NDLI: Modeling impact of choice complexity on production rate in mixed-model assembly system

Content Provider	Springer Nature Link
Author	Wang, Kunpeng Rao, Yunqing Wang, Mengchang
Copyright Year	2011
Abstract	The increasing variety of products complicates the mixed-model assembly process and affected the mixed-model assembly system in terms of product quality and productivity. Choice complexity comes from the process of making choices for various assembly operations due to the product variety and impacts production rate which is the performance measure of the system. The choice complexity is measured with information entropy, and the relational expression between choice complexity and error rate is analyzed by means of those research finds on average reaction time and speed-accuracy trade-off. The main achievement of our study is establishing an artificial neural network meta-model for the impact of choice complexity on production rate. The meta-model performs better than a multiple linear regression meta-model in terms of experiment results and appears to be the optimal model of the impact of choice complexity on production rate in the mixed-model assembly system.
Starting Page	1181
Ending Page	1189
Page Count	9
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	59
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-08-07
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Choice complexity Error rate Meta-model Artificial neural network Mechanical Engineering Industrial and Production Engineering Computer-Aided Engineering (CAD, CAE) and Design Production/Logistics/Supply Chain
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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