A Systematic Approach To Model Human System In Cellular Manufacturing

Manufacturing becomes increasingly complex as more variations and uncertainties are introduced to the system. Human competencies are valuable to the operation and are considered to be the most flexible manufacturing component. However, there is still lack of study on the impact of human aspects to...

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Bibliographic Details
Main Authors: Abdullah, Rohana, Abd Rahman, Md Nizam, Salleh, Mohd Rizal
Format: Article
Language:English
Published: The Japan Society of Mechanical Engineers 2019
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Online Access:http://eprints.utem.edu.my/id/eprint/24043/2/JSME%20-%20Systematic%20Approach%20to%20Model%20Human%20System%20in%20Cellular%20Manufacturing.pdf
http://eprints.utem.edu.my/id/eprint/24043/
https://www.jstage.jst.go.jp/article/jamdsm/13/1/13_2019jamdsm0001/_article/-char/en
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Summary:Manufacturing becomes increasingly complex as more variations and uncertainties are introduced to the system. Human competencies are valuable to the operation and are considered to be the most flexible manufacturing component. However, there is still lack of study on the impact of human aspects to the cellular manufacturing system performance. This article reports a case study application to evaluate the human impact in the complex cellular manufacturing system. Specifically, this work shows a systematic approach to depict and evaluate the human dynamics and attributes in measuring the labor utilization and determining the ideal man-machine configuration. The literature on modelling technologies relevant to cellular manufacturing design and change is presented to provide the rationale for the use of heuristic and enterprise modelling for this study. Evaluations on the existing human system model, CIMOSA and the heuristic mathematical model resulted in the development of an enhanced human system model framework. The newly developed model focuses on the aspects of human dynamics and attributes. To improve human work measurement data accuracy, the model also uses Maynard Operational Sequence Technique (MOST). An expert system was also developed which greatly reduced the time and effort spent on data entry and data analysis. An example using a multi-national semiconductor assembly and test company is presented where 20% improvement in resource efficiency and additional machine to a labor reconfiguration was achieved without any human fallout.