Data-Driven Innovation in Supply Chains and Manufacturing: From Predictive Analytics to Natural Language Processing

This book explores how modern technologies-especially data analytics, machine learning (ML), and the Internet of Things (IoT)-are transforming supply chain and manufacturing operations.Bridging academic research and industrial practice, this book presents data as a strategic asset driving agility, efficiency, and resilience. Structured around four themes, it covers:Foundational analytics and optimizationPredictive and prescriptive analytics for proactive decision-makingReal-time IoT data for workflow monitoring and controlDigital Twins and Natural Language Processing (NLP) for modeling andinteractionChapters include mathematical modeling, case studies, and implementation frameworks, with coverage spanning stochastic forecasting, reinforcement learning, anomaly detection, and semantic parsing of logistics documentation. Key benefits include its emphasis on integrated intelligence-blending ML, IoT, and simulation for real-time, predictive insights.It also highlights scalability across in