Bayesian Approach for Early Stage Reliability Prediction of Evolutionary Products

New product reliability prediction has been center of research studies for many years. Reliability prediction focuses on developing a proper reliability model based on available data. Early life reliability prediction is challenging due to the lack of available data thus it is important to use a proper method for reducing this uncertainty. Bayesian method has been used widely in different area of studies to model uncertainty exist in a probabilistic way. This paper proposes a novel model to facilitate reliability prediction of non-repairable evolutionary product early after production using Bayesian method. The proposed Bayesian model joins prior information on past product failure and sparse few field data on new product’s performance. This approach helps us to overcome one of the important obstacle in the new product early reliability prediction which is lack of data. This study shows that Bayesian model outcomes are more accurate and logical compared to classical methods and indications are favorable regarding the model’s practicality in industry applications.