Analysis and Consequences on Some Aggregation Functions of PRISM (Partial Risk Map) Risk Assessment Method

被引:16
作者
Bognar, Ferenc [1 ]
Hegedus, Csaba [2 ]
机构
[1] Budapest Univ Technol & Econ, Dept Management & Business Econ, H-1117 Budapest, Hungary
[2] Univ Pannonia, Dept Supply Chain Management, H-8200 Veszprem, Hungary
关键词
partial risk map; PRISM; PRISM number; failure mode and effect analysis; FMEA; RPN; risk matrix; risk assessment; safety science; systems safety; FAILURE MODE; COMPLIANCE MANAGEMENT; RANKING DIFFERENCES; FMEA; SUM;
D O I
10.3390/math10050676
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The PRISM (partial risk map) methodology is a novel risk assessment method developed as the combination of the failure mode and effect analysis and risk matrix risk assessment methods. Based on the concept of partial risks, three different aggregation functions are presented for assessing incident risks. Since the different aggregation functions give different properties to the obtained PRISM numbers and threshold surfaces (convex, concave, linear), the description of these properties is carried out. Similarity analyses based on the sum of ranking differences (SRD) method and rank correlation are performed and robustness tests are applied related to the changes of the assessment scale lengths. The PRISM method provides a solution for the systematically criticized problem of the FMEA, i.e., it is not able to deal with hidden risks behind the aggregated RPN number, while the method results in an expressive tool for risk management. Applying new aggregation functions, proactive assessment can be executed, and predictions can be given related to the incidents based on the nature of their hidden risk. The method can be suggested for safety science environments where human safety, environmental protection, sustainable production, etc., are highly required.
引用
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页数:19
相关论文
共 53 条
[1]   Risk Management in the Construction Industry Using Combined Fuzzy FMEA and Fuzzy AHP [J].
Abdelgawad, Mohamed ;
Fayek, Aminah Robinson .
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2010, 136 (09) :1028-1036
[2]   On the need for revising healthcare failure mode and effect analysis for assessing potential for patient harm in healthcare processes [J].
Abrahamsen, Hakon Bjorheim ;
Abrahamsen, Eirik Bjorheim ;
Hoyland, Sindre .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2016, 155 :160-168
[3]  
Benedek P, 2012, ACTA POLYTECH HUNG, V9, P135
[4]   Case Study on a Potential Application of Failure Mode and Effects Analysis in Assessing Compliance Risks [J].
Bognar, Ferenc ;
Benedek, Petra .
RISKS, 2021, 9 (09)
[5]  
Bognár F, 2021, ACTA POLYTECH HUNG, V18, P89
[6]   An Alternative FMEA Method for Simple and Accurate Ranking of Failure Modes [J].
Bradley, James R. ;
Guerrero, Hector H. .
DECISION SCIENCES, 2011, 42 (03) :743-771
[7]  
Braglia M., 2003, International Journal of Quality Reliability Management, V20, P503, DOI 10.1108/02656710310468687
[8]  
Braglia M., 2000, INT J QUAL RELIAB MA, V17, P1017, DOI DOI 10.1108/02656710010353885
[9]   Waste Segregation FMEA Model Integrating Intuitionistic Fuzzy Set and the PAPRIKA Method [J].
Carmen Carnero, Maria .
MATHEMATICS, 2020, 8 (08)
[10]   Fuzzy FMEA application to improve decision-making process in an emergency department [J].
Chanamool, Nalinee ;
Naenna, Thanakorn .
APPLIED SOFT COMPUTING, 2016, 43 :441-453