Original Article

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


Numerous studies have been conducted to assess the role of human errors in accidents in different industries. Human reliability analysis (HRA) has drawn a great deal of attention among safety engineers and risk assessment analyzers. Despite all technical advances and the development of processes, damaging and catastrophic accidents still happen in many industries. Human Error Assessment and Reduction Technique (HEART) and Cognitive Reliability and Error Analysis Method (CREAM) methods were compared with the hierarchical fuzzy system in a steel industry to investigate the human error. This study was carried out in a rolling unit of the steel industry, which has four control rooms, three shifts, and a total of 46 technicians and operators. After observing the work process, reviewing the documents, and interviewing each of the operators, the worksheets of each research method were completed. CREAM and HEART methods were defined in the hierarchical fuzzy system and the necessary rules were analyzed. The findings of the study indicated that CREAM was more successful than HEART in showing a better capability to capture task interactions and dependencies as well as logical estimation of the HEP in the plant studied. Given the nature of the tasks in the studied plant and interactions and dependencies among tasks, it seems that CREAM is a better method in comparison with the HEART method to identify errors and calculate the HEP.

1. Dhillon B. Human error in aviation nd sea transportation systems. Proc Transportation Systems Reliability and Safety. 2007:58-62.
2. Konstandinidou M, Nivolianitou Z, Kiranoudis C, Markatos N. A fuzzy modeling application of CREAM methodology for human reliability analysis. Reliability Engineering & System Safety. 2006;91(6):706-16.
3. Embrey D, Kontogiannis T, Green M. Guidelines for preventing human error in process safety. Center for Chemical Process Safety. 1994;1(1).
4. Peters GA, Peters BJ. Human error: Causes and control: CRC press; 2006.
5. Stojiljkovic E. Methodological framework for human error assessment: University of Nis Nis; 2011.
6. Griffith CD, Mahadevan S. Inclusion of fatigue effects in human reliability analysis. Reliability Engineering & System Safety. 2011;96(11):1437-47.
7. Hollnagel E. Cognitive reliability and error analysis method (CREAM): Elsevier; 1998.
8. Stojiljkovic E, Bijelic B, Cvetkovic M. Application of HEART technique for human reliability assessment–a Serbian experience. Facta Universitatis, Series: Working and Living Environmental Protection. 2018:187-96.
9. Swain AD. Accident sequence evaluation program: Human reliability analysis procedure. Sandia National Labs., Albuquerque, NM (USA); Nuclear Regulatory Commission …; 1987.
10. Williams J, editor Toward an improved evaluation analysis tool for users of HEART. Int Conf on Hazard Identification and Risk Analysis, Human Factors and Human Reliability in Process Safety; 1992.
11. Kim MC, Seong PH, Hollnagel E. A probabilistic approach for determining the control mode in CREAM. Reliability Engineering & System Safety. 2006;91(2):191-9.
12. Jung WD, Yoon WC, Kim J. Structured information analysis for human reliability analysis of emergency tasks in nuclear power plants. Reliability Engineering & System Safety. 2001;71(1):21-32.
13. Mosleh A, Chang Y. Model-based human reliability analysis: prospects and requirements.

Reliability Engineering & System Safety. 2004;83(2):241-53.
14. Kirwan B. Human reliability assessment. Encyclopedia of Quantitative Risk Analysis and Assessment. 2008;2.
15. Kirwan B, Gibson H, Kennedy R, Edmunds J, Cooksley G, Umbers I, editors. Nuclear action reliability assessment (NARA): a data-based HRA tool. Probabilistic safety assessment and management; 2004: Springer.
16. Gibson W, Mills A, Smith S, Kirwan B. Railway action reliability assessment, a railway specific approach to human error quantification. Rail Human Factors. Supporting reliability, safety and cost reduction. Taylor & Francis; 2012.
17. Akyuz E, Celik M, Cebi S. A phase of comprehensive research to determine marine-specific EPC values in human error assessment and reduction technique. Safety science. 2016;87:63-75.
18. Bowo LP, Furusho M, editors. Human Error Assessment and Reduction Technique for Reducing the Number of Marine Accidents in Indonesia. Applied Mechanics and Materials; 2018: Trans Tech Publ.
19. Casamirra M, Castiglia F, Giardina M, Tomarchio E. Fuzzy modelling of HEART methodology: application in safety analyses of accidental exposure in irradiation plants. Radiation Effects and Defects in Solids. 2009;164(5-6):291-6.
20. Kumar AM, Rajakarunakaran S, Prabhu VA. Application of Fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station. Journal of Loss Prevention in the Process Industries. 2017;48:186-98.
21. Wu B, Yan X, Wang Y, Soares CG. An evidential reasoning‐based CREAM to human reliability analysis in maritime accident process. Risk analysis. 2017;37(10):1936-57.
22. Maddah S, Ghasemi M. Estimating the human error probability using the fuzzy logic approach of CREAM (The case of a control room in a petrochemical industry). organization.4:0-100.
23. Shirali GA, Hosseinzadeh T, Kalhori SRN. Modifying a method for human reliability assessment based on CREAM-BN: A case study in control room of a petrochemical plant. MethodsX. 2019;6:300-15.
24. Shokria S. A Cognitive Human Error Analysis with CREAM in Control Room of Petrochemical Industry. Biotechnology and Health Sciences. 2017(1):13-21.
25. Liu H-T, Tsai Y-l. A fuzzy risk assessment approach for occupational hazards in the construction industry. Safety science. 2012;50(4):1067-78.
26. Marseguerra M, Zio E, Librizzi M. Quantitative developments in the cognitive reliability and error analysis method (CREAM) for the assessment of human performance. Annals of Nuclear Energy. 2006;33(10):894-910.
27. Williams J. HEART—A Proposed Method for Assessing and Reducing Human Error in Ninth Advances in Reliability T echnology Symposium. NEC, Birmingham, June, AEA, T echnology, Culcheth, Warrington. 1986.
28. Rashed CSK. The concept of human reliability assessment tool CREAM and its suitability for shipboard operations safety. Journal of Shipping and Ocean Engineering. 2016;6:348-55.
29. Zadeh LA. Fuzzy sets. Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh: World Scientific; 1996. p. 394-432.
30. Birgani YT, Yazdandoost F, editors. Resilience in urban drainage risk management systems. Proceedings of the Institution of Civil Engineers-Water Management; 2016: Thomas Telford Ltd.
31. Mamdani E, Assilian S. An experiment in linguistic synthesis with a fuzzy logic controller. International journal of human-computer studies. 1999;51(2):135-47.
32. Islam N, Sadiq R, Rodriguez MJ, Francisque A. Evaluation of source water protection strategies: a fuzzy-based model. Journal of environmental management. 2013;121:191-201.
33. Jelleli TM, Alimi AM, editors. Automatic design of a least complicated hierarchical fuzzy system. International Conference on Fuzzy Systems; 2010: IEEE.
34. Lee M-L, Chung H-Y, Yu F-M. Modeling of hierarchical fuzzy systems. Fuzzy sets and systems. 2003;138(2):343-61.
35. Zaidi A, Rokbani N, Alimi A. Implementation of a Hierarchical fuzzy controller for a biped robot. arXiv preprint arXiv:14128500. 2014.
36. Fayaz M, Ullah I, Kim D-H. Underground risk index assessment and prediction using a simplified hierarchical fuzzy logic model and kalman filter. Processes. 2018;6(8):103.
IssueVol 13 No 2 (2021) QRcode
SectionOriginal Article(s)
HEART Method CREAM Method Steel Factory

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How to Cite
Boroun R, Tahmasbi Birgani Y, Mosavianasl Z, Shirali GA. 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. Int J Occup Hyg. 2021;13(2):105-119.