Reducing Complexity in Exporting RMG Products Using Artificial Intelligence in Bangladesh

Abstract

The Ready-Made Garments (RMG) sector in Bangladesh is one of the primary contributors to the nation’s economy, holding the position as one of the world’s largest garment exporters. The industry faces significant challenges in maintaining its competitive edge due to inefficiencies in supply chain management (SCM), logistical issues, and quality control inconsistencies. This study investigates the potential of integrating Artificial Intelligence (AI) and Internet of Things (IoT) into the RMG supply chain to address these challenges. The proposed approach focuses on optimizing shipping routes using AI-driven methods, enhancing real-time tracking and quality control with IoT devices, and leveraging predictive analytics to streamline operations. Through AI-based route optimization, cost and time reductions are achieved using advanced algorithms like A* search guided by Convolutional Neural Networks (CNNs). The study also highlights stakeholder attitudes toward AI adoption in the sector, with most respondents supporting its integration despite concerns regarding workforce adaptability and implementation costs. The findings suggest that incorporating AI and IoT into SCM could significantly enhance operational efficiency, improve product quality, and reduce export complexities. The study concludes with recommendations for strategic AI adoption, emphasizing workforce reskilling, data security, and ethical considerations for sustainable growth in Bangladesh’s RMG sector.