Cost/benefit models for investments in quality improvements.

摘要

Industrial organizations are always struggling to improve product and process quality, often with the installation of Continuous Quality Improvement (CQI) programs. The intuitive appeal of CQI, coupled with some widely advertised success stories, has led to its widespread implementation by firms with the goal of improving performance. These implementation efforts, unfortunately, have not always met with success. An objective way of measuring the impact of CQI programs through the development of models for predicting the tangible benefits of CQI investments is required.; The benefits of CQI investments are very hard to predict because of the many complexities involved in production management. One set of activities do not yield the same results for every company. As a result, a wide variety of measures of the outputs of CQI investments need to be quantified, and it would be helpful if these could be expressed in some common metric. Relatively few authors have presented quantitative models in this area, and in those cases where quantitative models do exist, they tend to focus on only one or two measures of quality.; In this research, analytical models will be developed to quantify the effects of investment in quality improvement projects on tangible measures. This approach is unique due to the hierarchical structure used in studying the effect of investments. This structure illustrates the impact of investing in quality programs at six different levels. On the first level, investment options in quality are presented in terms of two main quality cost groups, namely prevention costs and appraisal costs. The specific investment opportunities are considered on the second level. The third level indicates items that are immediately effected by the investments in these quality initiatives, such as variances and the means of quality characteristics of the components and the final product, the manufacturing throughput time, the product development time, repetitive inspections and the measurement errors. Proportion of rejects and reliability, which affect internal and external quality costs, are included on level four. The fifth level involves the direct benefits of CQI investments, which can be classified as either cost reducers or revenue enhancers. The sixth level groups the items on level five into different categories such as internal and external failure costs, manufacturing costs, inventory costs, delay/tardiness costs, and revenue enhancement.; The final result of this research will include aggregate cost models which will capture the return on investment in CQI projects in one common metric. These cost models enable users to include a much wider range of cost elements than traditional models. The final models will be used in industry as a practical tool to predict the benefits of quality investments before they are made, and as a means to justify investments in CQI projects. The resource allocation model can enable industry to optimize CQI investments.