Elsevier

Computers & Industrial Engineering

Volume 125, November 2018, Pages 111-123
Computers & Industrial Engineering

A fuzzy Fine-Kinney-based risk evaluation approach with extended MULTIMOORA method based on Choquet integral

https://doi.org/10.1016/j.cie.2018.08.019Get rights and content

Highlights

  • The interactions among risk factors is considered in Fine-Kinney approach.

  • An integrated Choquet integral is used to determine the risk parameter weight.

  • An extended MULTIMOORA method is proposed to prioritize risk of hazard.

  • Sensitivity and comparison analysis are conducted to illustrate the new method.

Abstract

The Fine-Kinney as a comprehensive and quantitative risk assessment method has been commonly applied to aid in controlling occupational hazards in practice. However, the Fine-Kinney-based risk evaluation approach suffers from the drawbacks of failing to deal with the interaction relationships between risk parameters and determine the risk priority of occupational hazards. The purpose of this paper is to propose a novel Fine-Kinney-based risk evaluation approach combining triangular fuzzy number, MULTIMOORA method and Choquet integral to overcome the limitations in the current Fine-Kinney-based risk evaluation approach. First, the triangular fuzzy number is employed to determine the risk parameters scores in Fine-Kinney approach. Second, the relative preference relation based triangular fuzzy number ranking method is integrated with the Choquet integral to determine importance weights of risk parameters. Third, an extended MULTIMOORA method with Choquet integral is proposed to determine the risk priority order of hazards by considering the interaction relationships between risk parameters. Finally, a case study of ballast tank maintenance is selected to demonstrate the application and feasibility of the proposed hybrid Fine-Kinney-based risk evaluation method, and comparison and sensitivity analysis are also conducted to validate the effectiveness of the new risk assessment model.

Introduction

One of the main issues for Occupational Health and Safety (OHS) is to prevent and control the occupational hazards (Gul, Ak, & Guneri, 2017). Risk assessment has been employed as a tool to determine hazards and decide the risk status (Gurcanli et al., 2015, Ilbahar et al., 2018). A large number of quantitative and qualitative risk assessment techniques have been applied to OHS risk assessment, such as the decision matrix approach (Gul and Guneri, 2016, Marhavilas and Koulouriotis, 2008), failure mode and effect analysis (FMEA) (Chen et al., 2014, Zarei et al., 2017, Liu et al., 2017a, Liu et al., 2017b, Liu et al., 2018b), Fine-Kinney method (Ilbahar et al., 2018, Kokangül et al., 2017), hazard and operability (HAZOP) analysis (Kasai et al., 2016, Raoni et al., 2018) and human reliability assessment (HRA) techniques (Akyuz, 2016, Chadwick and Fallon, 2012, Liu et al., 2018a).

The Fine-Kinney approach, primarily introduced by Kinney and Wiruth (1976), is a quantitative and comprehensive tool for risk analysis and control. This approach determines risk degree of hazard through a mathematic product of three risk parameters, namely, the possible consequence of a potential accident (C), the exposure of a hazard-event (E) and the probability (P). For its simple mechanism and operation process, the Fine-Kinney-based risk assessment approach has been applied to various fields. Gurcanli et al. (2015) proposed a hybrid Fine-Kinney method to evaluate the risk of building construction project. Kokangül et al. (2017) reported a novel risk assessment framework based on Fine-Kinney approach to determine the risk classes of hazards in manufacturing industry. In (Gul, Guven, Guneri, 2017), an integrated Fine-Kinney-based risk evaluation method was introduced to identify and calculate the risk priority of each hazard in an arms manufacturing company. Gul, Celik, Akyuz (2017) introduced an integrated risk assessment method for ballast tank maintenance by using a developed Fine-Kinney approach. In (Gul & Celik, 2018), the Fine-Kinney approach was developed to analyze the risk of rail transportation systems. Ilbahar et al. (2018) proposed a hybrid Fine-Kinney approach to evaluate risk of hazards in construction yard.

With application of the Fine-Kinney approach in hazard risk assessment of complex situations, it is difficult for OHS experts to evaluate risk parameters C, E and P by exact numbers in practice (Gul and Celik, 2018, Gul et al., 2017). Instead, the experts prefer to express their evaluation information with nature linguistic terms. The fuzzy numbers have been widely utilized to convert the linguistic terms to accomplish the decision (Gul, 2018, Ilbahar et al., 2018). Triangular fuzzy number (Gul, Celik, et al., 2017), trapezoidal fuzzy number (Wang, You, Liu, & Wu, 2017) and intuitionistic fuzzy number (Sayyadi Tooranloo & Ayatollah, 2016) have been adopted to represent linguistic terms of risk evaluation information. Among the various types of fuzzy numbers, the triangular fuzzy numbers is the most widely used in current risk assessment (Baykasoğlu and Gölcük, 2017, Fattahi and Khalilzadeh, 2018, Gul et al., 2017, Kutlu and Ekmekçioğlu, 2012).

Choquet integral, first introduced by Sugeno (1974), is a method applied to handle interaction relationships among criteria (Labreuche and Grabisch, 2018, Tseng et al., 2009, Wang et al., 2017, Zhang et al., 2017). This method can not only deal with the dependencies among risk factors, but also represent the nonlinear correlations, ranging from redundancy to synergy. This method has been adopted to deal with different types of multi-criteria decision making (MCDM) problems with interaction of involved criteria (Horanská and Šipošová, 2018, Khan et al., 2018, Labreuche and Grabisch, 2018). In particular, Choquet integral is becoming increasingly prominent in risk analysis. It has been applied to solve risk evaluation problems with interacted risk factors (Büyüközkan and Ruan, 2010, Shah et al., 2014, Wang et al., 2017, Wu et al., 2018). Moradi, Delavar, and Moshiri (2017) introduced the Choquet integral to handle the interaction relationships between multiple risk factors during earthquake vulnerability assessment process. Wang et al. (2017) combined the Choquet integral with FMEA to determine the ranking order of failure modes by considering the interaction relationships between risk parameters. Wu et al. (2018) introduced a hybrid risk assessment approach to analyze risk of waste-to-energy projects by using Choquet integral and cloud model.

Risk assessment in the hazards analysis process can be considered as a group decision making process. Some integrated risk assessment using AHP (analytic hierarchy process) (Kokangül et al., 2017), FAHP (fuzzy analytic hierarchy process) (Ilbahar et al., 2018), VIKOR (VIse Kriterijumska Optimizacija Kompromisno Resenje) (Gul et al., 2017, Gul et al., 2017), and MULTIMOORA (multiple multi-objective optimization by ration analysis) (Liu, Fan, Li, & Chen, 2014) have been put forward to analyze the hazards. Among these approaches, the MULTIMOORA, developed by Brauers and Zavadskas (2010), is a novel approach for resolving multi-criteria decision problems. The MULTIMOORA method determines the priority ranking of alternatives from three aspects, namely, the ratio system, the reference point, and the full multiplicative form. Therefore, MULTIMOORA method is introduced into the risk assessment procedure, which can derive a reasonable result (Fattahi and Khalilzadeh, 2018, Liu et al., 2014, Zheng et al., 2016). Liu et al. (2014) proposed a fuzzy FMEA approach based on MULTIMOORA method to evaluate the risk of preventing infant abduction. Zheng et al. (2016) proposed a hybrid FMEA framework to analyze the risk in steel production procedure. They used the MULTIMOORA method to determine the risk priority of each failure mode. Fattahi and Khalilzadeh (2018) introduced an integrated risk evaluation approach, in which the FAHP is combined with MULTIMOORA method to find out the risk priority of various accidents.

Regarding to the above-mentioned papers, although the Fine-Kinney approach has been applied as an effective risk evaluation of hazards in various domains, it still suffers from some limitations in practice: First, the Fine-Kinney approach determines the score of risk parameters C, E and P by crisp values, but this is difficult to assess C, E and P precisely in practice. Second, in the traditional Fine-Kinney approach, the different combinations of risk parameters’ scores can product the same risk value, which is not effective in practical risk management. Third, in current Fine-Kinney method, the risk parameters are assumed to be independent, however, these parameters in practice often interrelate with each other.

To overcome these limitations of the current Fine-Kinney-based risk evaluation approach, in this paper, we develop a new fuzzy Fine-Kinney-based risk evaluation approach with extended MULTIMOORA method based on the Choquet integral. To depict the uncertainty and vagueness in risk evaluation, the triangular fuzzy number is adopted to deal with the determination of risk score for risk parameters. To model the interaction relationships between risk parameters in risk prioritization, the extended MULTIMOORA method based on Choquet integral is developed to determine the risk priority orders of hazards in a comprehensive way. In this process, the Choquet integral is used to calculate the weights of risk parameters in MULTIMOORA method by considering the interaction relationships between risk parameters. Furthermore, risk evaluation information ranking of the Choquet integral method is extended by the relative preference relation based ranking approach. Finally, an illustrative example of ballast tank maintenance is used to demonstrate the proposed Fine-Kinney-based risk evaluation approach.

The rest of this paper is organized as follows: In Section 2, basic concepts about triangular fuzzy number, Choquet integral and MULTIMOORA method are briefly introduced. In Section 3, the extended MUTLIMOORA approach based on Choquet integral for risk priority ranking is presented. In Section 4, the novel proposed fuzzy Fine-Kinney based risk evaluation approach by using MULTIMOORA and Choquet integral is introduced. In Section 5, a case study of ballast tank maintenance is used to demonstrate the application and effectiveness of the proposed risk evaluation method. Section 6 provides the conclusions and future research direction.

Section snippets

Preliminaries

In this section, the basic concepts related to triangular fuzzy number, linguistic variables, Choquet integral and MULTIMOORA method are briefly introduced.

The extended MULTIMOORA approach with Choquet integral for risk prioritization

In this section, we first provide a new ranking method to solve the risk evaluation information ranking problem of Choquet integral, and then propose an extended MULTIMOORA approach based on Choquet integral for risk prioritization.

The fuzzy Fine-Kinney-based risk evaluation based on extended MULTIMOORA

In this section, we develop an extended MULTIMOORA method based on Choquet integral for solving risk evaluation and priorization problems of Fine-Kinney approach. First, we present a description of the risk evaluation problem of fuzzy Fine-Kinney approach. Then, we present the extended MULTIMOORA approach based on Choquet integral to solve the risk evaluation and priorization problems of fuzzy Fine-Kinney model.

In this paper, we suppose that all the OHS experts provide their risk evaluation

An illustrative example

In this section, an illustrative risk assessment case study of the ballast tank maintenance (Gul, Celik, et al., 2017) is adopted to demonstrate the application and feasibility of the proposed hybrid risk evaluation approach. Furthermore, comparison and sensitivity analysis are also performed to validate the effectiveness of the novel fuzzy Fine-Kinney-based risk assessment model.

Conclusions

The Fine-Kinney-based risk assessment method is a technique that has been commonly employed in various workplaces for OHS (Occupational Health and Safety) risk assessment. However, the traditional Fine-Kinney-based risk assessment model has some limitations in aggregation of risk evaluation information, calculation of risk degree and ranking of risk priority. It is of great importance to develop a new Fine-Kinney-based risk evaluation framework to overcome these weaknesses and improve the

Acknowledgements

The work is supported by the National Natural Science Foundation of China (71771051, 71371049), the Natural Science Foundation Youth Project of China (71701158) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0202).

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