Simulation, or more specifically numerical simulation, is a very powerful tool for modeling of engineering, social, business, life science and other systems where the traditional analytical or graphical techniques become very complex, especially if some of the system variables have stochastic nature. Simulation has been applied for solving problems in reliability engineering also. In this paper a literature review on the application of simulation techniques for modeling and analysis of problems in reliability engineering is presented. Various simulation methodologies such as Monte Carlo simulation, Discrete event (DE) simulation, Subset simulation, Hybrid subset simulation, Simulated annealing, Stochastic simulation, Digital simulation, and Markov System Dynamics (MSD) simulation are discussed in details. Applications of these techniques in reliability engineering, their advantages and limitations are also presented. It is also found that the full potential of simulation as a system modeling and analysis approach has not been explored till date in the field of reliability engineering. Since several variables in reliability engineering field such as time to failure, time between failures, time to repair, down time, and others have stochastic nature, simulation approach is very appropriate. It appears that modeling of multi-state devices, degradation and wear out phenomena, state-space approach, point and steady state availability of complex systems can be simplified by simulation techniques. Therefore, this paper also has suggested that more research in these areas is needed.
Received on February 27, 2016, revised on June 13, 2016