An integrated Cognitive Reliability and Error Analysis Method (CREAM) and optimization for enhancing human reliability in blockchain

Modares, Azam; Bafandegan Emroozi, Vahideh; Gholinezhad, Hadi; Modares, Azade

doi:10.1016/j.dajour.2024.100506

Decision Analytics Journal

2024

DOI: 10.1016/j.dajour.2024.100506

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An integrated Cognitive Reliability and Error Analysis Method (CREAM) and optimization for enhancing human reliability in blockchain

Azam Modares,

Vahideh Bafandegan Emroozi,

Hadi Gholinezhad

et al.

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Evaluating human error probability in maintenance task: An integrated system dynamics and machine learning approach

Bafandegan Emroozi,

Kazemi,

Pooya

et al. 2024

Hum Ftrs & Erg Mfg Svc

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Human error is often implicated in industrial accidents and is frequently found to be a symptom of broader issues within the sociotechnical system. Therefore, research exploring human error during maintenance activities is important. This article aims to assess the probability of human error in maintenance tasks at a cement factory using the Cognitive Reliability and Error Analysis Method and System Dynamics modeling. Given that human error probability (HEP) is influenced by various common performance conditions (CPCs) and their sub‐factors, and changes dynamically in response to other variables, the SD method offers a practical approach for estimating and predicting human error behavior over time. This study identifies and quantifies the variables affecting HEP, explores their interactions and feedback in maintenance tasks, and assesses the associated costs. The machine learning technique is then used to estimate the relationship between HEP and these costs. The optimal value of the HEP function, 0.000772, is determined by identifying the minimum point of a cubic function, thereby minimizing associated costs and occupational accidents. Determining the optimal HEP is crucial for minimizing excessive costs and investing in improved ergonomics and CPCs for better performance. This addresses a significant gap in existing research where the impact of human error on maintenance tasks has not been estimated as a function. Furthermore, three scenarios are presented to help managers allocate the organization's budget more effectively.

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Evaluating human error probability in maintenance task: An integrated system dynamics and machine learning approach

Bafandegan Emroozi,

Kazemi,

Pooya

et al. 2024

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

show abstract

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An integrated Cognitive Reliability and Error Analysis Method (CREAM) and optimization for enhancing human reliability in blockchain

Cited by 1 publication

References 41 publications

Evaluating human error probability in maintenance task: An integrated system dynamics and machine learning approach

Evaluating human error probability in maintenance task: An integrated system dynamics and machine learning approach

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