Abstract
Having presented the general Human Reliability Analysis (HRA) principles and the special branch of Fuzzy/CREAM methodologies for Human error probability estimation, the chapter continues with some more details on CREAM which is the base for the fuzzy model developed. Some basic principles of fuzzy logic will then be covered before proceeding to the detailed description of the model itself. Special applications of the model i.e. the definition of critical transitions, the assessment of operators’ response times during a critical task performed in the chemical process industry along with a shorter tailored made version of the model will be presented in the remainder of this chapter.
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Notes
- 1.
Some analysts do not consider ATHEANA a third generation technique but rather a well advanced second generation one.
- 2.
However, the same researchers claim that the fuzzy model of CREAM brings on many redundant, self-contradictory rules, which would consume computational time, and lose the truth degree of the results.
- 3.
It has to be noted at this point that two out of the nine CPCs can have only a neutral or negative effect on human reliability. The effect of each CPC on human performance will be analytically explained in Sect. 4.2 where the development of the fuzzy model is being described.
References
Baziuk PA, Rivera SS, Núñez Mc Leod J (2016) Fuzzy human reliability analysis: applications and contributions review. Adv Fuzzy Syst. doi:10.1155/2016/4612086
Bedford T, Bayley C, Revie M (2013) Screening, sensitivity and uncertainty for the CREAM method of Human Reliability Analysis. Reliab Eng Syst Saf 115:100–110
Boecker M (2015) Enhancing the effectiveness and efficiency of control room operators—a roadmap-based approach for selecting interaction technologies for defence and safety-critical organisations and industries. Procedia Manuf 3:769–776
Cacciabue P (2004) Human error risk management for engineering systems: a methodology for design, safety assessment, accident investigation and training. Reliab Eng Syst Saf 83:229–240
Cooper S et al (2000) Technical basis and implementation guidelines for A Technique for Human Error Analysis (ATHEANA) NUREG-1624, Rev 1. U.S. Nuclear Regulatory Commission
Embrey DE (1992) Quantitative and qualitative prediction of human error in safety assessments. Major hazards Onshore and Offshore. IChemE, Rugby
Fujita Y, Hollnagel E (2004) Failures without errors: quantification of context in HRA. Reliab Eng Syst Saf 83:145–151
Geng J, Murè S, Gabriele B, Camuncoli G, Demichela M (2015) Human error probability estimation in ATEX-HMI area classification: from THERP to FUZZY CREAM. Chem Eng Trans 43:1243–1248
He X, Wang Y, Shen Z, Huang X (2008) A simplified CREAM prospective quantification process and its application. Reliab Eng Syst Saf 93:298–306
Hollnagel E (1996) Reliability analysis and operator modelling. Reliab Eng Syst Saf 52:327–337
Hollnagel E (1998) Cognitive reliability and error analysis method (CREAM). Elsevier, Amsterdam
Hollnagel E, Cacciabue P (1991) Cognitive modelling in system simulation. In: Proceedings of third European conference on cognitive science approaches to process control, Cardiff
Isaac A, Shorrock ST, Kirwan B (2002) Human error in European air traffic management: the HERA project. Reliab Eng Syst Saf 75(2):257–272
Kazaras K, Konstandinidou M, Nivolianitou Z, Kirytopoulos K (2013) Enhancing road tunnel risk assessment with a fuzzy system based on the CREAM methodology. Chem Eng Trans 31:349–354
Kim B, Bishu R (1996) On assessing operator response time in human reliability analysis (HRA) using a possibilistic fuzzy regression model. Reliab Eng Syst Saf 52:27–34
Kim M, Seong P, Hollnagel E (2006) A probabilistic approach for determining the control mode in CREAM. Reliab Eng Syst Saf 91:191–199
Klir J, Yuan B (1995) Fuzzy sets & fuzzy logic: theory and applications. Prentice Hall, Upper Saddle River, NJ
Konstandinidou M, Nivolianitou Z, Kiranoudis C, Markatos N (2006) A fuzzy modeling application of CREAM methodology for human reliability analysis. Reliab Eng Syst Saf 91:706–716
Konstandinidou M, Nivolianitou Z, Kiranoudis C, Markatos N (2008) Evaluation of significant transitions in the influencing factors of human reliability. Proc Inst Mech Eng O J Risk Reliab 222(1):39–45
Konstandinidou M, Nivolianitou Z, Simos G, Kiranoudis C, Markatos N (2009) Operators’ response time estimation for a critical task using the fuzzy logic theory. In: Proceedings of the joint ESREL and SRA-Europe conference on safety, reliability and risk analysis: theory, methods and applications, vol 1, pp 281–290
Kontogiannis T (1997) A framework for the analysis of cognitive reliability in complex systems: a recovery centred approach. Reliab Eng Syst Saf 58:233–248
Lee SM, Ha JS, Seong PH (2011) CREAM-based communication error analysis method (CEAM) for nuclear power plant operators’ communication. J Loss Prev Process Ind 2:90–97
Li PC, Chen GH, Dai LC, Li Z (2010) Fuzzy logic-based approach for identifying the risk importance of human error. Saf Sci 48(7):902–913
Liao PC, Luo X, Wan T, Su W (2016) The mechanism of how design failures cause unsafe behavior: the cognitive reliability and error analysis method (CREAM). Procedia Eng 145:715–722
Mamdani E (1974) Application of fuzzy Algorithms for simple dynamic plants. Proc IEE 121(12):1585–1588
Mamdani E, Assilian S (1975) An experiment in linguistic synthesis with a fuzzy logic controller. Int J Man Mach Stud 7(1):1–13
Mandal S, Singh K, Behera RK, Sahu SK, Raj N, Maiti J (2015) Human error identification and risk prioritization in overhead crane operations using HTA, SHERPA and fuzzy VIKOR method. Expert Syst Appl 42(20):7195–7206
Marseguerra M, Zio E, Librizzi M (2006) Quantitative developments in the cognitive reliability and error analysis method (CREAM) for the assessment of human performance. Ann Nucl Energy 33:894–910
Monferini A, Konstandinidou M, Nivolianitou Z, Weber S, Kontogiannis T, Kafka P, Kay AM, Leva MC, Demichela M (2013) A compound methodology to assess the impact of human and organizational factors impact on the risk level of hazardous industrial plants. Reliab Eng Syst Saf 119:280–289
Onisawa T (1996) Subjective analysis of system reliability and its analyser. Fuzzy Sets Syst 83:249–269
Park J, Kim Y, Kim JH, Jung W, Seung Jang C (2015) Estimating the response times of human operators working in the main control room of nuclear power plants based on the context of a seismic event—a case study. Ann Nucl Energy 85:36–46
Pedrycz W (1993) Fuzzy control and fuzzy systems. Second extended edition. Research Studies Press, London
Rachid B, Hafaifa A, Hadroug N, Boumehraz M (2016) Reliability evaluation based on a fuzzy expert system: centrifugal pump application. Stud Inf Control 25(2):181–188
Reason J (1990) The contribution of latent human failures to the breakdown of complex systems. Human factors in hazardous situations. Oxford Clarendon Press, Oxford
Saidi E, Anvaripour B, Jaderi F, Nabhani N (2014) Fuzzy risk modeling of process operations in the oil and gas refineries. J Loss Prev Process Ind 30(1):63–73
Sun Z, Li Z, Gong E, Xie H (2012) Estimating human error probability using a modified CREAM. Reliab Eng Syst Saf 100:28–32
Swain A, Guttmann H (1983) Handbook on human reliability analysis with emphasis on nuclear power plant application. NUREG/CR-1278. US Nuclear Regulatory Commission
Ung S-T, Shen W-M (2011) A novel human error probability assessment using Fuzzy modeling. Risk Anal 31(5):745–757
Verma M, Kumar A, Singh Y (2012) Fuzzy fault tree approach for analysing the fuzzy reliability of a gas power plant. Int J Reliab Saf 6(4):254–271
Vigier HP, Scherger V, Terceño A (2017) An application of OWA operators in fuzzy business diagnosis. Appl Soft Comput 54:440–448
Wang A, Luo Y, Tu G, Liu P (2011) Quantitative evaluation of human-reliability based on fuzzy-clonal selection. IEEE Trans Reliab 60(3):517–527
Wu B, Yan X, Wang Y, Soares CG (2017) An evidential reasoning-based CREAM to human reliability analysis in maritime accident process. Risk Anal. doi:10.1111/risa.12757
Yang ZL, Bonsall S, Wall A, Wang J, Usman M (2013) A modified CREAM to human reliability quantification in marine engineering. Ocean Eng 58:293–303
Zadeh L (1965) Fuzzy sets. Inf Control 8:338–353
Zadeh L (1973) Outline of a new approach to the analysis of complex systems and decision processes. IEEE Trans Syst Man Cybern 3:28–44
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Nivolianitou, Z., Konstantinidou, M. (2018). A Fuzzy Modeling Application for Human Reliability Analysis in the Process Industry. In: De Felice, F., Petrillo, A. (eds) Human Factors and Reliability Engineering for Safety and Security in Critical Infrastructures. Springer Series in Reliability Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-62319-1_5
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