Received: 2020.09.25, Accepted: 2020.12.25, Online ISSN: 2676-3346 DOI : 10.30699/IJRRS.3.2.12 Vol. 3/ Issue 2/ 2020 pp. 99-111 Computation of Importance Measures Using Bayesian Networks for the Reliability and Safety of Complex Systems S.A. Raza 1* , Q. Mahboob 1 , A.A. Khan 1 , T.A. Khan 1 , J. Hussain 1 1. Mechanical Department, University of Engineering and Technology (UET), Lahore, Pakistan Abstract Modern engineering systems have proven to be quite complex due to the involvement of uncertainties and a number of dependencies among the system components. Shortcoming in the inclusion of such complex features results in the wrong assessment of reliability and safety of the system, ultimately to the incorrect engineering decisions. In this paper, the usefulness of Bayesian Networks (BNs) for achieving improved modeling and reliability and risk analysis is investigated. The calculation of a number of Importance Measures with use of Fault Tree Analysis as well as BNs is provided for a complicated railway operation problem. The BNs based safety risk model is investigated in terms of quantitative reliability and safety analysis as well as for multi dependencies and uncertainty modeling. Keywords: Reliability, Safety, Importance Measures, Probabilistic modeling. Nomenclature * BNs Bayesian Networks FTA Fault Tree Analysis ETA Event Tree Analysis SPAD Signal Passing At Danger TPWS Train Protection and Warning Systems Te Top event IMs Importance Measures IMP Improvement Potential CIF Criticality Importance Factor FUV Fussell-Vesely BIM Birnbaum’s Measure DIF Diagnostic Importance Factor RRW Risk Reduction Worth RAW Risk Achievement Worth COP Conditional Probability SRM Safety Risk Model CTA Curve in Track Alignment HTRS High Train Speed FAF Failure Frequencies FU Fixed Unavailability Values SRM Safety Risk Model HTRS High Train Speed CPT Conditional Probability Table DE Driver error towards brake Application * Corresponding Author Email: aownraza217@gmail.com Introduction Importance Measures (IMs) may assist the system designers in the recognition of the components requiring improvement, helping the maintenance engineers for improving the maintenance strategies regarding the demanding components and expedite the decision makers regarding discharge of the engineering finances for the safety mechanization. There are a lot of Importance and criticality evaluation measures which are effective in various reliability and safety risk problems [1, 2, 3, 4]. For example, Risk Achievement Worth (RAW) recognizes the system risks increment in the case a specific component downfall in system has taken place. An increment in the occurrence possibility of the downfall of component will result into the increase of Fussel Vesely (FUV) Value. Event Tree Analysis (ETA) and Fault Tree Analysis (FTA) are the common methods applied to logically represent an engineering system such as a railway system, for the reliability and risk analyses [5, 6, 7, 8]. Generally, both FTA and ETA simplify the calculations by considering logically deterministic combinations of causes. Due to this reason, there exist