A New Fine-Kinney Method Based on Clustering Approach

Dağsuyu, Cansu; Oturakci, Murat; Essiz, Esra Sarac

doi:10.1142/s0218488520500208

Cited by 11 publications

(4 citation statements)

References 16 publications

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“…In addition, it is frequently applied together with MCDM methods since it reflects the nature of the decision problem in determining the importance weights of the parameters and prioritizing the risks (Can and Toktas 2021 ; Zhu et al 2019 ; Kokangül et al 2017 ). Miscellaneous applications of this method, apart from MCDM/fuzzy set theory, are performed (Dagsuyu et al 2020 ; Gul and Celik 2018 ). Dagsuyu et al ( 2020 ) combined Fine − Kinney with k -means and hierarchical clustering algorithms to overcome its limitations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Miscellaneous applications of this method, apart from MCDM/fuzzy set theory, are performed (Dagsuyu et al 2020 ; Gul and Celik 2018 ). Dagsuyu et al ( 2020 ) combined Fine − Kinney with k -means and hierarchical clustering algorithms to overcome its limitations. In Gul and Celik ( 2018 ), a fuzzy rule-based system is designed according to the rail transportation risk assessment processes under Fine–Kinney.…”

Section: Literature Reviewmentioning

confidence: 99%

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Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Gül

Yücesan

2022

Environ Sci Pollut Res

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The Fine − Kinney is a risk assessment method widely used in many industries due to its ease of use and quantitative risk evaluation. As in other methods, it is a method that recommends taking a series of control measures for operational safety. However, it is not always possible to implement control measures based on the determined priorities of the risks. It is considered that determining the priorities of these measures depends on many criteria such as applicability, functionality, performance, and integrity. Therefore, this study has studied the prioritization of control measures in Fine − Kinney-based risk assessment. The criteria affecting the prioritization of control measures are hierarchically structured, and the importance weights of the criteria are determined by the Bayesian Best–Worst Method (BBWM). The priorities of control measures were determined with the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (FVIKOR) method. The proposed model has been applied to the risk assessment process in a petrol station’s liquid fuel tank area. According to the results obtained with BBWM, the most important criterion affecting the prioritization of control measures is the applicability criterion. It has an importance weight of about 42%. It is followed by performance with 31%, functionality with 18%, and integrity with 10%, respectively. FVIKOR results show that the “Periodic control of the ventilation device” measure is the top priority for Fine − Kinney risk assessment. “The absence of any ducts or sewer pits that may cause gas accumulation in the tank area and near the dispenser; Yellow line marking of entry and exit and vehicle roads; Placing of speed limit warning signs” has been determined as a secondary priority. On conclusion, this proposed model is expected to bring a new perspective to the work of occupational health and safety analysts, since the priority suggested by Fine − Kinney risk analysis methods is not always in the same order as the one in the stage of taking action, and the source, budget, and cost/benefit ratio of the measure affect this situation in practice. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-022-19454-x.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Gül

Yücesan

2022

Environ Sci Pollut Res

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“…Tang et al ( 2021 ) aimed to improve a hybrid risk prioritization approach for Fine–Kinney using the generalized TODIM (an acronym in Portuguese of interactive and multi-criteria decision-making), best–worst and interval type-2 fuzzy set. Dagsuyu et al ( 2020 ) developed a new approach to the classical Fine–Kinney risk assessment method. It is possible to reach the same RPN values with different combination calculations made with the three parameters.…”

Section: Literature Reviewmentioning

confidence: 99%

Action selection in risk assessment with fuzzy Fine–Kinney-based AHP-TOPSIS approach: a case study in gas plant

Dogan

Oturakci

Dağsuyu

2022

Environ Sci Pollut Res

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In this study, the hazards occurring in a medium-sized gas filling facility were defined, and the risk scores of these hazards were determined by the expert team according to the Fine–Kinney risk analysis method. However, since the same risk significance score is obtained in different combinations of scale values in the classical Fine–Kinney risk analysis method and the characteristics/constraints of the company applied in the risk analysis are not taken into account, the hazards were evaluated using fuzzy Fine–Kinney risk analysis, and the most critical hazards were determined. Action plans are defined for critical hazards determined as a result of fuzzy Fine–Kinney risk analysis. Among the actions that require company resources, the action selection was performed with the TOPSIS method, taking into account their relationship with the hazards by integrating the weights, which was calculated with the AHP method, of affected groups. The effect of operating constraints is included in the last step of the study to calculate the final weights. Calculating the results by including the risk-affected groups and company constraints and ranking the actions reveals that the study is an original, objective, and applicable study.

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“…The methods such as AHP [ 16 ], fuzzy AHP and fuzzy VIKOR [ 17 ], Pythagorean fuzzy AHP [ 18 ], k-means [ 19 ], and COPSOQ II questionnaire [ 20 ], are integrated into the Fine-Kinney method to overcome its shortcomings. Fuzzy logic provides to transform linguistic risk information into quantitative risk rating information.…”

Section: Introductıonmentioning

confidence: 99%

A new hybrid risk assessment method based on Fine-Kinney and ANFIS methods for evaluation spatial risks in nursing homes

Gökler

Yılmaz²,

Ürük³

et al. 2022

Heliyon

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A New Fine-Kinney Method Based on Clustering Approach

Cited by 11 publications

References 16 publications

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Control measure prioritization in Fine − Kinney-based risk assessment: a Bayesian BWM-Fuzzy VIKOR combined approach in an oil station

Action selection in risk assessment with fuzzy Fine–Kinney-based AHP-TOPSIS approach: a case study in gas plant

A new hybrid risk assessment method based on Fine-Kinney and ANFIS methods for evaluation spatial risks in nursing homes

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