Optimizing supply chain operations with machine learning at scale

Kiran, Sarat (2025) Optimizing supply chain operations with machine learning at scale. World Journal of Advanced Engineering Technology and Sciences, 15 (1). pp. 367-373. ISSN 2582-8266

Supply chain management is undergoing a transformative evolution through the integration of machine learning and advanced data engineering practices. This comprehensive article examines how modern organizations are leveraging ML technologies to enhance operational efficiency, improve demand forecasting, and optimize resource utilization across their supply chain networks. The article explores the implementation of digital twins, autonomous planning systems, and blockchain integration for enhanced transparency and risk management. Through multiple case studies spanning retail, manufacturing, and healthcare sectors, this article demonstrates how ML-driven solutions are revolutionizing traditional supply chain practices. The article covers the technical infrastructure requirements, real-world implementation challenges, and future directions in supply chain automation, providing insights into both the opportunities and obstacles organizations face in their digital transformation journey.