Volume 6, Issue 4 ( Iranian Journal of Ergonomics 2019)
Iran J Ergon 2019, 6(4): 66-74 |
Back to browse issues page
Mahnaz Shakerian1 
, Alireza Choobineh * 2, Mehdi Jahangiri3 , Moslem Alimohammadlou4 , Mohammad Nami5
, Alireza Choobineh * 2, Mehdi Jahangiri3 , Moslem Alimohammadlou4 , Mohammad Nami5
1- Student Research Committee, Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
2- Professor, Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran , alrchoobin@sums.ac.ir
3- Associate Professor, Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
4- Assistant Professor, Department of Management, Faculty of Economic, Management and Social Science, Shiraz University, Shiraz, Iran
5- Assistant Professor, Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
2- Professor, Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran , alrchoobin@sums.ac.ir
3- Associate Professor, Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
4- Assistant Professor, Department of Management, Faculty of Economic, Management and Social Science, Shiraz University, Shiraz, Iran
5- Assistant Professor, Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
Abstract: (7982 Views)
Background and Objectives: The recognition of a system failure causes and their related factors are considered as the most important factor in preventing accident occurrence in different organizations including industries. Human error is a known important factor in unpredictable events of which cognitive factors are the most influential ones. The purpose of this study was to introduce a new model for individual cognitive factors influencing human error as well as determining the interactions between the factors and their intensity using DEMATEL approach.
Methods: First a qualitative study was performed in order to identify and elicit the individual cognitive factors influencing human error among the workers of different industries. To ensure the adequacy and comprehensiveness of the elicited factors, then, the experts’ opinion was applied. DEMATEL method was used for understanding the interactions among the individual cognitive factors influencing human error. Finally, using these relationships, a new model of the study was proposed.
Results : Calculating D-R and D+R relating to the factors in terms of being cause or effect factor, D-R was -1.213 for C5 as the highest negative value, and D+R was 2.294 for the same factor (C5). Also, threshold level was calculated as 0.087 in the current study
Conclusion: In this study, the factors of failure in problem solving and decision making (C5) and difficulty in predicting possible hazards in the workplace areeffects and the other factors were the cause factors. The factor of C5 was the highest interactive factor.
Methods: First a qualitative study was performed in order to identify and elicit the individual cognitive factors influencing human error among the workers of different industries. To ensure the adequacy and comprehensiveness of the elicited factors, then, the experts’ opinion was applied. DEMATEL method was used for understanding the interactions among the individual cognitive factors influencing human error. Finally, using these relationships, a new model of the study was proposed.
Conclusion: In this study, the factors of failure in problem solving and decision making (C5) and difficulty in predicting possible hazards in the workplace are
Type of Study: Research |
Subject:
Other Cases
Received: 2019/02/12 | Accepted: 2019/03/16 | ePublished: 2019/06/8
Received: 2019/02/12 | Accepted: 2019/03/16 | ePublished: 2019/06/8
References
1. Flin R, Mearns K, O'Connor P, Bryden R. Measuring safety climate: identifying the common features. Safety science. 2000;34(1):177-92. Moura R, Beer M, Patelli E, Lewis J, Knoll F. Learning from major accidents to improve system design. Safety science. 2016;84:37-45. Reason J. Understanding adverse events:human factors. Quality in health care. 1995;4:80-9. [DOI:10.1136/qshc.4.2.80] [PMID] [PMCID]
2. Hollnagel E. Human reliability analysis:Context and Control. Academic Press; 1993. [Google Book]
3. Dhillon BS. Human reliability and error in transportation systems. Springer Science & Business Media. 2007. [Google Book]
4. Kumar P, Gupta S, Agarwal M, Singh U. Categorization and standardization of accidental risk-criticality levels of human error to develop risk and safety management policy. Safety science. 2016;85:88-98. [DOI:10.1016/j.ssci.2016.01.007]
5. Van Cott H. Human errors: Their causes and reduction. InHuman error in medicine 2018 Feb 6 (pp. 53-65). CRC Press.. [DOI:10.1201/9780203751725-4]
6. Castillo E, Calviño A, Grande Z, Sánchez‐Cambronero S, Gallego I, Rivas A, et al. A Markovian-Bayesian network for risk analysis of high speed and conventional railway lines integrating human errors. Computer‐Aided Civil and Infrastructure Engineering. 2016;31(3):193-218. [DOI:10.1111/mice.12153]
7. Madigan R, Golightly D, Madders R. Application of Human Factors Analysis and Classification System (HFACS) to UK rail safety of the line incidents. Accident Analysis & Prevention. 2016;97:122-31. [DOI:10.1016/j.aap.2016.08.023] [PMID]
8. Abbassi R, Khan F, Garaniya V, Chai S, Chin C, Hossain KA. An integrated method for human error probability assessment during the maintenance of offshore facilities. Process Safety and Environmental Protection. 2015;94:172-9. [DOI:10.1016/j.psep.2015.01.010]
9. Graziano A, Teixeira A, Soares CG. Classification of human errors in grounding and collision accidents using the TRACEr taxonomy. Safety science. 2016;86:245-57. [DOI:10.1016/j.ssci.2016.02.026]
10. Olivares RDC, Rivera SS, Mc Leod JEN. A novel qualitative prospective methodology to assess human error during accident sequences. Safety science. 2018;103:137-52. [DOI:10.1016/j.ssci.2017.10.023]
11. Akyuz E, Celik M. A methodological extension to human reliability analysis for cargo tank cleaning operation on board chemical tanker ships. Safety Science. 2015;75:146-55. [DOI:10.1016/j.ssci.2015.02.008]
12. Stanton NA, Salmon PM, Rafferty LA, Walker GH, Baber C, Jenkins DP. Human factors methods: a practical guide for engineering and design: CRC Press; 2017. [DOI:10.4324/9781351156325]
13. Mandal S, Singh K, Behera R, Sahu S, Raj N, Maiti J. Human error identification and risk prioritization in overhead crane operations using HTA, SHERPA and fuzzy VIKOR method. Expert Systems with Applications. 2015;42(20):7195-206. [DOI:10.1016/j.eswa.2015.05.033]
14. Horberry T, Burgess-Limerick R, Steiner LJ. Human factors for the design, operation, and maintenance of mining equipment: CRC Press; 2016. [DOI:10.1201/9781439802335]
15. Martinez MG, Zouaghi F, Garcia MS. Capturing value from alliance portfolio diversity: The mediating role of R&D human capital in high and low tech industries. Technovation. 2017;59:55-67. [DOI:10.1016/j.technovation.2016.06.003]
16. Akyuz E, Celik E. A modified human reliability analysis for cargo operation in single point mooring (SPM) off-shore units. Applied Ocean Research. 2016;58:11-20. [DOI:10.1016/j.apor.2016.03.012]
17. Thiels CA, Lal TM, Nienow JM, Pasupathy KS, Blocker RC, Aho JM, et al. Surgical never events and contributing human factors. Surgery. 2015;158(2):515-21. [DOI:10.1016/j.surg.2015.03.053] [PMID] [PMCID]
18. Evans M, Maglaras LA, He Y, Janicke H. Human behaviour as an aspect of cybersecurity assurance. Security and Communication Networks. 2016;9(17):4667-79. [DOI:10.1002/sec.1657]
19. Woods DD, Dekker S, Cook R, Johannesen L, Sarter N. Behind human error: CRC Press; 2017. [DOI:10.1201/9781315568935]
20. Reason J, Hobbs A. Managing maintenance error: a practical guide: CRC Press; 2017. [DOI:10.1201/9781315249926]
21. Simpson G, Horberry T. Understanding human error in mine safety: CRC Press; 2018. [DOI:10.1201/9781315549194]
22. Dekker S. The field guide to understanding'human error': CRC press; 2017. [DOI:10.1201/9781315239675]
23. Carpitella S, Carpitella F, Certa A, Benítez J, Izquierdo J. Managing Human Factors to Reduce Organisational Risk in Industry. Mathematical and Computational Applications. 2018;23(4):67. [DOI:10.3390/mca23040067]
24. Guo BH, Yiu TW, González VA. Predicting safety behavior in the construction industry: Development and test of an integrative model. Safety science. 2016;84:1-11. [DOI:10.1016/j.ssci.2015.11.020]
25. Shou W, Wang J, Wang X, Chong HY. A comparative review of building information modelling implementation in building and infrastructure industries. Archives of computational methods in engineering. 2015;22(2):291-308. [DOI:10.1007/s11831-014-9125-9]
26. Aalipour M, Ayele YZ, Barabadi A. Human reliability assessment (HRA) in maintenance of production process: a case study. International Journal of System Assurance Engineering and Management. 2016;7(2):229-38. [DOI:10.1007/s13198-016-0453-z]
27. Brehm E, Hertle R, Wetzel M, editors. Influence of Human Error on Structural Reliability. IABSE Symposium Report; 2017: International Association for Bridge and Structural Engineering. [Google Scholar]
28. Schulz CM, Krautheim V, Hackemann A, Kreuzer M, Kochs EF, Wagner KJ. Situation awareness errors in anesthesia and critical care in 200 cases of a critical incident reporting system. BMC anesthesiology. 2015;16(1):4. [DOI:10.1186/s12871-016-0172-7] [PMID] [PMCID]
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |