Production Scheduling Optimization of Garment Intelligent Manufacturing System Based on Big Data

Author:

Sun Ning1ORCID,Cao Botao2ORCID

Affiliation:

1. College of Art and Design, Shaanxi University of Science and Technology, Shaanxi, Xi’an, China

2. College of Mechanical & Electrical Engineering, Shaanxi University of Science and Technology, Shaanxi, Xi’an, China

Abstract

In order to improve the efficiency of cloth laying and cutting integrated production process, this article proposes a method of optimal scheduling of cloth laying and cutting garment production system process based on big data and genetic algorithm. The chromosomes in the algorithm are expressed by real strings. The method of bit string crossover and mutation is used to solve the premature problem of the algorithm. The experimental results show that the actual cutting time of the plan is 736 min, and the total idle time is 113 min. The idle time occurs in processes 25, 28, 34, 35, and 31, respectively. The cutting time of the plan arranged by the genetic algorithm is 627 min, and there is no idle time. Conclusion. This method can effectively solve the optimal scheduling problem of the cloth laying and cutting production process.

Funder

Key Project of International Science and Technology Cooperation Program for Shaanxi Province

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Business intelligence adoption among small apparel retailers in KwaZulu-Natal;International Journal of Research in Business and Social Science (2147- 4478);2023-09-14

2. Retracted: Production Scheduling Optimization of Garment Intelligent Manufacturing System Based on Big Data;Computational Intelligence and Neuroscience;2023-08-02

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