| dc.description.abstract | With advances in technology, and enhancement of the living level, the demand for multi-functional, thin, and light-weighted products increases day by day. It drives the electronic manufacturing technology to improve continuously, and also makes packaging technology face great challenges. Packaging companies of the electronic components require lot of money to invest in R & D, and time to resolve quality issues arising from the new electronic components with advanced technology. In order to reduce the development cost and the time of the product development, effective methodology is needed to enhance the ability of product development of R & D.
Based on our experiences on the electronic packaging products, this study uses the techniques of data mining with consideration of product structures, process conditions, and materials of the packaging products to build prediction models, decision tree, neural network, and logistic regression models, of reliability tests of packaging products. Through this study, we will find more accurate prediction models, uses these models to find the important variables that influence the test result most, and then find the optimal level of these variables. This study will be able to help to increase staff efficiency and reduce the cost of human and material to meet the effect of reducing the cost in R & D and the time of product development, and enhance the ability of the product development and the competitiveness of the enterprise.
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