Fuzzy Logic in HEART and CREAM Methods to Assess Human Error and Find an Optimum Method Using a Hierarchical Fuzzy System: A Case Study in a Steel Factory

boroun, Razie; Birgani, Yaser Tahmasbi; Mosavianasl, Zeinab; Shirali, Gholam Abbas

doi:10.18502/ijoh.v13i2.8372

Cited by 2 publications

(4 citation statements)

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“…Thus an appropriate distribution to model the weights is to use the Dirichlet. Given a parameter 𝛼 the Dirichlet distribution of the weights 𝑊 is in Equation (9).…”

Section: Bayesian Bwmmentioning

confidence: 99%

“…The control room serves as the center of an industrial system, and any errors made by control room operators during their duties can lead to adverse consequences and potentially irreparable damage. [6][7][8][9] Therefore, there is a need to enhance organizational productivity through the assessment of human errors. Various methods and techniques exist for mitigating human errors, which can be categorized into two main groups: first-generation methods and second-generation methods.…”

Section: Introductionmentioning

confidence: 99%

“…In the cement industry, control room operators are responsible for the critical task of continuous process control. The control room serves as the center of an industrial system, and any errors made by control room operators during their duties can lead to adverse consequences and potentially irreparable damage 6–9 . Therefore, there is a need to enhance organizational productivity through the assessment of human errors.…”

Section: Introductionmentioning

confidence: 99%

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A new model to optimize the human reliability based on CREAM and group decision making

Bafandegan Emroozi,

Modares,

Roozkhosh

2023

Quality & Reliability Eng

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The Cognitive Reliability and Error Analysis Method (CREAM) represents one of the second‐generation approaches to human reliability assessment, taking into account the influence of environmental conditions on human error probability (HEP). In the context of CREAM, the Common Performance Conditions (CPCs) influence error probabilities. Since not all CPCs have equal impacts, this study employs the Bayesian Best Worst Method (BWM), a novel approach in group decision‐making, to assign weights to these factors. Subsequently, two techniques based on basic CREAM are proposed. The current control mode is determined in the first technique according to the experts' opinions. Then the probability of human error is calculated based on the amount of control. It is possible to provide solutions for improving control mode, based on obtained results. Therefore, in this study, the second method has been used to make suggestions to enhance human reliability. For this purpose, in the second technique, an optimization problem is formulated to select the best applicable programs for managers to enhance human reliability. The proposed bi‐objective model tries to increase the reliability of human resources by reducing human error and costs. The proposed bi‐objective model seeks to bolster the reliability of human resources by concurrently minimizing HEP and associated costs. The efficiency of the presented methods is verified through a case study in the control room of the cement factory. The results of the first technique reveal an opportunistic control mode with a corresponding HEP of 0.0198. On the other hand, the outcomes of our proposed model underscore the greater impact of improving CPC levels in reducing the probability of human error. Ultimately, the practical programs derived from our mathematical model provide decision‐makers with valuable insights to reduce the probability of human error to a mere 0.000172 through the transition from opportunistic to strategic control.

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“…Thus an appropriate distribution to model the weights is to use the Dirichlet. Given a parameter 𝛼 the Dirichlet distribution of the weights 𝑊 is in Equation (9).…”

Section: Bayesian Bwmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A new model to optimize the human reliability based on CREAM and group decision making

Bafandegan Emroozi,

Modares,

Roozkhosh

2023

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…CREAM calculates human error probabilities in accordance with the COCOM, which has scrambled, opportunistic, tactical, and strategic control modes, each corresponding to an error probability interval. Table 2 provides error probability intervals under different COCOM modes [45,46].…”

Section: Creammentioning

confidence: 99%

A Risk-Data-Based Human Reliability Analysis for Chemical Experiments with Hazardous Processes

Zhang

et al. 2023

Processes

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In recent years, chemical experiment accidents have frequently occurred, resulting in injuries and fatalities among researchers. It is crucial to address this issue to improve laboratory safety. Based on many publications, it is clear that human error makes a major contribution to many laboratory accidents which contain hazardous processes. However, there is limited research focusing on human error in laboratory safety, and there is also a lack of effective measures to assess Human Error Probability (HEP) for experimental process safety. Therefore, we propose an improved Cognitive Reliability and Error Analysis Method (CREAM) which is based on risk data to assess the HEP during hazardous processes in chemical experiments. The proposed method adjusts nine Common Performance Conditions (CPCs) in conventional CREAM to make them suitable to describe chemical experiments. Then, in contrast to the traditional approach, this study uses the definition of risk as the support to collect CPC data from the perspectives of possibility and severity, so as to improve the rationality of the data and decrease the subjectivity of expert judgment. Afterwards, the weight value of each CPC is calculated through Gray Relation Analysis (GRA) based on the collected risk data of each CPC. Meanwhile, the collected risk data are used to determine the fuzzy degrees of each CPC, the activated fuzzy If-Then rules, and the corresponding rule weights. Finally, the CPCs’ membership degrees, the CPCs’ weights, and If-Then rule weights are integrated together to acquire the HEP by defuzzification. In short, the proposed method changes the CPCs to ensure they are suitable, and then it innovatively uses risk data as the source to directly and indirectly determine the CPC’s fuzzy degree, the CPC’s importance weight, and the If-Then rule weight by fuzzy theory and GRA for collecting final HEP results. This method was tested on a selected chemical experiment, “preparation of active ferrous sulfide”, which contains hazardous processes. Through the proposed method, the HEP of each procedure in the selected risky chemical experiment could be determined, and among the procedures, the highest HEP was 1.51 × 10−3. In addition, with the HEP results, several subtasks with a high risk of human error could be identified. The results matched the real situations.

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Fuzzy Logic in HEART and CREAM Methods to Assess Human Error and Find an Optimum Method Using a Hierarchical Fuzzy System: A Case Study in a Steel Factory

Cited by 2 publications

References 0 publications

A new model to optimize the human reliability based on CREAM and group decision making

A new model to optimize the human reliability based on CREAM and group decision making

A Risk-Data-Based Human Reliability Analysis for Chemical Experiments with Hazardous Processes

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