Quality control is often associated with strict rules, detailed calculations, and intimidating statistical language. This perception discourages many practitioners from fully engaging with probabilistic methods, even though they already rely on them implicitly. This report presents probabilistic quality control in a concept-driven, non-mathematical way. By focusing on intuition, examples, and practical decision-making, it demonstrates how probability helps manage uncertainty rather than complicate it. The aim is to make probabilistic quality control accessible, usable, and free from unnecessary anxiety.
Ali Darijani (Thu,) studied this question.