A Monte Carlo approach for evaluation of availability and failure intensity under g-renewal process model

Introducing a g-renewal component in system reliability analysis

“…is calculated [7]. These raw simulations can be used for validation of other approximate solutions and for identification of problems emerging in the simulation.…”

“…These raw simulations can be used for validation of other approximate solutions and for identification of problems emerging in the simulation. For example, it has been shown in [7] that a large number of trials are required for Frequency of Failures calculation. In the Table 1 We have to note, that the most significant accuracy problem arises in the range 1 )…”

“…This result was confirmed by a raw Monte Carlo simulation. In addition, to improve the speed of calculations we implemented multithreading programming approach, which perfectly fits Monte Carlo method [7]. After all, it takes roughly 0.2 sec to calculate the Expected Number of Failures, Unavailability and Failure Frequency at 10 time points in the time interval corresponding to 0<W(t)≤10.…”

“…This formula is much more efficient in terms of accuracy compared to direct Monte Carlo calculations, because usually the probability ( ) t Q is very small and requires many trials [7].…”

“…The method was expanded [7] [7] under the assumption that the repair time is much less than mean time between failures. The present paper will show that even though this assumption is valid for Expected Numbers of Repairs calculation, it causes significant error in calculation of Failure Frequency and Unavailability of a system component.…”