With the increase of market fluctuation, assembly systems moved from a mass production scheme to a mass customization scheme. Mixed model assembly systems (MMASs) have been recognized as enablers of mass customization manufacturing. However, effective implementation of MMASs requires, among other things, a highly proactive and knowledgeable workforce. Hence, modeling the performance of human operators is critically important for effectively operating these manufacturing systems. But, certain cognitive factors have seldom been considered when it comes to modeling process quality of MMASs. Thus, the objective of this paper is to introduce an integrated modeling framework by considering the factors—both intrinsic (such as work experience, mental deliberation time, etc.) and extrinsic (such as task complexity)—that affect the operator’s performance. The proposed model is justified based on the findings presented in the psychological literature. The effect of these factors on process operation performance is also investigated; these performance measures include process quality, throughput, and process capability in regard to handling complexity induced by product variety in MMASs. Two examples are used to demonstrate potential applications of the proposed model.
Modeling and Analysis of Operator Effects on Process Quality and Throughput in Mixed Model Assembly Systems
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Abad, A. G., Paynabar, K., and Jin, J. J. (April 4, 2011). "Modeling and Analysis of Operator Effects on Process Quality and Throughput in Mixed Model Assembly Systems." ASME. J. Manuf. Sci. Eng. April 2011; 133(2): 021016. https://doi.org/10.1115/1.4003793
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