Smart Master Production Schedule for the Supply Chain: A Conceptual Framework

Computers

Julio C. Serrano-Ruiz¹  Josefa Mula¹  Raúl Poler¹ 

[1] Research Centre on Production Management and Engineering (CIGIP), Universitat Politècnica de València Escuela Politécnica Superior de Alcoy, C/Alarcón 1, Alcoy, 03801 Alicante, Spain;

关键词: supply chain 4.0;    master production schedule;    zero-defect manufacturing;    digital twin;    machine learning;   

DOI  :  10.3390/computers10120156

来源: DOAJ

【 摘 要 】

Risks arising from the effect of disruptions and unsustainable practices constantly push the supply chain to uncompetitive positions. A smart production planning and control process must successfully address both risks by reducing them, thereby strengthening supply chain (SC) resilience and its ability to survive in the long term. On the one hand, the antidisruptive potential and the inherent sustainability implications of the zero-defect manufacturing (ZDM) management model should be highlighted. On the other hand, the digitization and virtualization of processes by Industry 4.0 (I4.0) digital technologies, namely digital twin (DT) technology, enable new simulation and optimization methods, especially in combination with machine learning (ML) procedures. This paper reviews the state of the art and proposes a ZDM strategy-based conceptual framework that models, optimizes and simulates the master production schedule (MPS) problem to maximize service levels in SCs. This conceptual framework will serve as a starting point for developing new MPS optimization models and algorithms in supply chain 4.0 (SC4.0) environments.

【 授权许可】

Unknown