Reducing Supply Chain Bottlenecks Using Generative AI and Industry 4.0 Technologies

Abstract

Supply-chain bottlenecks are chronic operational sources of constraint that inhibit throughput and reliability in worldwide manufacturing and distribution. The traditional systems of management are typified by reacting processes of planning and too much depend on the past trends of data and a lack of visibility and predictive intelligence. The integration of Generative AI with Industry 4.0 cyber-physical infrastructure addresses fundamental gaps in constraint detection, scenario generation, and autonomous response execution. Digital-twin models generate simulations of physical assets, and can be continuously simulated and optimised. Constraining based algorithms like mixed integer programming, reinforcement learning and genetic optimisation are algorithm models that detect bottlenecks and formulate solutions that are doable under competing options. The autonomous operations frameworks achieve the light out supply-chains using robotics, computer vision and cyber-physical coordination structures. The unstructured data on suppliers communications, financial news, weather projections, and regulatory announcements is processed by proactive risk-mitigation capabilities that identify the occurrence of disruptions in advance before they have the opportunity to impact operations. The enterprise integration architectures indicate the seamless integration of generative AI reasoning systems with operational platforms by connecting between them via API-based interfaces, event-sourced messaging, and the coordination of microservices. Domain application demonstrates the visible reduction of bottlenecks in manufacturing operations, logistics, procurement process and retail distribution channel. Such convergence represents a radical change of reactive problem-solving in favor of proactive constraint elimination via the use of cognitive reasoning and infrastructure interconnection. The supply-chains in healthcare during a pandemic and the problem of sustainable manufacturing are the examples of the efficacy of the combined digital technologies to create operational resilience and adaptive capacity.