The Advantages of SPC Models in Quality Control Processes

Abstract

Product quality, which is positively associated both with firms’ income and with their expenditures, is a crucial factor in competition among firms. Accordingly, the field of quality control and process management has developed substantially over the last decades. In the past, the leading approach in quality control was sampling across the product line and classifying samples as either “good†or “badâ€. If a sample was classified as “badâ€, the entire batch would be thrown out. This binary approach is problematic, as it might lead to wastage. This article will attempt to show, using a mathematical control model, that process management based on statistical data can improve quality control processes by saving time and money, and can ultimately improve the quality of the final product.

In what follows we first review several common approaches to quality and process control; these approaches are not based on mathematical modeling. We then introduce our approach, called statistical process control. On the basis of this approach, we develop a mathematical model with the objective of minimizing the expected cost per unit of time in the manufacturing process. We then present a numerical example of our method.