Abstract
<jats:p>With the global operating environment becoming rapidly more volatile, uncertain, complex, and ambiguous, supply chain resilience has risen to the top of the strategic agenda for organizations that want to not only survive but thrive amid disruptions from economic turmoil and digital transformation, and in general, rapid change. This book aims to provide an intelligible and powerful intelligent, adaptive, and human-centric supply chain as well as manufacturing systems enabled by emerging digital technologies. The move from Industry 4.0 to Industry 5.0 represents an important departure from the automation and connectedness of 4.0 to a next level of sustainability, resilience, and collaboration between people and machines. In this context, artificial intelligence (AI) and machine learning (ML) have become transformational enablers of supply chain resilience, providing predictive capabilities, autonomous decision-making, and data-driven optimization for intricate manufacturing networks. This work offers an exhaustive discussion on how AI and ML can be incorporated to design, manage, and operate supply chains that are not only more resilient but also better able to predict, withstand, and recover from the consequences of disruptions. Taking the reader step-by Step through the strategic journey of mining industry, and integrative coverage on key topics from risk assessment, decision making, inventory optimization, logistics to anomaly detection and sustainability, this work covers a gamut of areas, utilising technology, applications, and outcomes. We’ve tried to offer the best of theory and practice, both concepts and building-block approaches. The individual chapters are based on extensive research while being easily accessible to both practitioners and all those interested in the junction of AI/ML and supply chain management/smart manufacturing. We trust this book will be a useful reference guide for those looking to transform supply chain, digitally, build a sustainable, resilient and the future ready manufacturing ecosystem.</jats:p>