Decisional DNA (DDNA) Based Machine Monitoring and Total Productive Maintenance in Industry 4.0 Framework

被引：4

作者：

Shafiq, Syed Imran ^{[1
]}

Sanin, Cesar ^{[2
]}

Szczerbicki, Edward ^{[3
]}

机构：

[1] Aligarh Muslim Univ, Fac Engn & Technol, Aligarh, Uttar Pradesh, India

[2] Univ Newcastle, Fac Engn & Built Environm, Callaghan, NSW, Australia

[3] Gdansk Univ Technol, Fac Management & Econ, Gdansk, Poland

来源：

CYBERNETICS AND SYSTEMS | 2022年 / 53卷 / 05期

关键词：

Decisional DNA; SOEKS; machine monitoring; total productive maintenance;

D O I：

10.1080/01969722.2021.2018549

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：510 / 519

页数：10

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