Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61748
Title: Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework
Contributor(s): Shafiq, Syed Imran (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2022-07
Early Online Version: 2021-12-22
DOI: 10.1080/01969722.2021.2018549
Handle Link: https://hdl.handle.net/1959.11/61748
Abstract: 

The entire manufacturing spectrum is transforming with the advent of Industry 4.0. The features of Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA) were utilized for developing Virtual Engineering Objects (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF), which in turn facilitate the creation of smart factories. In this study, DDNA based Machine Monitoring for Total Maintenance in Industry 4.0 framework is demonstrated. The concept of VEO is used for the Tool and Equipment Monitoring, while for the Plants Operations Monitoring and Quality Monitoring, VEP and VEF are employed. Query extraction feature of DDNA is exploited for Adaptive Control. This study shows that Machine Efficiency (ME) can be monitored along with analysis of machine KPI’s like breakdown time, setting time, and other losses. Moreover, reports can be generated efficiency-wise, breakdown-wise, operator-wise. The data of these reports is used to predict and make future decisions related to machine maintenance.

Publication Type: Journal Article
Source of Publication: Cybernetics and Systems, 53(5), p. 510-519
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

Files in This Item:
1 files
File SizeFormat 
Show full item record

SCOPUSTM   
Citations

4
checked on Jan 25, 2025

Page view(s)

172
checked on Aug 3, 2024

Download(s)

2
checked on Aug 3, 2024
Google Media

Google ScholarTM

Check

Altmetric


Items in Research UNE are protected by copyright, with all rights reserved, unless otherwise indicated.