Life Prediction based on Degradation Amount Distribution using Composite Time Series Analysis

This paper presents a life prediction method to predict Degradation Amount Distribution ( DAD) of products using a composite time series modeling procedure based on degradation data. Product DAD data are treated as composite time series and described using composite time series model and utilized to predict long-term trend of degradation. A degradation test is processed for a certain electronic product and degradation data are collected for life prediction. A comparison between the predicted DAD using composite time series analysis and the predicted DAD using regression analysis of the electronic product is processed and the results show that the DAD prediction of the product using composite time series analysis is more effective than regression analysis. (C) 2012 Published by Elsevier B. V. Selection and peer review under responsibility of Information Engineering Research Institute