Statistical analysis of accelerated experiments in mechanics using a mechanical accelerated life model

Accelerated testing of mechanical products offers great potential for development in reliability life testing. Unfortunately, difficulties met in accelerated life testing have limited its applications and acceptance. This paper presents a discussion of the different approaches to accelerate life of mechanical materials. The importance of failure mechanism models and the separate treatment of failure mechanisms during accelerated life tests are discussed. We formulate a new mechanical accelerated testing life model called Mecha-Statistical model. This model, considered as parametric, is constructed on the base of an appropriate mechanical damaging, model (fatigue). Like most traditional accelerated testing models, the Mecha-Statistical model consists of a life distribution that describes the lifetimes of components and relationships between the parameters of this distribution and stress. We suggest a method to construct the lognormal distribution based on the Basquin model that describes fatigue data and integrates mechanical characteristics of the product. The appropriate stress parameters and their limits are determined and studied for the failure mechanism under consideration (fatigue). They are selected so that the failure mode and mechanism generated under nominal stress are also generated under the accelerating stress. Assuming that number of cycles to failure has a lognormal distribution, the relationship between reliability and mechanical characteristics were modeled and used to estimate reliability. Optimum parameters of accelerated testing models were determined by optimization methods. These parameters were used to make comparison between our Mecha-Statistical model and the other parametric and semi parametric accelerated life models. The results obtained reveal that theses models do not fit the fatigue data better and that our model is useful and beneficial. The Mecha-Statistical model describes perfectly the lifetime testing data of fatigue tests because it depends on the product, the test method and the accelerating stress.