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Realisability of production recipes

de Silva, Lavindra; Felli, Paolo; Chaplin, Jack C.; Logan, Brian; Sanderson, David; Ratchev, Svetan

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Authors

Lavindra de Silva

Paolo Felli

Brian Logan

Professor SVETAN RATCHEV svetan.ratchev@nottingham.ac.uk
CRIPPS PROFESSOR OF PRODUCTION ENGINEERING & HEAD OF RESEARCH DIVISION



Abstract

There is a rising demand for customised products with a high degree of complexity. To meet these demands, manufacturing lines are increasingly becoming autonomous, networked, and intelligent, with production lines being virtualised into a manufacturing cloud, and advertised either internally to a company, or externally in a public cloud. In this paper, we present a novel approach to two key problems in such future manufacturing systems: the realisability problem (whether a product can be manufactured by a set of manufacturing resources) and the control problem (how a particular product should be manufactured). We show how both production recipes specifying the steps necessary to manufacture a particular product, and manufacturing resources and their topology can be formalised as labelled transition systems, and define a novel simulation relation which captures what it means for a recipe to be realisable on a production topology. We show how a controller that can orchestrate the resources in order to manufacture the product on the topology can be extracted from the simulation relation, and give an algorithm to compute a simulation relation and a controller.

Citation

de Silva, L., Felli, P., Chaplin, J. C., Logan, B., Sanderson, D., & Ratchev, S. (2016, August). Realisability of production recipes. Presented at 22nd European Conference in Artificial Intelligence (ECAI 2016), The Hague, The Netherlands

Presentation Conference Type Edited Proceedings
Conference Name 22nd European Conference in Artificial Intelligence (ECAI 2016)
Start Date Aug 29, 2016
End Date Sep 2, 2016
Acceptance Date Jun 17, 2016
Publication Date 2016
Deposit Date Jul 26, 2016
Publicly Available Date Dec 31, 2016
Publisher IOS Press
Peer Reviewed Peer Reviewed
Volume 285
Pages 1449-1457
Book Title ECAI 2016 - 22nd European Conference on Artificial Intelligence
ISBN 978-1-61499-671-2
DOI https://doi.org/10.3233/978-1-61499-672-9-1449
Public URL https://nottingham-repository.worktribe.com/output/804756
Publisher URL http://ebooks.iospress.nl/volumearticle/44902
Related Public URLs http://www.ecai2016.org/
Contract Date Jul 26, 2016

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