Abstract
Industry 4.0 has revolutionized supply chain management and logistics through a concentration on automation, data interchange, and smart technologies. Autonomous Mobile Robots (AMRs) is advanced robotic applications in industry 4.0 which can provide flexibility, efficiency, and scalability in supply chain management. So, the integration of AMRs in advanced manufacturing, could provide cost-effectiveness production, and consumer satisfaction. AMRs can minimize delays by lowering reliance on humans, and guaranteeing real-time flexibility in response to customer demand fluctuations. Their unmatched flexibility, adaptability, and scalability in warehouse tasks like picking and sorting are made possible to function without predetermined routes and human involvement. Furthermore, by maximizing the usage of resources and minimizing negative environmental effects, AMRs play a crucial role in promoting resilience and sustainability. Thus, challenges from e-commerce expansion, sustainability concerns, and supply chain disruptions can be managed by using ARMs in part manufacturing. This review explores the role of AMRs in logistics and supply chain management within the industry 4.0 paradigm. Key topics in the study are ARMs integration with IoT, AI, and digital twins; optimization of operations such as order picking, inventory management, and last-mile delivery. Also, challenges and difficulties such as interoperability, cybersecurity, interoperability, regulatory constraints and high initial investment are critically analyzed in order to be analyzed and managed along with potential strategies. The review also addresses future research directions, focusing on human-robot collaboration, swarm robotics, advanced human-robot collaboration, fleet optimization, and the development of standardized protocols of robotic applications and the transition of ARMs to Industry 4.0. As a result, by analyzing the applications of AMRs in logistic and supply chain managements of production processes, novel models of robotic applications in advanced manufacturing processes of industry 4.0 can be proposed and discussed in terms of productivity enhancement of part manufacturing.