Development of Automatic Balancing Application forFashion Company Using Artificial Intelligence

May Alrasheed; Mohamed Jmali; Thouraya Hamdi

doi:10.14502/tekstilec.66.2024009

Authors

May Alrasheed Department of Fashion and Textile Design, College of Arts and Design, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia Author https://orcid.org/0000-0002-9482-0944
Mohamed Jmali Department of Fashion and Textile Design, College of Arts and Design, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia; Textile Engineering Laboratory, University of Monastir, Monastir, Tunisia Author https://orcid.org/0000-0002-5148-1751
Thouraya Hamdi Department of Fashion and Textile Design, College of Arts and Design, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia Author https://orcid.org/0000-0002-7573-0695

DOI:

https://doi.org/10.14502/tekstilec.66.2024009

Keywords:

automatic balancing, fashion company, artificial intelligence, ant colony method

Abstract

Industrial companies aim to minimise production costs and improve product quality by analysing work organisation levels. Workshop scheduling and line balancing are essential in realising production plans, particularly in the fashion industry. Balancing systems must optimise precise criteria while sticking to constraints. Preserving balance needs precise parameters that align theoretical and practical production results. Manual methods overlook the balancing process, where managers rely on experience to prove balance and adjust parameters as needed. This article presents a creative automatic balancing application for fashion companies, leveraging artificial intelligence’s (AI) power. It focuses on utilising ant colony algorithms for optimal balancing. The results show the significance of these algorithms in attaining optimal balancing in production systems. The article highlights outstanding balancing results achieved through this approach, providing alignment with detailed criteria and constraints. The algorithm reliably distributes tasks among operators, improving overall productivity. Therefore, ant colony algorithms are perfect for manufacturers pursuing cost reduction, improved product quality and facilitated production processes. This article introduces an AI-based automatic balancing application for fashion companies. The ant colony algorithms achieve optimal balancing, improve inventory management and enhance productivity.

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