Reinventing production quality on a nano‐granularity level

Purpose – This paper aims to resolve the phenomenon of the gaps between plentiful data and useful information for many manufacturing companies. Design/methodology/approach – By introducing Bayesian dynamic sampling processes, a quality process control cycle will be achieved through the sequential linkages between the involved entities; namely, user's requirement statement, target specification document, database management, and data collection. Findings – For commercial product‐development processes, the requirement for continuous product improvement can be done by adopting a Bayesian sequential procedure. As such, industry practitioners can be able to justify whether the manufactured products have been done successfully in fulfilling target specification documents on the nano‐scale granularity level. The unsatisfactory manufacturing cases may indicate the situations of the necessity for remedy treatments of component‐wise re‐engineering processes incrementally, or for radical innovation of creating new markets through new functional capacity, based on new technical generation of the target system. Originality/value – This paper proposes managerial quality strategic decision guidelines which may be served as an incentive for stimulating further practical industrial case studies, especially on the area of quality products assurance.