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Feature-Based Adaptive Manufacturing Equipment Control for Cloud Environments
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0003-1265-8451
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. Royal Institute of Technology, Stockholm, Sweden. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0001-8679-8049
Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID-id: 0000-0002-1699-3778
Falmouth University, Cornwall, United Kingdom.
2016 (engelsk)Inngår i: Proceedings of the ASME 11th International Manufacturing Science and Engineering Conference, 2016, vol 2, American Society of Mechanical Engineers (ASME) , 2016, artikkel-id UNSP V002T04A019Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

The ideas of on-demand, scalable and pay-for-usage resource-sharing in Cloud Manufacturing are steadily attracting more interest. For implementing the concept of Manufacturing as-a-Service in a cloud environment, description models and implementation language for resources and their capabilities are required. A standardized approach for systemived virtualization, servisilisation, retrieval, selection and composition into higher levels of functionality is necessary. For the collaborative sharing and use of networked manufacturing resources there is also a need for a control approach for distributed manufacturing equipment. In this paper, the technological perspective for an adaptive cloud service-based control approach is described, and a supporting information model for its implementation. The control is realized through the use of a network of intelligent and distributable Function Block decision modules, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the cloud service management functionality is described, as well as a feature-level capability model and the use of ontologies and the Semantic Web.

sted, utgiver, år, opplag, sider
American Society of Mechanical Engineers (ASME) , 2016. artikkel-id UNSP V002T04A019
Emneord [en]
Cloud manufacturing, adaptive robot control, ontology
HSV kategori
Forskningsprogram
Teknik; Produktion och automatiseringsteknik
Identifikatorer
URN: urn:nbn:se:his:diva-13213DOI: 10.1115/MSEC2016-8771ISI: 000388159400054Scopus ID: 2-s2.0-84991619741ISBN: 978-0-7918-4990-3 (tryckt)OAI: oai:DiVA.org:his-13213DiVA, id: diva2:1054584
Konferanse
ASME 2016 11th International Manufacturing Science and Engineering Conference (MSEC 2016), Blacksburg, USA, June 27–July 1, 2016
Tilgjengelig fra: 2016-12-08 Laget: 2016-12-08 Sist oppdatert: 2018-03-28bibliografisk kontrollert

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