An effective multi-part dedicated flow-line reconfiguration model considering the optimal selection of machining process path and machines. (January 2023)

• Record Type: Journal Article
• Authors: Yu, Hao; Yang, Bo; Wang, Shilong; Wang, Yankai; Wang, Sibao; Wang, Zehua; Wang, Zhongning
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 237:Number 1/2(2023)
• Page Start: 154
• Page End: 170
• Publication Date: 2023-01
• Subjects: Reconfiguration manufacture system -- multi-part dedicated flow-line -- production line reconfiguration -- machining process path -- Enhanced Equilibrium Optimizer (EEO); Mechanical engineering -- Periodicals; Engineering -- Management -- Periodicals; Manufacturing processes -- Periodicals; 629.8
• DOI: 10.1177/09544054221100873
• Languages: English
• ISSNs: 0954-4054

Abstract

Multi-part Dedicated Flow-line (MDF) is widely used to produce discrete products for high volumes with low varieties. Since frequent changes occur in customers' demand and rapid upgrading of machines, the line needs to reconfigure timely to remain competitive. A lot of researchers investigate how to reconfigure the line when facing these changes, and most of them adopts small adjustments such as machine resettlement or buffer size rearrangements to react. However, when great changes occur in product' machining process or machine's performance, it's time to reconfigure the line in a higher level by reselecting machining process of products and/or reselecting machines composition of the line. To fill this research gap, the paper proposes an effective Multi-part Dedicated Flow-line Reconfiguration Model (MDFRM) which can effectively react to great changes occur in products and machines. By optimal selection of Machining Process Path (MPP) for every product and machines composition for the new line, MDFRM can reconfigure MDF with objective of minimizing the products' cost and capital investment. To solve this problem, an Enhanced Equilibrium Optimizer (EEO) with three layers of code and three steps to handling boundaries and constraints based on Equilibrium Optimizer (EO) is presented. The proposed new model and the designed method are validated by numerical experiments and real case study. This paper will significantly help decision-makers make a scientific decision to optimally reconfigure MDF.