The second step will involve applying those levels within DesignLife to a virtual model of our product to obtain life estimates for both the average user (50 TH percentile) and the high-end user (90 th percentile). The first step will involve fitting a distribution to existing customer usage data to obtain the 50 th and 90 th percentile usage levels. In this article, we will combine the analysis capabilities of ReliaSoft Weibull++ and nCode DesignLife to perform a two-step analysis to estimate product life. In some cases, usage estimation is sufficient, however, collecting actual customer usage data allows for more accurate predictions. In order to meet these requirements, it is important to understand how customers use the product. As cost effectiveness and time to market have become higher priorities during the developmental process, more and more companies are turning to Computer Aided Engineering (CAE) to achieve these goals while ensuring that next generation products continue to meet customer expectations.
