The course objective is to introduce basic theory and the most common tools for statistical process control, which enable efficient monitoring and minimization of variability in the production processes and thereby improving the quality of products. The main areas are descriptive statistics and probability (data management and visualization, numerical descriptions, correlation and regression, basic probability, random variables and probability distributions), statistical inherence (statistics and sampling distributions, estimations of parameters, hypothesis testing), statistical process control (basic tools and philosophy of statistical process control, fundamentals of control diagrams, control charts for variables, control charts for attributes, process capability ratios), and visual quality control (cameras, illumination and optical systems, basic tools for image processing and analysis, examples of machine vision systems for visual quality control).
