Process and Product Quality Optimization with Explainable Artificial Intelligence

In today's rapidly evolving technological landscape, businesses across various industries face a critical challenge: maintaining and enhancing the quality of both their processes and the products they deliver. Traditionally, this task has been tackled through manual analysis, statistical methods, and domain expertise. However, with the advent of artificial intelligence (AI) and machine learning, new opportunities have emerged to revolutionize quality optimization. This chapter explores the process and product quality optimization in a real industrial use case with the help of explainable artificial intelligence (XAI) techniques. While AI algorithms have proven their effectiveness in improving quality, one of the longstanding barriers to their widespread adoption has been the lack of interpretability and transparency in their decision-making processes. XAI addresses this concern by enabling human stakeholders to understand and trust the outcomes of AI models, thereby empowering them to make informed decisions and take effective actions.