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Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/26767

Title: Interoperable manufacturing knowledge systems
Authors: Palmer, Claire
Usman, Zahid
Canciglieri, Osiris
Malucelli, Andreia
Young, R.I.M.
Keywords: Interoperability
Decision support
Reference ontologies
Manufacturing systems
Knowledge sharing
Issue Date: 2017
Publisher: © Taylor & Francis
Citation: PALMER, C. ... et al, 2017. Interoperable manufacturing knowledge systems. International Journal of Production Research, In Press.
Abstract: For many years now, the importance of semantic technologies, that provide a formal, logic based route to sharing meaning, has been recognized as offering the potential to support interoperability across multiple related applications and hence drive manufacturing competitiveness in the digital manufacturing age. However, progress in support of manufacturing enterprise interoperability has tended to be limited to fairly narrow domains of applicability. This paper presents a progression of research and understanding, culminating in the work undertaken in the recent EU FLEXINET project, to develop a comprehensive manufacturing reference ontology that can (a) support the clarification of understanding across domains, (b) support the ability to flexibly share information across interacting software systems and (c) provide the ability to readily configure company knowledge bases to support interoperable manufacturing systems.
Description: This paper is closed access until 12 months after publication.
Sponsor: We wish to acknowledge the FLEXINET consortium and especially the financial support from the European Union Seventh Framework Programme FP7-2013-NMP-ICT-FOF (RTD) under grant agreement no 688627. We also wish to acknowledge the support of the EPSRC in the early research understanding presented in this paper who funded the Interoperable Manufacturing Knowledge Systems (IMKS) under project 253 of the Loughborough University Innovative Manufacturing and Construction Research Centre (IMCRC). We also wish to acknowledge the Brazilian Science without Borders programme who supported inputs through the “Intelligent Knowledge Libraries: exploiting new ICT technologies for improved Manufacturing Intelligence” project.
Version: Accepted for publication
URI: https://dspace.lboro.ac.uk/2134/26767
Publisher Link: http://www.tandfonline.com/toc/tprs20/current
ISSN: 0020-7543
Appears in Collections:Closed Access (Mechanical, Electrical and Manufacturing Engineering)

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