Proceedings of the 2nd International Conference on Art Design and Digital Technology, ADDT 2023, September 15–17, 2023, Xi’an, China

Research Article

Optimization of Shirt Pocket Manufacturing Process Based on Ant Colony Algorithm

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  • @INPROCEEDINGS{10.4108/eai.15-9-2023.2340860,
        author={Wei  Wang},
        title={Optimization of Shirt Pocket Manufacturing Process Based on Ant Colony Algorithm},
        proceedings={Proceedings of the 2nd International Conference on Art Design and Digital Technology, ADDT 2023, September 15--17, 2023, Xi’an, China},
        publisher={EAI},
        proceedings_a={ADDT},
        year={2024},
        month={1},
        keywords={ant colony algorithm; shirt pocket; process parameter optimization; pheromone; cooperation and competition},
        doi={10.4108/eai.15-9-2023.2340860}
    }
    
  • Wei Wang
    Year: 2024
    Optimization of Shirt Pocket Manufacturing Process Based on Ant Colony Algorithm
    ADDT
    EAI
    DOI: 10.4108/eai.15-9-2023.2340860
Wei Wang1,*
  • 1: Anqing Vocational & Technical College
*Contact email: ws246236@126.com

Abstract

Based on the ant colony algorithm, this paper explores its application in optimizing shirt pocket manufacturing process parameters. As one of the critical processes in garment manufacturing, the layout and stitching process of shirt pockets has an essential impact on the appearance and quality of products. Because the traditional experience makes it difficult to meet the optimization needs of the production process, we introduce the ant colony algorithm into the process optimization field to simulate the cooperation and competition behavior of ants in searching for food and seek the best bag production scheme. In this study, experiments were designed to collect bag-making data under different parameters, and an ant colony algorithm was used to optimize. The results show that the ant colony algorithm has remarkably optimized shirt pocket manufacturing process parameters. By comparing the ant colony algorithm with the traditional method, we verify the superiority of the ant colony algorithm in optimizing process parameters and provide a new idea and plan for improving the shirt-making process.