Reliability Estimation of Complex Technical Systems with

Complex technical systems may fail unexpectedly leading to process disruption and may bring a safety-hazard situation. The system failure is an outcome of failure dependency among subsystems where the degradation process of subsystems/components is random and uncertain process. Hence, reliability assessment of complex systems is of paramount importance. Quantitative reliability assessment needs failure data, which is scarce and/or not wellrecorded, thus statistically inconsistent in process industry. Most often, in such industries, the reliability is expressed linguistically (like Good, OK, Bad, etc.,) rather than quantitatively. This paper proposes an approach for quantitative reliability estimation considering failure dependency among subsystems using fuzzy failure possibility instead of failure probabilities. Condition monitoring data is used to estimate the failure possibilities with fuzzy sets. Fault tree analysis is applied to arrive at system failure possibility. The proposed approach is applied on large electric motor (2300 kW) by treating it as a system of subsystems. An order of 50% variation is found in the failure possibility estimates between with and without dependencies considerations. This approach not only helps the maintenance engineer to assess reliability but also assist in timely scheduling of suitable maintenance task. © 2008 World Academic Press, UK. All rights reserved.