What is it about?

The control of critical to quality (CTQ) variables can be done in a given process or in a downstream process. Companies must define the control method: statistical process control (SPC) or 100% inspection. However, operational constraints can influence its definition. Overall, the control for a given process can be excessive or insufficient, resulting in a non-optimal quality cost. This paper discusses the relevance of different factors that can influence the selection of a quality control method. Then, it assesses the likelihood of companies having reliable data on such factors and it is proposed a model to minimize the total quality costs of a given process. The model uses information like SPC efficiency in detecting potential process variations, false alarms, measurement system error, inspection cost, repair cost and the cost of passing defective units to the next process. The quality control method can be updated whenever recent data on the 18 parameters are available. Through an application example, quality control mechanisms are selected to minimize quality costs.

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Why is it important?

The application of this method can make companies more competitive and more sustainable.

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This page is a summary of: Integrating quality costs and real time data to define quality control, Procedia Manufacturing, January 2019, Elsevier,
DOI: 10.1016/j.promfg.2020.01.125.
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