Prediction of the time-dependent failure rate for normally operating components taking into account the operational history

Abstract

The prediction of the time-dependent failure rate has been studied, taking into account the operational history of a component used in applications such as system modeling in a probabilistic safety analysis in order to evaluate the impact of equipment aging and maintenance strategies on the risk measures considered. We have selected a time-dependent model for the failure rate which is based on the Weibull distribution and the principles of proportional age reduction by equipment overhauls. Estimation of the parameters that determine the failure rate is considered, including the definition of the operational history model and likelihood function for the Bayesian analysis of parameters for normally operating repairable components. The operational history is provided as a time axis with defined times of overhauls and failures. An example for demonstration is described with prediction of the future behavior for seven different operational histories.

Prediction of time dependent standby failure rates for periodically tested components taking into account the operational history

“…Failuresared iscovered only when arequest fort he component'soperation ismade. Foradiscussion on the dependencyof failurerateson equipmentage,itisr eferred tothe paperon prediction of the time-dependent(operating) failureratef ornormallyoperatingcomponents, [ 1], Section 2.Some furtherdiscussion canbef ound,forexample,in [2][3][4][5].Forastandbyfailure rate,the same type of time dependenteffectivef ailurerate model asin [1]ist aken,b ased on Pulcini [7], wherei tisassumed thatinherentt ime tof irst failuref ollows the Weibull distribution and principle of proportionalage reduction is then employed,i. e.,…”

“…considering that,in thiscase, t represents the cumulativetime spentin standby.Fordefinitionsand meaning of parameters,it isr eferred to [1].Inthe caseo fstandbyperiodicallyt ested components itisalsoassumed that t=0 isatime pointatwhich the componentwasassembled and thatEq. (1) appliesonlyfollowing some initialperiod [ 0,T 1 i (thisin ordertoallowforthe possibility thatt he failureratem ayfollowanothermodel during the initialperiod dueto,forexample,earlyfailures).…”

“…(1) by meansof Bayesiani nference,the same analyticalp rocedure appliesasdescribed in Section 3.1 of ref. [1].…”

“…Regardingthe time tof irst failureo fstandbyequipment knowntobeo perable at t=t 0 ,relationsfrom Section 3.3in [1]fort he probability density function (Eq. (12)i n [1])and forthe probability thatthe first failureoccurs during the time period h t 0 ,t ](Eq.…”

Development and application of a living probabilistic safety assessment tool: Multi-objective multi-dimensional optimization of surveillance requirements in NPPs considering their ageing

“…Subsequently, optimization study is conducted using the maintenance period as the control parameter. In [5] the authors have studied the prediction of the time-dependent failure rate, taking into account the operating history of a component used in applications such as system modelling in PSA. In such a way, the impact of equipment ageing and maintenance strategies on the risk measures is considered.…”