Job-shop Scheduling Model for Machine State Fluctuations

MENG Biao; ZHAO Zhigang; GAO Jianli

doi:10.13976/j.cnki.xk.2020.0574

Volume 49 Issue 4

Aug. 2020

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INFORMATION AND CONTROL > 2020 > 49(4): 499-506, 512. > DOI: 10.13976/j.cnki.xk.2020.0574 CSTR: 32166.14.xk.2020.0574

MENG Biao, ZHAO Zhigang, GAO Jianli. Job-shop Scheduling Model for Machine State Fluctuations[J]. INFORMATION AND CONTROL, 2020, 49(4): 499-506, 512. DOI: 10.13976/j.cnki.xk.2020.0574

Citation:

MENG Biao, ZHAO Zhigang, GAO Jianli. Job-shop Scheduling Model for Machine State Fluctuations[J]. INFORMATION AND CONTROL, 2020, 49(4): 499-506, 512. DOI: 10.13976/j.cnki.xk.2020.0574

Citation:

MENG Biao, ZHAO Zhigang, GAO Jianli. Job-shop Scheduling Model for Machine State Fluctuations[J]. INFORMATION AND CONTROL, 2020, 49(4): 499-506, 512. DOI: 10.13976/j.cnki.xk.2020.0574

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Job-shop Scheduling Model for Machine State Fluctuations

1.
Key Laboratory of Fundamental Science for National Defense of Aeronautical Digital Manufacturing Process, Shenyang Aerospace University, Shenyang 110136, China
2.
AVIC Information Technology Co., Ltd., Beijing 100028, China
3.
Guide Infrared Group, Wuhan 430000, China

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Received Date: October 17, 2019
Revised Date: May 07, 2020
Accepted Date: January 20, 2020
Available Online: December 01, 2022
Published Date: August 19, 2020

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Abstract

Abstract

To improve the adaptability of the work plan to the machine state, in this study, we establish a job-shop scheduling model driven by quality data. To do so, we first use expert domain knowledge and relevancy analysis to mine the association rules hidden in the quality data and identify the machine-state fluctuations. Then, we construct a global scheduling performance indicator based on the loss time function to enable the scheduling model to make cycle optimization adjustments in response to machine-state fluctuations and to ensure the feasibility of the small-time-scale scheduling scheme. Finally, we verifie the effectiveness of the model by successfully changing the scheduling in a manufacturing enterprise in response to changes in the machine state.
- job shop scheduling problem(JSSP),
- data ming,
- machine state fluctuation,
- genetic algorithm

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References (18)

References

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