A study based on using Pearson distribution family on reliability analysis

In everyday life, prodcucts or systems that we use, wearing out day by day and this situation causes fails of protucts and systems. It is very important for manufacturers to forecast this kind of fails. With that perspective reliability analysis is carried out to determine the potential lifetime of products. As a part of this analysis, products are tests under specific environmental conditions and their test results are examines to determine the products failure time. By this way, products lifetime and whether they are meeting of customer expectations or not can be determined. Failure time?s distribution is the basis of the reliability analysis. While choosing the proper distribution, some statistical tools can be used. Cumulative distribution, reliability function, hazard function, mean residual life, variance residual life are the most common tools to determine proper distribution in reliability analysis. By the way failure distributions can be characterized by using relations between these functions. Pearson Differantial Equation System includes many distributions which are also used in reliability analysis commonly. Because of this reason it has a very important place in reliability analysis. In this study, Pearson Differantial Equation System's cubic denominator structure which derives asymmetric distribution will be handled. Then asymmetry measures will be examined by using conditional moments for that structure. Keywords: Reliability Analysis, Pearson Differantial Equation System, Conditional Moment