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This study explores the contrasting approaches to robotics integration in manufacturing processes employed by Bangladesh and the United States. By examining three distinct case studies – garment manufacturing, high-tech manufacturing, and agriculture – the analysis reveals significant variations in adoption rates, technological focus, and strategic implementation. These disparities stem from each nation's unique economic landscape, industrial structure, and labour market dynamics. Bangladesh, characterised by low-wage labour in garment manufacturing, cautiously incorporates automation technologies like Sewbots to enhance long-term efficiency and product quality. Conversely, the U.S. garment industry strategically utilises robots for specialised tasks in niche markets, seeking a competitive advantage through precision and design innovation. In high-tech manufacturing, the U.S. leverages readily available commercial solutions and a skilled workforce for extensive robotics adoption, ensuring precision and consistency in complex processes. Bangladesh acknowledges these benefits but faces challenges related to cost and skills gaps, necessitating capability building and strategic partnerships for future integration. Both countries recognise the high potential of robotics in agriculture; however, the U.S. combats labour shortages and enhances efficiency through advanced solutions like farming robots and UAVs. Bangladesh explores automation to increase yield and reduce manual labour dependence. This comparative analysis contributes to understanding global manufacturing and supply chain optimisation by highlighting the diverse factors influencing robotics adoption across nations. The research suggests a future where the U.S. refines and expands advanced robotics use. Bangladesh strategically invests in and develops its workforce, potentially forming partnerships to integrate robotics into high-tech manufacturing and agriculture. As robotics and automation technologies evolve, both countries stand to benefit by embracing these advancements while navigating the challenges to ensure a smooth transition toward a more automated and efficient future for their manufacturing sectors.
A Sat, study studied this question.