Research on Flexible Job Shop Scheduling Considering Equipment Failure Disturbance

DOI

10.2991/978-94-6239-758-3_30How to use a DOI?

Keywords

equipment failure disturbance; flexible production workshop scheduling; scheduling algorithm improvement; complete rescheduling

Abstract

Addressing the scheduling disturbance issues arising from random equipment failures in an axial flexible job shop, this paper proposes a multi-objective dynamic scheduling method with the dual goals of minimizing the maximum completion time and maximizing the average equipment utilization rate. The performance of two strategies, complete rescheduling and right-shift rescheduling, is systematically compared. Firstly, a dynamic scheduling mathematical model considering failure disturbances is established, incorporating typical multi-process flexible machining paths for axial components (such as turning, grinding, gear machining, etc.). An improved non-dominated sorting genetic algorithm (NSGA-II) is employed for optimization and solution: a static Pareto front is generated in the initial stage, and after the occurrence of a failure, complete rescheduling (re-optimizing all unprocessed processes) and right-shift rescheduling (only postponing the subsequent processes affected by the failure in their original order) are executed respectively. Through the rapid non-dominated sorting and crowding distance mechanism of NSGA-II, a balance is achieved between minimizing the completion time and maximizing equipment utilization rate, and the computational efficiency and scheduling robustness of the two strategies are evaluated. Simulation experiments are conducted based on simulated data from a gearbox axial production workshop, with six types of workpieces, eight machines, a total of 42 processes, and an average equipment failure interval of 200 minutes. The experimental results show that, according to the simulated actual machining scenarios, the average completion time obtained by the complete rescheduling strategy is 1285 minutes, the average equipment utilization rate is 76.5%, and the average rescheduling computation time is 45 seconds; the average completion time obtained by the right-shift rescheduling strategy is 1356 minutes, the average equipment utilization rate is 73.8%, and the average rescheduling computation time is less than 1 seconds; the adaptive improved NSGA-II algorithm (ARI-NSGA-II) proposed in this paper achieves an average completion time of 1268 minutes, an average equipment utilization rate of 78.2%, a standard deviation of 9.6% in equipment utilization rate, and an average rescheduling computation time of 8 seconds under the same failure scenario. Compared to complete rescheduling, the proposed algorithm reduces the completion time by 1.3%, increases the equipment utilization rate by 1.7 percentage points, decreases the standard deviation of equipment utilization rate by 22.0%, and reduces the rescheduling computation time by 82.2%. This research provides a quantitative basis for selecting rescheduling strategies in axial flexible workshops under equipment failures.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zhanyi Zhu
PY  - 2026
DA  - 2026/09/08
TI  - Research on Flexible Job Shop Scheduling Considering Equipment Failure Disturbance
BT  - Proceedings of the 2026 7th International Conference on Management Science and Engineering Management (ICMSEM 2026)
PB  - Atlantis Press
SP  - 295
EP  - 302
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-758-3_30
DO  - 10.2991/978-94-6239-758-3_30
ID  - Zhu2026
ER  -