SPC (Statistical Process Control)  is the part of industrial statistics that deals with monitoring data streams in order to timely detect changes (the word control in the name is a historical misnomer because it leads to confusion with feedback control; a better name should have been Statistical Process Monitoring). The field originated in the manufacturing industry. In this talk, we give a brief overview of the standard procedures in SPC, applications fields and position SPC in the wider data science context. We will discuss an industrial case study with wind turbines, that illustrates the methodological challenges in the field. The wind turbine case study arose in a maintenance context. We will discuss benefits of including SPC in predictive maintenance strategies and highlight some methodological challenges and how they could fit within the PrimaVera context.

The slides are available here.