Performance Measure Of Industrial Robotics In Lean Enterprise: A Case Study In Semiconductor Industry

A. Perumal, Puvanasvaran and Safady, Hammam M. H. and Tay, Choo Chuan and Yoong, Sai Sieng (2019) Performance Measure Of Industrial Robotics In Lean Enterprise: A Case Study In Semiconductor Industry. International Journal Of Recent Technology And Engineering (IJRTE), 8 (1S5). pp. 12-16. ISSN 2277-3878

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Abstract

Industrial robotics replaced human workers in almost all fields due to their abilities to multitask, flexibility and configurability in any position they involved in. However, implementing industrial robotics is challenging due to their high cost, expert handling, and complexity. The object of this study is to determine the performance measurement using the QCDAC method or (quality, cost, delivery, accountability and continual improvement) then categorized according to lean principles and then identifying seven main areas that the industrial robotics contributes in the semi-conductor company. The performance identification and ranking is done by using Interpretive Structural Modelling (ISM) methodology to identify the most affected performance of the model and to clarify the industrial robotics performance in these areas in which the industrial robotics fit and compatible with the lean enterprise. Human- robot interaction considered to guarantee the workers' safety working alongside industrial robotics. The result of the ISM method shows the performance measure that affects the industrial robotics to support lean enterprise in terms of quality improvement, cost reduction and efficiency.

Item Type:	Article
Uncontrolled Keywords:	Lean enterprise, industrial robotics, human interaction, interpretive structural modeling, Semiconductor Industry
Subjects:	T Technology > T Technology (General) T Technology > TS Manufactures
Divisions:	Faculty of Manufacturing Engineering
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	28 Jul 2020 14:32
Last Modified:	28 Jul 2020 14:32
URI:	http://eprints.utem.edu.my/id/eprint/24077
Statistic Details:	View Download Statistic

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