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An advanced human error assessment approach: HEART and AV‐DEMATEL
Author(s) -
Can Gülin F.,
Delice Elif K.
Publication year - 2020
Publication title -
human factors and ergonomics in manufacturing and service industries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.408
H-Index - 39
eISSN - 1520-6564
pISSN - 1090-8471
DOI - 10.1002/hfm.20819
Subject(s) - computer science , flexibility (engineering) , human error , process (computing) , task (project management) , reduction (mathematics) , context (archaeology) , categorization , error detection and correction , reliability engineering , machine learning , artificial intelligence , data mining , algorithm , statistics , systems engineering , mathematics , engineering , paleontology , geometry , biology , operating system
Human error assessment and reduction technique (HEART) is one of the most commonly used human error assessment approaches which computes human error probability (HEP) to prioritize errors related to human actions. HEART is a powerful tool considering error producing conditions (EPCs) which increase the HEP for generalized task versions named as generic task types (GTTs). HEART can give a solution including prevention of human‐related errors (HREs) and reduction of the HREs’ impacts via implementing additional controls. However, it has many shortcomings for real‐life error assessments. In this context, this study aims to improve effective usage of HEART through an advanced version of decision‐making trial and evaluation laboratory (AV‐DEMATEL). The reason to perform AV‐DEMATEL is to show the complex effect relations between main tasks (MTs), subtasks (STs), and EPCs in a process. For this aim, an integrated effect relation matrix is proposed for DEMATEL and importance weights of MTs, STs, and EPCs are computed based on this matrix. In addition, not only HREs are considered but also machine‐related errors (MREs) are taken into account to make error assessment for the process. The proposed approach also provides flexibility to categorize STs in different GTTs. Finally, a new term “process error probability” including HREs’ probabilities and MREs’ probabilities is recommended to compute error probability in an integrated manner for the process. To utilize the proposed approach, an example of a steam boiler daily control process is given.

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