Warranty Return Rate Prediction Based on Laboratory Step-stress Testing Data

• Main Authors: Yu, I-Hsien, 余奕賢
• Other Authors: Tseng, Sheng-Tsaing
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/r9sbvz

碩士 === 國立清華大學 === 統計學研究所 === 106 === Quality-assurance liability of manufacture or sale matter for a specified period of time is known as the warranty period. In the market competition environment, manufacturers often adopt a warranty policy to attract their potential consumers. It is likely to increase the manufacturing and operation costs substantially if the return rate under a warranty period cannot be predicted precisely. Therefore, “how to predict the product’s return rate within the warranty period precisely” is a challenging issue to the manufacturers. The goal of thesis is mainly on the return rate prediction of information and communication technology (ICT) products, where the laboratory quality testing data are used to predict the product’s return rate under the warranty period. Most of existing literature, the step-stress laboratory testing data are recorded by a discrete-type “go/no go” pattern, while the return rate is collected by a continuous-type measurement. Hence, the physical meanings between laboratory and field data are not easy to explain due to two different sources of data. To overcome this difficulty, this thesis introduces a logistic model to transform attribute-type “go/no go” data into a continuous-type data. In addition, a hierarchical empirical Bayes procedure is also adopted to provide a better utility of all product’s information. Finally, from a real case study, it demonstrates that the proposed procedure has a better prediction performance, in comparing with the conventional approach.