To achieve quality improvement in manufacturing environments, the design of experiment (DOE) and Taguchi methods are two efficiency approaches to address such problems. Applying those methods to resolve quality improvement frequently focuses on the measurable quality response (or quantitative response). However, the complexity of products or processes is gradually increased and due to the limitation of measuring equipment, the quality response could not be directly measured. Visual inspection or measurement is then used to judge the quality for nonmeasurable response (or qualitative response). Basically, for assessing the quality of a qualitative response, it is initially divided into several classes or ordered categories. As for customers' requirements gradually changing and applications' flexibility gradually increasing, a dynamic structure for this process will be another important consideration for manufacturers. That is, it causes the work of quality improvement to be dynamically analyzed. Dr. Taguchi had proposed a dynamic method to analyze such issues. However, only several studies focused on quality improvement of a qualitative response during the static characteristic. Parameter optimization approaches were seldom proposed to address quality improvement of a qualitative response with the dynamic characteristic. Therefore, in this study, we proposed an integrated parameter-optimization approach to resolve quality improvement of a qualitative response with dynamic characteristics. An illustrative example, quality improvement of lead twist during the stamping process for lead frame manufacturing at Science-based park in Taiwan, is employed to demonstrate the effectiveness of the proposed approach.
|Number of pages||11|
|Journal||International Journal of Advanced Manufacturing Technology|
|State||Published - 1 Jun 2005|
- Dynamic characteristic
- Parameter optimization
- Qualitative response
- Quality improvement