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An optimization framework for enterprise quality infrastructure system under coupling constraints

Author

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  • Chen, Xiangpeng
  • Wang, Rongxi
  • Gao, Jianmin

Abstract

Improving quality infrastructure (QI) is the cornerstone of improving enterprise quality management activities. Currently, the lack of a QI system optimization approach makes it difficult to exploit the role of QI for enterprise quality improvement. In this study, a generic QI system optimization framework is proposed to guide the development of enterprise QI optimization strategies, and three ideas of coupling constraints are presented in QI optimization for the first time: (1) How does optimization reflect the logical connotation of QI? (2) How to incorporate the cost of optimization? (3) How to determine and guide the direction of QI optimization? Firstly, the QI optimization index system is constructed to reflect the current QI level and future development goals of the enterprise. Secondly, the coupling constraint mechanism of QI system optimization is modeled based on the idea of the heterogeneous information network: the QI indicator sensitivity algorithm is designed to integrate it with cost and urgency. Finally, the optimization index characterizing the priority of QI index optimization is proposed to realize the formulation of enterprise optimization strategies. The framework is applied to eight QI system optimization cases of typical Oil Country Tubular Goods (OCTG) companies. The results show that the proposed framework can solve the three major factors in QI optimization, which is more in line with the enterprise optimization construction and fills the gap in the field of QI optimization. This work can provide ideas for the optimization of systems with such coupling constraint characteristics in other fields.

Suggested Citation

  • Chen, Xiangpeng & Wang, Rongxi & Gao, Jianmin, 2023. "An optimization framework for enterprise quality infrastructure system under coupling constraints," International Journal of Production Economics, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:proeco:v:262:y:2023:i:c:s0925527323001299
    DOI: 10.1016/j.ijpe.2023.108897
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