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An integrated scheduling method for personalized products with no-wait constraints.

Authors :
Xiaowei, Zhang
Zhiqiang, Xie
Xia, Shao
Yingchun, Xia
Source :
International Journal of Advanced Manufacturing Technology. Sep2022, Vol. 122 Issue 1, p279-290. 12p. 9 Diagrams, 1 Chart, 2 Graphs.
Publication Year :
2022

Abstract

In the production of personalized, non-standard and trial products, orders are often single-piece or small-batch, and the processing parameters and BOM structure vary greatly between products. In such cases, it is necessary to consider processing and assembly in an integrated manner, and directly formulate flexible scheduling solutions according to the precedence constraints of BOM (PCB). To design such integrated scheduling method for personalized products with no-wait constraints (ISMPNC), firstly, a mathematical model considering both no-wait constraints and flexible machines is established, then, the event-based rescheduling rule (ERR) is used to deal with dynamic production tasks; finally, to solve the mathematical model, the artificial bee colony (ABC) algorithm with enhancements is proposed. Hence, a virtual grouping-based encoding method is designed to handle the precedence constraints when the number of no-wait predecessors is greater than one; a first-time-fit decoding method based on overlapping time is proposed to guarantee that no-wait operations always meet the precedence and no-wait constraints after decoding; a discrete differential equation based on the Hemming distance is proposed so that the ABC is capable of handling discrete encoding spaces; a neighborhood action based on key product moving is proposed and embedded into the ABC to enhance the local search capability. The operation research solver OR-Tools is used to verify the correctness of the mathematical model. The proposed ISMPNC considers both no-wait constraints and flexible machines, which is more realistic than the control method and could obtain a better scheduling scheme. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
122
Issue :
1
Database :
Academic Search Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
159003271
Full Text :
https://doi.org/10.1007/s00170-022-09394-8