Decisional-DNA Based Smart Production Performance Analysis Model

Title
Decisional-DNA Based Smart Production Performance Analysis Model
Publication Date
2019
Author(s)
Shafiq, Syed Imran
Szczerbicki, Edward
Sanin, Cesar
( author )
OrcID: https://orcid.org/0000-0001-8515-417X
Email: cmaldon3@une.edu.au
UNE Id une-id:cmaldon3
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Taylor & Francis Inc
Place of publication
United States of America
DOI
10.1080/01969722.2019.1565122
UNE publication id
une: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.

Link
Citation
Cybernetics and Systems, 50(2), p. 154-164
ISSN
1087-6553
0196-9722
Start page
154
End page
164

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