Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61901
Title: Knowledge based modelling framework for flexible manufacturing system
Contributor(s): Shafiq, Syed Imran (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2019-09
DOI: 10.46354/i3m.2019.emss.002
Handle Link: https://hdl.handle.net/1959.11/61901
Abstract: 

This paper proposes knowledge-based modelling framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical Flexible Manufacturing System (FMS). The framework utilizes the concept of virtual engineering object (VEO) and virtual engineering process (VEP) for developing knowledge models of FMS to achieve effective scheduling and manufacturing flexibility. The proposed generic model is capable of capturing in real time the manufacturing data, information and knowledge at every stage of production i.e. at the object level, the process level, and at the factory level. The significance of this study is that it supports decision making by reusing past decisional experience, which will not only help in effective real time data monitoring and processing but also make FMS system more intelligent and ready to function in the virtual Industry 4.0 environment.

Publication Type: Conference Publication
Conference Details: EMSS 2019: 31st European Modeling & Simulation Symposium, Lisbon, Portugal, 18th - 20th September, 2019
Source of Publication: Proceedings of the 31st European Modeling & Simulation Symposium (EMSS 2019), p. 9-15
Publisher: DIME University of Genoa, DIMEG University of Calabria
Place of Publication: Italy
ISSN: 2724-0029
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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