An extension to the second model is also proposed that allows system level growth analysis to be accomplished based on subsystem development data. These models were compared to a number of existing growth models and found to be consistently superior in terms of relative error and mean-square error. engineering judgement, CERT testing, etc.), (2) the assumption that the failure intensity is stochastically decreasing, and (3) accountability of changes that are incorporated into the design after testing is completed. Major points of this Bayesian model include: (1) the ability to encorporate data from a number of test sources (e.g. The second model, while requiring the assumption of an exponential failure distribution, remains significantly more flexible than past models. Further, the first of the models only requires that the time-to-failure distribution be unimodal and that the reliability become no worse as development progresses. This thesis proposes two new growth models, neither requiring the assumption of a specific function to describe the intensity λ(t). The inability of any one family of distributions or parametric form to describe the growth process resulted in a multitude of models, each directed toward answering problems encountered with a particular test situation. The popular Duane model, for example, assumes that λ(t) = β(1 – α)t ⁻ᵅ. Major differences among models centered on the particular functional form of the intensity function. The result was that in most cases the improvement was modeled as a nonhomogeneous Poisson process with intensity λ(t). In addition, the time-to-failure distribution of the system was generally assumed to be exponential. Past research into the phenomenon of reliability growth has emphasised modeling a major reliability characteristic in terms of a specific parametric function.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
May 2023
Categories |