No abstract

No abstract

No abstract

Quality investment decisions are complex and interrelated, with added uncertainties associated with the many``unknown and unknowable'' costs (such as the value of an unhappy customer). However, existing cost of quality models are overly simplistic. In order to improve quality investment decisions, this paper thoroughly reviews the cost of quality literature, and then proposes a multi-level model tracing the impact of prevention and appraisal program investments on key performance results such as sales revenues, manufacturing and inventory costs, and quality failure costs. Several sub-sections of this framework are developed and described in detail with analytical models. In particular, the variance reduction sub-model expands Taguchi's Loss Function for estimating hidden external failure costs by linking variance and process mean settings to reliability. This paper proposes analytical models to quantify the effects of quality improvement investments on tangible measures of firm performance.

No abstract