Knowledge acquisition development in failure diagnosis analysis as an interactive approach

2019

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Probabilistic risk assessment techniques are the important tools which can considerably improve the safety performance of the studied system and reduce the risk to an acceptable level. Typically, decision‐making process is an important part of risk assessment methods that accordingly bring the ambiguity inside. Decision makers as experts commonly express their subjective opinions about the occurrence of the root events in order to obtain the probability of the undesired event. Subsequently, the critical root events are identified, and possible intervention is performed to reduce the probability of the critical events. However, the serious point is the viability of the obtained probabilities and priority ranking of the critical events. In this study, a heuristic optimization model of linear mathematical programming using triangular intuitionistic fuzzy number (TrIFN) is proposed to obtain the feasible, optimum, and reliable results compared with available methods. The Spearman correlation is performed to examine the reliability and behavior of the proposed model. In order to show the effectiveness of the proposed approach, it is applied on a real case study. The application of the model confirms its robustness to prioritize critical root events over the conventional one.

Section: Fault Tree Construction and Probabilistic Assessmentmentioning

confidence: 99%

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

2019

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“…Many scholars have been used the probabilistic risk assessment techniques in different industrial sectors, which help decision makers for risk and safety assessment of an undesired event, eg, FTA, 6-8 ETA, 9,10 Bow-tie, 11,12 and Bayesian updating mechanism. Fuzzy set theory proposed by professor Lotfi A. Zadeh 24 and several extension to fuzzy set theory 25,26 can properly handle the subjectivity in decision-making problems. In this accordance, decision-makers need to provide some intervention as mitigative and corrective actions to improve safety performance.…”

Section: Introductionmentioning

confidence: 99%

A perceptual computing–based method to prioritize intervention actions in the probabilistic risk assessment techniques

2019

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Probabilistic risk assessment techniques as the systematic tools have been widely used on the different type of industrial sectors to reduce the estimated risk to an acceptable level. The fact is to design inherently safety; hazards have to be eliminated and reduced in risk as much as possible with the consideration of several interventions. In this regard, multicriteria decision making (MCDM) science is commonly integrated with the probabilistic risk assessment techniques to improve the safety performance of a system. Thus, it has been widely used to assist decision makers in controlling the identified process hazards in a different type of engineering applications. However, by increasing the complexity of industrial sectors as well as human being judgments, typical MCDM methods cannot highly guarantee their output results. According to this point, proposing MCDM methods based on mathematical programming have been interested in scholars due to high reliability and feasibility of the results. In this paper, we extended integration of MULTIMOORA approach with the Choquet integral under subjectivity circumstances to prioritize corrective actions in a typical probabilistic risk assessment technique. To illustrate the efficiency and feasibility of the proposed method, it has been applied in a real case study.

“…Yazdi (2018) introduced a novel 2‐tuple intuitionistic fuzzy‐hybrid‐modified TOPSIS approach for assessing hazards in a gas refinery for the welding and lamination task to represent the effectiveness and reliability of proposed model to compare with the conventional risk matrix. In current year, Yazdi and Soltanali (2018) used recently IFNs in order to compute the failure probability in fluid filling system and then compare the results employing an updating mechanism tool . Therefore, the model based on the interval 2‐tuple linguistic terms method will be more flexible and precise to cope with expert judgments in the tacit knowledge acquisition process.…”

Section: Introductionmentioning

confidence: 99%

“…In current year, Yazdi and Soltanali (2018) used recently IFNs in order to compute the failure probability in fluid filling system and then compare the results employing an updating mechanism tool. 40 Therefore, the model based on the interval 2-tuple linguistic terms method will be more flexible and precise to cope with expert judgments in the tacit knowledge acquisition process.…”

mentioning

confidence: 99%

“…However, to the best of authors knowledge, there are few attempts that have been done to use 2-tuple linguistic terms in FTA, whereas many studies have been performed using conventional fuzzy FTA like as Rajakarunakaran et al, (2015), Yazdi and Zarei, (2018), and . [40][41][42] As a prior study, an intuitionistic fuzzy sets based method has been engaged for the failure analysis of the printed circuit board assembly. 43 Authors directly computed the intuitionistic fuzzy FTA interval, old-fashioned reliability, and the intuitionistic fuzzy reliability interval.…”

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confidence: 99%

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Footprint of knowledge acquisition improvement in failure diagnosis analysis

2018

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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.