document”, i.e. the ontology, is beneficial as an up-todate type of a project glossary but its joint formulation based on discussions and cooperation by the involved parties. The benefit of ontology-based approaches to advance the common understanding in the context of engineering-related activities has been researched in relation to requirements by Kerr et al. (2006) and to manufacturing by Lin et al. (2004), showing its appropriateness for the support of the co-operation of engineers along the processes for product and production engineering, resulting in lower efforts and shorter time-tomarkets for new products by enhanced communication. The second essential reason for the ontology-based approach of the platform, besides its usefulness as common vocabulary to support a documented understanding, is its benefit for systems integration, i.e. to realise an integrated but open system. For this purpose, the platform builds on work as the ontology-based approaches for the support of data and information integration by Wache et al. (2001), for enterprise integration by Izza et al. (2005), for interoperability in the manufacturing area by Knutilla et al. (1998), and the comprehensive engineering-related work by Spath and Lentes (2009). In addition, the standard-related work concerning enterprise-control system integration is considered by Chen (2005), amongst others. To support systems integration, i.e. the continuous flow of data and information from one software system or module to another, the ontology realises a semantic data model with concepts, relation, and their respective attributes. The ontology is formulated in the quasistandard notation OWL (Web Ontology Language, cf. McGuinness and van Harmelen (2004)), enabling the usage of existing tools and libraries to work with the ontology as well as to implement interfaces for reading and writing data and operating on it. See the work of McBride (2002) for an example programming library. The application of an ontology as semantic data model enables the derivation of specific concepts of the application domain of a knowledge-based system from generic concepts that are independent of the domain and supports the reuse of the implemented problem solving methods. Although work concerning ontologies and problem solving methods is done since more than a dozen years, for an example please refer to Goméz Pérez and Benjamins (1999), not much work has been done to implement this promising approach to the engineering domain. Spath et al. (2005) introduced the ontology-based usage of domain-neutral problem solving methods in the specific context of production systems planning. E.g. the modelling of a production system as directed graph with the system element as nodes and material flow as edges enables the application of generic analysis methods from graph theory on the production system without further adaption. Eckstein (2010) presented the EC-funded project SWOP addressing the application of ontologies and problem solving methods to develop optimized combinations for products and production systems, even when these come from different suppliers, in order to obtain individual solutions to customer-specific problems.
An essential advantage of the application of ontologies in product development is knowledge sharing. Bradfield and Gao (2007) determined three main problem categories for knowledge sharing in the new product development (NPD) process of a manufacturing company: inappropriate information about the knowledge in the NPD process, multilingualism as well as multidisciplinarity, and insufficient information provision to users. By means of an ontology-based approach, knowledge sharing in NPD may be facilitated. Lutters et al. (2000) work to apply information management based on an ontological approach on design and engineering processes under special consideration of manufacturing, i.e. process planning and cost estimation. Young et al. (2007) show the benefits of applying ontologies to support knowledge sharing in PLM with a focus on manufacturing processes. By using a product ontology as pivotal element, Panetto et al (2012) introduce an approach to support interoperability in Product Data Management (PDM). Matsokis and Kiritsis (2010) developed an ontology of concepts and rules to support PLM, emphasizing the product and its role in closed-loop PLM. This shows advantages of the application of ontologies for PLM like automatically (rule-based) handling of multiple data from multiple physical products and of concept equivalencies-inconsistencies, supporting system interoperability and data integration. Slimani et al. (2006) presented an approach to support conflict management in collaborative design by means of an ontology-based approach. To summarize, a comprehensive approach leveraging the usage of an ontology as joint vocabulary, as integrative semantic data model and to implement information provision and the application of neutral problem-solving methods for the integrated development of products and production systems could not be identified in scientific work nor as commercially available software system, but partial solutions exist. 4. SOLUTION APPROACH 4.1 Principal Architecture To tackle the resulting challenges for engineering in manufacturing companies the platform is, as motivated in chapter 3, based on an ontology that serves as an interoperable model and integrating element for an open engineering system (the Platform). Second main element of overall solution are methods implemented as modules to realize tools to assist in product and process development, analysis, virtual testing, and optimization based on heuristic methods and simulation that operate on knowledge represented by information, which is structured by means of an ontology. The usage of an ontology-based approach enables the application of domain-neutral problem solving methods to specific engineering activities. Third building block of the solution is an open engineering platform laid on existing tools and libraries, specifically on Open Source Software systems. The resulting principal architecture of the overall solution is briefly shown in Fig. 2.
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
inter- or intranets. Along the entities in the ontology, a semantic search will be constructed and federated over distributed sources.
and PLM), funded by the European Commission as part of the “Factories-of-the-Future” Programme, contract number 285171.
After first approaches using existing open source and commercial tools like Protégé, Semantic MediaWiki and OntoStudio/OntoBroker, currently a second version completely based on open source technology is developed, based on the framework for building Semantic Web applications Jena (Jena, 2012). To support the presentation of the potential and benefits of the approach, a simple frontend has been developed, which enables the unobtrusive information provision while editing text documents in Microsoft® Word, e.g. during the definition of product requirements.
The consortium of the project consists in alphabetical order of Aerogen Ltd, Association pour la Recherche et le Developpement des Methodes et Processus Industriels, Fraunhofer IAO, Intel Performance Learning Solutions Limited, MBtech Group GmbH & Co KGaA, Ontoprise GmbH, Politecnico di Torino, R.T.T., Shannon Coiled Springs Limited, Universita degli Studi di Trieste, Universität Stuttgart, University of Limerick, University of Nottingham.
6. CONCLUSIONS In this paper, an integrative open platform supporting engineers in the integrated development of products and the related production systems has been presented. Besides the neutral software platform itself, essential elements of the overall solution are modules representing methods as well as interfaces to software systems that have already existed in industrial companies, and engineering models. This is a set of ontologies as semantic data model and documented common vocabulary facilitating communication among humans and software systems. Main advantages to be leveraged by the solution presented are reduced times to search data and information during engineering activities, support by means of problem solving methods, capturing and re-use of knowledge and experience as well as integrated access to information distributed in different software systems by the interoperability aspect of the solution. Focus of the paper is the semantic backend as an essential part of the platform. The semantic backend acts as “long-term memory” of the solution. Moreover, the backend enables the retrieval of information from external sources as the file system, databases, or legacy systems. The development of first prototypes has been done in two steps. At first, the base for the development was commercial available technology. To push the usage and advancement of the developed solution prevent a vendor lock-in with the according risks, emphasis has been put on open source software, resulting in the current usage of Jena as essential base technology for the semantic backend. Further work concerning the backend will concentrate on the implementation of software agents to support semantic information retrieval in the file system, intranet and extranet as well as interfacing towards databases and legacy systems in the real-world pilot cases. In addition, the solution that is prototypically developed will be advanced to a system that is scalable and robust enough to be applied in daily work of practitioners in real industrial settings. ACKNOWLEDGEMENT The work presented in this paper is part of the project amePLM (advanced Platform for manufacturing engineering
REFERENCES Bradfield, D. J., Gao J. X. (2007): A methodology to facilitate knowledge sharing in the new product development process. International Journal of Production Research 45 (7), 1489–1504. Chen, D. (2005). Enterprise-control system integration—an international standard. International Journal of Production Research 43 (20), 4335–4357. Eckstein, H. (2010). Self-Optimized, Individual Product and Production Solutions. Product Data Journal, 17 (1), 5458. Goméz Pérez, A., Benjamins, V.R. (1999). Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem Solving Methods. In Proceedings of the IJCAI-99 workshop on Ontologies and Problem Solving Methods, 1.1-1.15. Stockholm, Sweden. Gruber, T. (1993). A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition, 5 (2), 199-220. Izza, S.; Vincent, L.; Burlat, P. (2005). A Unified Framework for Enterprise Integration: An Ontology-Driven ServiceOriented Approach. In Proceedings of Interop-ESA ’05. Geneva, Switzerland. Jasper, R., Uschold, M. (1999). A Framework for Understanding and Classifying Ontology Applications. In Twelfth Workshop on Knowledge Acquisition Modeling and Management KAW'99. Banff, Alberta, Canada. JADE (2012) JADE (Java Agent DEvelopment Framework. WWW-Page: (22nd November 2012): http:// http://jade.tilab.com. Jena (2012) Apache Jena: WWW-Page. (24th November 2012): http://jena.apache.org.JESS (2012). Jess, the Rule Engine for the Java Platform: WWW-Page. (24th November 2012): http://herzberg.ca.sandia.gov. Kerr, C. I. V., Roy, R. and Sackett, P. J. (2006). Requirements management: an enabler for concurrent e automotive industry. International Journal of Production Research, 44 (9), 1703-1717. Knutilla, A.; Schlenoff, C.; Ivester, R. (1998). A Robust Ontology for Manufacturing Systems Integration. In Proceedings of the Second International Conference on Engineering Design and Automation. Maui, Hawaii, USA. Lacy, L. (2005). OWL: representing information using the web ontology language. Trafford , Victoria, B.C., USA.
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2013 IFAC MIM June 19-21, 2013. Saint Petersburg, Russia
Light, J., and Miller, J. D. (2002). Miramar: a 3D Workplace. In Proceedings of the IEEE Professional Communication Conference 2002, 271-282. Portland, Oregon, USA. Lin, H. -K., Harding, J. A. and Shahbaz, M.(2004) Manufacturing system engineering ontology for semantic interoperability across extended project teams, International Journal of Production Research, 42 (24), 5099-5118. Lutters, E., Brinke, E. T., Streppel, T., Kals, H. (2000). Information management and design & engineering processes. International Journal of Production Research, 38 (17), 4429-4444. Matsokis, A.; Kiritsis, D. (2010). An ontology-based approach for Product Lifecycle Management. Computers in Industry, 61 (8), 787-797. McBride, B. (2002), Jena: a semantic Web toolkit. IEEE Internet Computing, 6 (6), 55-59. McGuinness, D., van Harmelen, F. (2004). OWL Web Ontology Language Overview, http://www.w3.org/TR/owl-features/. Panetto, H., Dassistib, M., Tursia, A. (2012) ONTO-PDM: Product-driven ONTOlogy for Product Data Management interoperability within manufacturing process environment. Advanced Engineering Informatics. Slimani, K., Silva, C. Ferreira Da, Médini, L. and Ghodous, P. (2006). Conflict mitigation in collaborative design. International Journal of Production Research, 44 (9), 1681-1702. Smith, C.A.P., Kisiel, K., Morrison, J. (2009). Working through synthetic worlds. Ashgate, Farnham, Surrey, UK. Spath, D.; Lentes, H.-P.; Lentes, J. (2005). Towards an ontology supporting the planning of production systems. Production Engineering: Research and development in Germany - Annals of the German Academic Society for Production Engineering, 12 (2), 117-120. Spath, D., Lentes, J. (2009). Ontology-based linking of product development and production planning. In Proceedings of International Conference on Production Research ICPR20. Wache, H.; Vögele, T.; Visser, U.; Stuckenschmidt, H.; Schuster, G.; Neumann, H.; Hübner, S. (2001). Ontology-Based Integration of Information – A Survey of Existing Approaches. In Proceedings of IJCAI-01, Seventh International Joint Conference on Artificial Intelligence. Young, R. I. M., Gunendran, A. G., Cutting-Decelle, A. F., Gruninger, M. (2007). Manufacturing knowledge sharing in PLM: a progression towards the use of heavy weight ontologies. International Journal of Production Research, 45 (7), 1505-1519.
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