Economic models and process quality control

Abstract

Quality is an important business strategy in the economic and technological environment of today. To achieve high product quality, it is important to take explicit account of the cost of quality, and to use this cost as another management control. A new direction for achieving a cost‐effective quality management system is to design statistical process controls so as to directly incorporate quality costs. This paper discusses the major approaches to the economic design of statistical process controls, and compares several different model formulations. The practical implication of these techniques is stressed. In particular, two economic models of the chart are presented: a full economic model requiring a user‐specified process and nine cost parameters, and a semi‐economic model using five user‐specified parameters. Both of these could serve as approaches to reducing the total cost of process control. Because of its simplicity in application the semi‐economic model should gain greater acceptance by practitioners for the design of process control techniques.

Redefining quality in terms of value, risk and cost: a literature review

“…For example, the work of "The Student" (1908) within Guinness; Fisher's agricultural experimentation (Fisher, 1937); Shewhart's work within Bell Telephone laboratories (Shewhart, 1930) and Dodge and Romig's (1929) development of acceptance sampling plans. In keeping with early industrial development, most of these developments were economically motivated, and "economic" is a commonly occurring motivation within writings on statistical QC (Montgomery and Storer, 1986;Woo et al, 1986;Rowland and Kazmer, 1997). The purpose of using statistical approaches was to introduce less expensive sampling-based methods to replace batch inspection, complete on-line control or too many wasteful improvement trials.…”