Recipe-based Integrated Semantic Product, Process, Resource (PPR) Digital Modelling Methodology

Virtual engineering methods based on digital modelling and simulations have potential to improve analysis and performance of manufacturing systems. Current generation digital modelling techniques in view of systems design and life cycle modelling attempts to integrate aspects of product, process and resource requirements. Despite these advances, to facilitate rapid design and provide support for the selection of processes and resources, there is the need to semantically model and integrate product-process requirements with resource capabilities. This paper therefore p resents a ‘recipe-based’ approach to modelling based on ontologies with capability to rapidly define and select resource sys tems meeting product a nd process requirements. © 2014 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of th e International Scientific Committee of “The 47th CIRP Conference on Manufacturing Systems” in the person of the Conference Chair Professor Hoda ElMaraghy.

[1]  Svetan Ratchev,et al.  Review of semantic modelling technologies in support of virtual factory design , 2013 .

[2]  François Vernadat,et al.  UEML: Towards a unified enterprise modelling language , 2002 .

[3]  José Barbosa,et al.  Bio-inspired multi-agent systems for reconfigurable manufacturing systems , 2012, Eng. Appl. Artif. Intell..

[4]  Darek Ceglarek,et al.  Qualitative product/process modelling for reconfigurable manufacturing systems , 2013, 2013 IEEE International Symposium on Assembly and Manufacturing (ISAM).

[5]  Tonci Grubic,et al.  Supply chain ontology: Review, analysis and synthesis , 2010, Comput. Ind..

[6]  Yasumichi Aiyama,et al.  A holonic architecture for easy reconfiguration of robotic assembly systems , 2003, IEEE Trans. Robotics Autom..

[7]  Jenny A. Harding,et al.  A manufacturing system engineering ontology model on the semantic web for inter-enterprise collaboration , 2007, Comput. Ind..

[8]  Guus Schreiber,et al.  Knowledge Engineering and Management: The CommonKADS Methodology , 1999 .

[9]  Nigel Shadbolt,et al.  Knowledge Engineering and Management , 2000 .

[10]  Lanfen Lin,et al.  Developing manufacturing ontologies for knowledge reuse in distributed manufacturing environment , 2011 .

[11]  Niels Lohse,et al.  Fundamentals of a co-design methodology for improving the performance of machine tools based on semantic representation , 2013, Int. J. Comput. Integr. Manuf..

[12]  Américo Azevedo,et al.  Factory Templates for Digital Factories Framework , 2011 .

[13]  Angappa Gunasekaran,et al.  Information systems in supply chain integration and management , 2004, Eur. J. Oper. Res..

[14]  Paolo Pedrazzoli,et al.  Virtual Factory Framework: Key Enabler For Future Manufacturing , 2007 .

[15]  Tullio Tolio,et al.  SPECIES—Co-evolution of products, processes and production systems , 2010 .

[16]  Krassen Stefanov,et al.  Selection and use of domain ontologies in Learning Networks for Lifelong Competence Development , 2006 .

[17]  Svetan Ratchev,et al.  Equipment ontology for modular reconfigurable assembly systems , 2005 .

[18]  Luís Miguel Marques Borges,et al.  Virtual factory framework , 2010 .

[19]  László Monostori,et al.  Agent-based systems for manufacturing , 2006 .

[20]  Botond Kádár,et al.  Towards adaptive and digital manufacturing , 2010, Annu. Rev. Control..

[21]  Ahmed Azab,et al.  Modelling evolution in manufacturing: A biological analogy , 2008 .