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Study on Quality Prediction Technology of Manufacturing Supply Chain

Study on Quality Prediction Technology of Manufacturing Supply Chain

Genbao Zhang, Yan Ran, Dongmei Luo
Copyright: © 2015 |Volume: 8 |Issue: 4 |Pages: 19
ISSN: 1935-5726|EISSN: 1935-5734|EISBN13: 9781466676428|DOI: 10.4018/ijisscm.2015100104
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MLA

Zhang, Genbao, et al. "Study on Quality Prediction Technology of Manufacturing Supply Chain." IJISSCM vol.8, no.4 2015: pp.44-62. http://doi.org/10.4018/ijisscm.2015100104

APA

Zhang, G., Ran, Y., & Luo, D. (2015). Study on Quality Prediction Technology of Manufacturing Supply Chain. International Journal of Information Systems and Supply Chain Management (IJISSCM), 8(4), 44-62. http://doi.org/10.4018/ijisscm.2015100104

Chicago

Zhang, Genbao, Yan Ran, and Dongmei Luo. "Study on Quality Prediction Technology of Manufacturing Supply Chain," International Journal of Information Systems and Supply Chain Management (IJISSCM) 8, no.4: 44-62. http://doi.org/10.4018/ijisscm.2015100104

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Abstract

Supply chain quality is the assurance of product quality in its full life-cycle. Although supply chain quality control is a hot topic among researchers, supply chain quality prediction is actually an important but unsolved problem in manufacturing industry. In this paper, an approach of manufacturing supply chain quality prediction based on quality satisfaction degree is proposed to control supply chain better, in order to help ensure product quality. Supply chain quality prediction 3D model and model based on customer satisfaction and process control are established firstly. And then technologies used in quality prediction are studied, including quality prediction index system established on Expert scoring -AHP and prediction workflow built on ABPM. Finally an example is given to illustrate this approach. The customer satisfaction prediction result of supply chain quality can help supply chain management, and the quality prediction software system can make it easier, which provides a new direction for the product quality control technology research.

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