This book systematically reviews XAI techniques and introduces how these XAI techniques can be systematically applied to SCM, including methodology, system architecture, and applications. Relevant references, examples, or cases are also used as supporting evidence.
So far, artificial intelligence (AI) technologies have been widely used in the field of supply chain management (SCM) for supply chain design, production and transportation planning, demand and sales forecasting, cell manufacturing, just-in-time (JIT) control, etc. Some applications of AI technologies in SCM are not easy to understand or communicate, especially for supply chain stakeholders with insufficient background knowledge of AI, which undoubtedly limits the practicality and credibility of these applications. To solve this problem, explainable artificial intelligence (XAI) is considered as a feasible strategy. However, most of the relevant research results are scattered in various journals or conference proceedings, and there is an urgent need to systematically integrate these results. In addition, although there have been many reviews on the possible applications of XAI in SCM, there are few systematic introductions, including methodology, system architecture, and case studies. This book answers this need.
Table of Contents:
Explainable Artificial Intelligence (XAI) Applications in Supply Chain Management (SCM).- XAI applications in production planning and job scheduling for supply chains.- XAI applications in facility location planning and supply network optimization.- XAI applications to manage supply chain risks and resilience.
About the Author :
Dr. Chen has published papers on XAI applications in journals such as Expert Systems and Applications, Applied Soft Computing, International Journal of Advanced Manufacturing Technology, Complex & Intelligent Systems, Digital Health, etc. He also authored several books on XAI, including “Explainable Ambient Intelligence (XAmI)—Explainable Artificial Intelligence Applications in Smart Life”, “Explainable Artificial Intelligence in Manufacturing: Methodology, Tools, and Applications,” “Explainable and Customizable Job Sequencing and Scheduling: Advancing Production Control and Management with XAI” for Springer. Dr. Chen is the co-editor of Supply Chain Analytics, an Elsevier journal. He is also an IET fellow and AIAT fellow.
