Reliability prediction of electronic boards by analyzing field return data

In this study, we perform field return data analysis of electronic boards. We cooperate with one of the Europe's largest manufacturers and use their well-maintained data with over 1000 electronic board failures. We follow two steps that are filtering the return data and modeling the filtered data with probabilistic distribution functions. In the first step of filtering we propose a new technique to eliminate improper data, correlated to incomplete and poorly collected data, from the whole field return data. In the second step of modeling, we use the filtered data to develop our reliability model. Rather than conventionally using a single distribution for all service times that does not accurately model the substantial changes of the electronic boards reliability performance over time, we use different distributions for different service time intervals. In order to determine the distributions we propose a technique that deals with forward and backward time analysis of the data.