Hakeem Owolabi

This chapter examines the use of artificial intelligence, data analytics and other digital technologies in the management of the supply chain decision-making. The study highlights the challenges faced by supply chain managers and how the application of AI and data analytics can help in making better and more informed decisions with respect to sustainability. Data analytics, AI techniques, such as machine learning, natural language processing and other digital technologies that include Internet of Things, Robotics and Cloud computing and their applications to different areas of supply chain management, such as demand forecasting, inventory management and logistics optimisation are discussed. Some of the challenges (initial cost of physical and cloud resources, change management, ethical and legal-related issues) that the supply chain managers need to put into consideration when adopting these technologies are also presented. The chapter concludes that continuous data collection and storage across all the stakeholders in the supply chain must be ensured to enable transparent and efficient use of AI algorithms to support quick and timely supply chain decision-making.

This book chapter explores the challenges associated with adopting Industry 4.0 technologies in the context of achieving a sustainable manufacturing supply chain. The chapter highlights both general and technology-specific hurdles that organizations encounter when implementing Industry 4.0, such as dealing with data accumulation and compatibility issues with legacy systems, data management complexities, data protection, privacy and cyber attack risks, cost considerations, and workforce upskilling and transition. The chapter emphasizes the importance of addressing these challenges to enable the effective incorporation of Industry 4.0 technologies for sustainability goals. It provides insights and recommendations for mitigating these challenges, including prioritizing sustainability considerations during technology selection and implementation, emphasizing energy efficiency and environmental impact assessments in technology design and deployment, incorporating ethical frameworks and guidelines for data usage, privacy, and fairness in AI and IoT systems, encouraging collaboration among stakeholders to develop industry standards and best practices for sustainable technology adoption, among a few others. By proactively addressing these challenges, organizations can leverage the transformative potential of Industry 4.0 while driving sustainability in their manufacturing supply chain.