A production optimization model of supply-driven chainwith quality uncertainty.pdf

A production optimization model of supply-driven chainwith quality uncertainty.pdf

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A production optimization model of supply-driven chainwith quality uncertainty

J Syst Sci Syst Eng (Jun 2012) 21(2): 144-160 ISSN: 1004-3756 (Paper) 1861-9576 (Online) DOI: 10.1007/s11518-011-5184-8 CN11-2983/N ? Systems Engineering Society of China and Springer-Verlag Berlin Heidelberg 2012 A PRODUCTION OPTIMIZATION MODEL OF SUPPLY-DRIVEN CHAIN WITH QUALITY UNCERTAINTY? Renbin XIAO1 Zhengying CAI1 Xinhui ZHANG2 1 Institute of Systems Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China rbxiao@163.com caizhengying@ 2 Department of Biomedical, Industrial Human Factors Engineering, Wright State University, Dayton, OH 45435, USA xinhui.zhang@ Abstract Supply-driven chain’s production is different from traditional demand-driven production because its supplies must guide the full production flow toward the markets and respond actively to customer demand. According to the control theory, a novel multi-variable operation model of supply-driven chain is discussed here, integrating suppliers, manufacturers, distributors and market demands. Especially the coordination problem between suppliers and manufacturers is discussed where suppliers play more important role than manufacturers. Because defect is common in real production system, the production operation of supply-driven chain with imperfect quality is described on the basis of fuzzy set to model the ambiguity of quality and to provide appropriate supply coordination mechanism. In a designed numerical example, it is apparent that both response and robustness performances of supply-driven production system on demand with imperfect quality are improved by a fuzzy proportional-integral- differential regulator. The proposed model may apply to similar productions with imperfect quality. Keywords:Supply-driven chain, quality, production planning, fuzzy regulator *This work is supported by the National Natural Science Foundation of China (Grant No.. 1. Introduction

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