Job Shop Rescheduling Under Recessive Disturbance Based on Digital Twin

Authors

Dinghui Wu, 1.Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Wuxi 214122, China;Follow
Tongrui Zhang, 1.Key Laboratory of Advanced Process Control for Light Industry, Jiangnan University, Wuxi 214122, China;Follow
Xiuli Zhang, 2.Wuxi Institute of Technology, Wuxi 214122, China;

Abstract

Abstract: A new shop rescheduling model driven by digital twin is proposed to solve the problems of disturbance cumulative rescheduling. A scheduling parameter updating method is proposed and a random probability distribution is used to describe the distribution of scheduling parameters to improve the accuracy of scheduling parameters. An implicit disturbance detection model is built based on Siamese Network using real-time data as input to realize the start time of rescheduling. The sample data for scheduling knowledge mining are extracted from the historical scheduling scenarios. Through the Pseudo-Siamese CNN, the mapping relationship between the Process state and machine state is obtained, which is applied to production online rescheduling. Simulation experiments show the feasibility of the proposed digital twin driven shop rescheduling model.

Recommended Citation

Wu, Dinghui; Zhang, Tongrui; and Zhang, Xiuli (2022) "Job Shop Rescheduling Under Recessive Disturbance Based on Digital Twin," Journal of System Simulation: Vol. 34: Iss. 3, Article 15.
DOI: 10.16182/j.issn1004731x.joss.21-0110
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss3/15

First Page

573

Revised Date

2021-05-18

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0110

Last Page

583

CLC

TP391.9

Recommended Citation

Dinghui Wu, Tongrui Zhang, Xiuli Zhang. Job Shop Rescheduling Under Recessive Disturbance Based on Digital Twin[J]. Journal of System Simulation, 2022, 34(3): 573-583.

Corresponding Author

Tongrui Zhang,ztrdaydayup@foxmail.com

DOI

10.16182/j.issn1004731x.joss.21-0110