Krishnamoorthi, K.S. (1986, ASQC) Bradley University, Peoria, IL
Often times we want to know the interrelationship among the four components of the Total Quality Cost so that we will be able to say what changes will occur in one when another is changed. For example we may want to know how much of a reduction in failure costs will result from a certain increase in prevention or appraisal cost. Similarly we may want to know by how much the prevention budget must be increased in order to accomplish a certain reduction in the failure costs. Even though the relationship among the component costs is as varied as there are companies keeping such cost systems, existence of some general pattern is hypothesized at least among similar companies doing similar business or producing similar products. Regression analysis is used to extract this relationship from data obtained from Q-Cost systems, and formulas are proposed as a rough approximation to describe this relationship. This model can be further refined, based on more data, to obtain more accurate models for specific industries such as: automobile, metals, pharmaceuticals etc. Availability of such formulas will be helpful in estimating benefits from Q.C. investments while justifying budget proposals, and in recognizing when optimal condition is reached. The relationship derived above is used in a simulation model that describes the cost system of a typical manufacturing company. The results from the simulator are used to show graphically how the unit cost of product changes with changes in investments in quality control.
Cost of quality (COQ)