Explainable Artificial Intelligence (XAI) in Lean Manufacturing: Transparent and Trustworthy Machine and Deep Learning for Continuous Process Improvement - Tin-Chih Toly Chen

This book systematically reviews XAI techniques and introduces how these XAI techniques can be systematically applied to lean manufacturing, including methodology, system architecture, and applications. So far, artificial intelligence (AI) technologies have been widely used in the field of lean manufacturing for cycle time reduction, capacity balancing, transportation planning, demand and sales forecasting, just-in-time (JIT) control, bottleneck detection, etc. Some applications of AI technologies in lean manufacturing are not easy to understand or communicate, especially for managers or engineers 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 lean manufacturing, there are few systematic introductions, including methodology, system architecture, and case studies. Relevant references, examples, or cases are also used as supporting evidence.