Over the past decade, quality-related fault detection and diagnosis, as an important branch of multivariate statistical process monitoring, has become a critical component of industrial process monitoring. As one of the pioneering research teams in this field, we have achieved significant research outcomes. In particular, we have proposed many effective methods in nonlinear quality-related fault modeling, detection, isolation, and root cause analysis. In this chapter, we will provide a detailed summary and review of these methods and validate them through simulations using numerical examples and industrial case studies. We hope this will serve as a valuable reference for future research.