Footprint of knowledge acquisition improvement in failure diagnosis analysis

Abstract

Fault tree analysis (FTA) as an effective and efficient risk assessment tool are widely used to analyze the reliability of a complex system. In this context, FTA can properly improve the safety performance of the system by preventing an event which may lead to occurrence of a catastrophic accident. However, traditional FTA is still suffering from dynamic structure demonstration and importantly epistemic uncertainty processing. In this study, a novel methodology is introduced using Bayesian updating mechanism to deal with dynamic structure and 2‐tuple fuzzy set named as intuitionistic fuzzy numbers are employed to cope with subjectivity of uncertainty processing. Accordingly, the most critical system components which affect the system reliability are recognized by using an appropriate sensitivity analysis method. The proposed methodology is then applied on a real case study application (a brake fluid filling system) in order to examine the effectiveness and feasibility of the approach. The results illustrated that the new methodology can have enough benefits for diagnosing the systems' faults compared with listing approaches of safety and reliability analysis. In terms of empirical case study, “electromotor failure” was evaluated as the second most critical basic event in conventional‐based approaches, whereas in the novel methodology “high pressure liquefied material” was recognized as the second one.

Fuzzy smart failure modes and effects analysis to improve safety performance of system: Case study of an aircraft landing system

“…Failure modes (FMs) and effects analysis (FMEA) is a structural risk assessment technique that started in the aerospace industry in the 1960s. FMEA is widely used to define, identify, and eliminate potential failures; and because the risk assessment is a continuous procedure, process designs are often better improved . According to some evidence‐based experts' opinions from the FMEA team members, each FM will obtain risk priority number (RPN) to represent the level of its risk.…”

“…FMEA is widely used to define, identify, and eliminate potential failures; and because the risk assessment is a continuous procedure, process designs are often better improved. [1][2][3][4][5][6] According to some evidence-based experts' opinions from the FMEA team members, each FM will obtain risk priority number (RPN) to represent the level of its risk. Subsequently, some recommendations are provided on how FMs might be controlled to prevent them from having negative effects on the system.…”

Introducing a heuristic approach to enhance the reliability of system safety assessment

“…In order to obtain the optimum possibility of each basic event, it is vital to confirm following assumptions as a fact: The probability value of all basic events as well as the top event cannot guarantee that the specific event will surely happen during the recognized period of time. As an example, if safety expert computed the probability of the top event is close to 1 even 0.99, it is not meaning that the undesired event will surely occur in the specific period of time, eg, 1 year The reliability of objective probabilistic risk assessment methods are more than subjective ones, and reliability of both mentioned approaches are more than integration of objectivity and subjectivity in an approach.…”

“…The probability value of all basic events as well as the top event cannot guarantee that the specific event will surely happen during the recognized period of time. As an example, if safety expert computed the probability of the top event is close to 1 even 0.99, it is not meaning that the undesired event will surely occur in the specific period of time, eg, 1 year …”

Ignorance‐aware safety and reliability analysis: A heuristic approach

“…MCDM means “making preference decisions,” including estimation, prioritization, evaluation, and selection, of the options over all possible alternatives that are typically characterized by multiple criteria . Obviously, decision‐making science is an integrated part of safety and reliability analysis, which is inherently based on uncertainty . Uncertainty conceptually consists of two forms as structural and parameter uncertainties, respectively, reflecting the ambiguity in a model selection and the uncertainties in the input data .…”