Abstract
In this paper, we focus the failure rate of components which compose of products and are the dominant cause of unsafe incidents of the product. We analyzed data base of NITE reports to figure out component failure rate through electric fan incident cases. The failure rate resides in accidental failure mode and wear-out failure mode. We propose a method to derive an equivalent distribution of probability of failure rate by using the limited number of incident case samples. Failure rates at a certain time is shifted to an observation time, we derive the distribution of probability of failure rate data using shifted data to the observation time where we defined the distribution as equivalent distribution of probability of at the observation time. Assuming that the probability distribution can be identical at the crossing point of accidental mode and wear-out mode, we compare the failure rate distributions at the crossing point between accidental failure mode and wear-out failure mode and choose the crossing point based on its correlation. After setting crossing point, we estimate the all equivalent failure rate data from both failure modes comparing its distribution to Normal, Weibull, and Log-normal, and decide the Weibull distribution as the equivalent failure rate distribution with the highest correlation coefficient. Furthermore, we apply the probability distribution to the failure rate calculated by the definition of IEC/TR62380 and find that the probability of failure rate for a standard environment is 50% and severer environment failure rate becomes 69.5% of probability. As we apply the distribution function of failure rate given by the field data to IEC/TR62380 mathematical model, we can set standard criteria of the failure rate using IEC/TR62380 and adjust criteria according to the environment of product usage at setting the risk level for a manufacturing management system.
