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Volume 17, Issue 1
Balance Study of Clothing Single-Piece Production Line Based on Dual-Population Genetic Algorithm

Ming-Ming Yang, Long Wu, Jing Qi, Bo-An Ying & Yue Wang

Journal of Fiber Bioengineering & Informatics, 17 (2024), pp. 51-60.

Published online: 2024-11

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  • Abstract

Currently, line production is the mainstream production method for various clothing enterprises. Therefore, optimising and improving the production line plays a crucial role in promoting the development of manufacturing enterprises. To solve the problems of unbalanced operation time and low production line balance rate of each workstation of the garment sewing production line, a multi-objective optimisation mathematical model with the minimum smoothing index and the largest production line balance rate was established, and the dual-population genetic algorithm was designed in the MATLAB environment. The jeans (front piece) were used as an example to be simulated and verified in simulation software. Achieve load balancing at workstations, save production costs, and eliminate overproduction between jobs. The research results show that the smoothness index of the optimised production line has been reduced from 20.89 to 8.43, and the production line balance rate has been increased from 77.57% to 89.06%, which meets the requirements of enterprise process planning and can deliver on time. This verifies that the model proposed in this paper can effectively solve the production balance problem of a single clothing production line.

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@Article{JFBI-17-51, author = {Yang , Ming-MingWu , LongQi , JingYing , Bo-An and Wang , Yue}, title = {Balance Study of Clothing Single-Piece Production Line Based on Dual-Population Genetic Algorithm }, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2024}, volume = {17}, number = {1}, pages = {51--60}, abstract = {

Currently, line production is the mainstream production method for various clothing enterprises. Therefore, optimising and improving the production line plays a crucial role in promoting the development of manufacturing enterprises. To solve the problems of unbalanced operation time and low production line balance rate of each workstation of the garment sewing production line, a multi-objective optimisation mathematical model with the minimum smoothing index and the largest production line balance rate was established, and the dual-population genetic algorithm was designed in the MATLAB environment. The jeans (front piece) were used as an example to be simulated and verified in simulation software. Achieve load balancing at workstations, save production costs, and eliminate overproduction between jobs. The research results show that the smoothness index of the optimised production line has been reduced from 20.89 to 8.43, and the production line balance rate has been increased from 77.57% to 89.06%, which meets the requirements of enterprise process planning and can deliver on time. This verifies that the model proposed in this paper can effectively solve the production balance problem of a single clothing production line.

}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbim03071}, url = {http://global-sci.org/intro/article_detail/jfbi/23520.html} }
TY - JOUR T1 - Balance Study of Clothing Single-Piece Production Line Based on Dual-Population Genetic Algorithm AU - Yang , Ming-Ming AU - Wu , Long AU - Qi , Jing AU - Ying , Bo-An AU - Wang , Yue JO - Journal of Fiber Bioengineering and Informatics VL - 1 SP - 51 EP - 60 PY - 2024 DA - 2024/11 SN - 17 DO - http://doi.org/10.3993/jfbim03071 UR - https://global-sci.org/intro/article_detail/jfbi/23520.html KW - Dual-population genetic algorithm, Balance optimisation, Garment sewing line, Simfactory software. AB -

Currently, line production is the mainstream production method for various clothing enterprises. Therefore, optimising and improving the production line plays a crucial role in promoting the development of manufacturing enterprises. To solve the problems of unbalanced operation time and low production line balance rate of each workstation of the garment sewing production line, a multi-objective optimisation mathematical model with the minimum smoothing index and the largest production line balance rate was established, and the dual-population genetic algorithm was designed in the MATLAB environment. The jeans (front piece) were used as an example to be simulated and verified in simulation software. Achieve load balancing at workstations, save production costs, and eliminate overproduction between jobs. The research results show that the smoothness index of the optimised production line has been reduced from 20.89 to 8.43, and the production line balance rate has been increased from 77.57% to 89.06%, which meets the requirements of enterprise process planning and can deliver on time. This verifies that the model proposed in this paper can effectively solve the production balance problem of a single clothing production line.

Yang , Ming-MingWu , LongQi , JingYing , Bo-An and Wang , Yue. (2024). Balance Study of Clothing Single-Piece Production Line Based on Dual-Population Genetic Algorithm . Journal of Fiber Bioengineering and Informatics. 17 (1). 51-60. doi:10.3993/jfbim03071
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