26th International Association for Management of Technology Conference - IAMOT 2017

Managers of organisations are often faced with non-structured problems which involve quite a lot of uncertainties in their process. The reason is that organisations have not been recognised as dynamic and open and the stochastic nature of their complex systems is not fully appreciated. Hence, there is ample need for developing a tool that applies reliability techniques that are normally used in assessing the performance of physical complex systems, to help managers to assess the reliability of their departmental performances. Although some applications were previously designed to reveal the probabilistic nature of system's components performances, unfortunately, the results are still obtained from deterministic modelling which is inadequate for real understanding and analysis of complex systems' performance. The aim of this work is the development of a simulated probabilistic fault tree analysis that can facilitate the accurate study of the possible events that can cause the failure of the system’s failure. By allowing probabilistic input of basic events a Probabilistic Fault Tree Diagram (Prob_FTD) can be built giving managers more freedom to check among a range of failure probabilities that the system might fall in rather than one limited deterministic failure value. The addition in this work is the use of the Monte Carlo Simulation (MCS) method to simulate this Prob_FTD to get more accurate results and values for the intermediate and top events. This makes the analysis more rigorous and gives more practicality to the assessment of the whole system resulting in better management actions and higher reliable system performance.