Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61813
Title: Decisional-DNA Based Smart Production Performance Analysis Model
Contributor(s): Shafiq, Syed Imran (author); Szczerbicki, Edward (author); Sanin, Cesar  (author)orcid 
Publication Date: 2019
Early Online Version: 2019-02-07
DOI: 10.1080/01969722.2019.1565122
Handle Link: https://hdl.handle.net/1959.11/61813
Abstract: 

In order to allocate resources effectively according to the production plan and to reduce disturbances, a framework for smart production performance analysis is proposed in this article. Decisional DNA based knowledge models of engineering objects, processes and factory are developed within the proposed framework. These models are the virtual representation of manufacturing resources, and with help of Internet of Things, are capable of capturing the past experience and formal decisions. A case study for the smart tool performance analysis is presented in which information of key tool parameters like tool life, surface integrity, tool forces and chip formation can be sensed in real-time, and predictions can be made according to specific requirements. This framework is capable of creating a cyber-physical conjoining of the bottom-level manufacturing resources and thus can work as a technological basis for smart factories and Industry 4.0.

Publication Type: Journal Article
Source of Publication: Cybernetics and Systems, 50(2), p. 154-164
Publisher: Taylor & Francis Inc
Place of Publication: United States of America
ISSN: 1087-6553
0196-9722
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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