IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 243 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 WAREHOUSE RISK ASSESSMENT USING INTERVAL VALUED INTUITIONISTIC FUZZY AHP Selcuk Cebi ,1 Department of Industrial Engineering, Yildiz Technical University, Besiktas 34349, Istanbul, Turkey scebi@yildiz.edu.tr Esra Ilbahar Department of Industrial Engineering, Istanbul Technical University, Macka 34367, Istanbul, Turkey esrailbahar@gmail.com ABSTRACT Warehouses are essential components of a supply chain management system. Any malfunction in warehouses may have an important effect on the subsequent operations of a firm. For example, an accident that occurs in a warehouse can damage the operations of the company as well as the health of the employees. In this paper, critical operations at a warehouse are considered in terms of occupational health and safety. The originality of the paper is that the proposed approach provides a new perspective on warehouse risk assessment. It is the first time a method involving interval valued intuitionistic fuzzy Analytical Hierarchy Process (IVIF-AHP) and a new risk assessment table is utilized to evaluate and categorize the risks in warehouses. As a result of the proposed risk assessment method, hazards in warehouses are categorized as insignificant, marginal, or catastrophic. Keywords: Warehouse risk management; risk assessment; risk analysis; interval valued intuitionistic fuzzy sets; Analytical Hierarchy Process 1. Introduction Warehouses are crucial components of a supply chain management system, and efficiently functioning warehouses enable companies to carry out their operations smoothly. Since any malfunction in warehouses may influence the subsequent operations of a firm, an accident that occurs in the warehouse can damage the operations of the company as well as the health of the employees. Thus, it is important to identify hazards in a warehouse and the risks associated with them in order to be able to prevent potential accidents in warehouses. A risk is defined as a combination of the probability of occurrence of an undesired situation and the severity of that situation. Risk assessment consists of an analysis and evaluation process of the risks associated with hazards in operations, and should be done systematically. The main objective in the risk assessment process is to rank the risky 1 Corresponding author mailto:scebi@yildiz.edu.tr IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 244 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 factors in the operations in order to provide risk elimination or reduction by applying protective measures from the most important risk to the least important risk. The first step of a risk assessment is hazard identification. The following steps in the assessment are risk identification, risk analysis, determination of precautions, and risk review, respectively. The determination of precautions is performed based on the risk magnitude obtained from the risk analysis step. In general, risk analysis methods use categorical scales and these scales are inadequate for the evaluation. For instance, let us assume that probability of occurrence and severity are 3 and 4 for Case A, 3 and 5 for Case B, and 4 and 4 Case C, respectively. If we use an L-type risk analysis method, risk magnitudes of these cases are obtained as 12, 15, and 16, respectively. Based on the risk evaluation procedure of an L-type matrix method, these results are categorized as high, very high and very high, respectively. Sometimes, a mere one point increase on any parameter may change the category of the risk. Furthermore, there are some gaps in the risk magnitude scale of the conventional methods since they use categorical data. For instance, in an L-Type risk matrix, the scores such as 5, 7, 11, 13, 14, [17, 19], [21, 24] are not obtained by producing any probability of occurrence or severity of occurrence. Therefore, in some cases, the sensitivity of the conventional methods to small changes can be pointless. In the scope of this study, a new approach is proposed in order to overcome this deficiency. In this study, after a wide literature review hazards in a warehouse are identified and grouped together to form a hierarchy. Then, interval valued intuitionistic fuzzy Analytical Hierarchy Process (IVIF-AHP) is utilized to obtain the weights of risks based on probability of occurrence and the severity in the warehouse. Then, these weights are used to assess risks in warehouse operations. In this study, since the evaluation process is based on the expert’s judgments and the collected data for the risk severity and probability of occurrence are in linguistic form, fuzzy logic is required for the calculation of risk magnitudes. Intuitionistic fuzzy sets are preferred because of their ability to better represent the expert’s opinions by using both membership and non-membership values. The preventive measures that should be taken first, the operations that should be stopped immediately and the processes that should be monitored are determined according to the results of the analysis. The originality of the paper is that the proposed approach presents a new perspective to risk evaluation in terms of occupational health and safety, and it is the first time an IVIF-AHP is applied to a risk evaluation procedure. 2. Literature review There have been several studies related to hazards in warehouses throughout the literature. Forklift accidents were examined by Larsson and Rechnitzer (1994) and Saric et al. (2013). In these studies, it was emphasized that a foot run over by a loaded forklift is a lot more dangerous than expected. It can cause severe trauma and fractures. Moreover, since they operate in confined spaces and make maneuvers within narrow aisles, forklifts can be dangerous for the pedestrians nearby. One of the most common forklift accidents involves a forklift striking a pedestrian and possibly leading to severe trauma or death. Some other forklift accidents include falling from/by forklift, collisions, overturns, and sudden stops (Larsson & Rechnitzer, 1994; Saric et al., 2013). Ren (2012) investigated logistics warehouse fire risk by using the Analytic Hierarchy Process. In the evaluation process, warehouse fire risk was examined under the four categories of warehouse building, goods, management, and environment. Tyldesley et IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 245 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 al. (2004) analyzed the benefits of fire compartmentation in chemical warehouses. Moreover, the cost-effectiveness of fire compartmentation with respect to other fire protection measures was emphasized. Markert (1998) evaluated the mitigation of the consequences of fires in chemical warehouses. In the study, the performances of four fire testing methods were compared to evaluate the toxicity of fire products. Moreover, the impact of the release of unburned pesticides and their pyrolysis products on human health was assessed. Qin et al. (2016) examined the feasibility of natural smoke extraction in warehouse buildings whereas Miles and Cox (1996) utilized a computational fluid dynamics model in order to assess hazards related to warehouse fires. Basahel (2015) examined work-related musculoskeletal disorders (MSDs) in warehouse workers. In the study, lifting and pulling activities in supermarket warehouses was analyzed by using Rapid Upper Limb Assessment and a pain self- report chart to reveal the relation between these activities and lower back, shoulder and lower arm pain. Furthermore, the heart rates of workers were continuously recorded to assess the physiological stresses of the activity postures. It was concluded that lifting activity significantly affects low back pain. Bouloiz et al. (2013) proposed a system dynamics model to show causal interdependencies among technical, organizational and human related safety factors. A behavioral analysis of safety conditions in a chemical storage unit was conducted by examining different scenarios through VENSIM software in order to enhance the safety of the system. 3. Method In this section, a new approach is proposed to the literature in order to eliminate or reduce the magnitude of any risk in warehouses. The steps of the procedure are as follows: Phase 1. Planning. In the scope of this phase, the following activities are executed. Step 1.1. Construction of a risk assessment team. Since most of the systems are complex, a risk assessment team whose members have technical expertise or extensive knowledge on the activities at the corresponding working environment has to be constructed. Furthermore, the team should consist of members who are familiar with risk analysis methods. Step 1.2. Definition of data collection procedure. In this step, plans are made about how to gather information and measure information output on a work environment and tasks are allocated to the team members. Step 1.3. Definition of hazard sources. Potential sources of harm or hazardous situations are identified. In this respect, all potential sources of danger including human related, hardware or machine related problems, and systematic errors should be inspected in the hazard identification process. Step 1.4. Definition of potential risks. One attempts to foresee all risks that are a possibility from any potential source. Phase 2. Analysis. In this phase, the risk magnitude is obtained based on the probability of occurrence and the severity. Step 2.1. Determining probability and severity weights. The main purpose of this step is to predict the probability of an undesired event causing the risks identified above. For this, the past statistics or expert views have been widely used in the literature. In particular, expert views are preferred when past statistics are not available. However, expert preferences are not precise and they include uncertainty and vagueness. Hence, IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 246 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 in this study, the probability and severity of the undesired events are obtained by using IVIF-AHP. The steps of IVIF-AHP are as follows (Wu et al., 2013): Step 2.1.1. Pairwise comparisons of hazards with respect to probability and severity are obtained by using the linguistic terms given in Table 1 and these linguistic terms are converted their corresponding interval valued intuitionistic fuzzy numbers. Step 2.1.2. From this pairwise comparison, score judgment matrix, �̃�𝑖𝑗 , is obtained by using Equation 1. �̃�𝑖𝑗 = �̃�𝑖𝑗 − �̃�𝑖𝑗 = [𝜇𝑖𝑗 𝐿 − 𝜗𝑖𝑗 𝑈 , 𝜇𝑖𝑗 𝑈 − 𝜗𝑖𝑗 𝐿 ], for all i, j=1, 2, . . . , n (1) Step 2.1.3. Then, interval multiplicative matrix, �̃�, is obtained by using Equation 2. �̃� = 10�̃� (2) Step 2.1.4. The priority vector of interval multiplicative matrix is calculated as follows: �̃�𝑖 = ∑ �̃�𝑖𝑗 𝑛 𝑗=1 ∑ ∑ �̃�𝑖𝑗 𝑛 𝑗=1 𝑛 𝑖=1 = [ ∑ �̃�𝑖𝑗 − 𝑛𝑗=1 ∑ ∑ �̃�𝑖𝑗 +𝑛 𝑗=1 𝑛 𝑖=1 , ∑ �̃�𝑖𝑗 + 𝑛𝑗=1 ∑ ∑ �̃�𝑖𝑗 −𝑛 𝑗=1 𝑛 𝑖=1 ] (3) Step 2.1.5. As �̃�𝑖 (𝑖 ∈ N) are interval numbers, comparison of each �̃�𝑖 with others is made and possibility degree matrix, 𝑃 = (𝑝𝑖𝑗 )𝑛𝑥𝑛, is constructed by using Equation 4. Let 𝑎 = [𝑎−, 𝑎+] and 𝑏 = [𝑏−, 𝑏+] be interval numbers. The possibility degree of 𝑎 ≥ 𝑏 is as follows: 𝑝(𝑎 ≥ 𝑏) = min {𝐿𝑎+𝐿𝑏,max(𝑎 +−𝑏−,0)} 𝐿𝑎+𝐿𝑏 (4) where 𝐿𝑎 = 𝑎 + − 𝑎− and 𝐿𝑏 = 𝑏 + − 𝑏−. Step 2.1.6. Prioritization of 𝑃 = (𝑝𝑖𝑗 )𝑛𝑥𝑛 by using Equation 5 to obtain weights and rank. 𝑤𝑖 = 1 𝑛 [∑ 𝑝𝑖𝑗 𝑛 𝑗=1 + 𝑛 2 − 1] (5) Table 1 Linguistic scale for evaluation Linguistic Terms [µL, µU] [𝒗L, 𝒗U] VH [0.6, 0.8] [0, 0.2] H [0.45, 0.65] [0.15, 0.35] E [0.3, 0.5] [0.3, 0.5] L [0.15, 0.35] [0.45, 0.65] VL [0, 0.2] [0.6, 0.8] IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 247 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 Step 2.2. Determination of risk category. To determine the risk category, the chart given in Table 2 is utilized based on the values obtained in Step 2.1. Table 2 Risk assessment matrix Severity ratio for a risk: WRS Likelihood ratio for a risk: WRP WRS≥0.08 0.08>WRS≥0.06 0.06>WRS≥0.04 0.04>WRS≥ 0.02 0.02>WRS ≥0 0.08WRP Category I Category I Category I Category II Category III 0.06WRP<0.08 Category I Category I Category II Category II Category III 0.04WRP<0.06 Category I Category II Category II Category III Category III 0.02WRP<0.04 Category II Category II Category III Category III Category III 0.0WRP<0.02 Category III Category III Category III Category III Category III The interpretations of the categories given in Table 2 are as follows: Category III: Insignificant. The risk may occur but it is not possible for it to result in any damage or injury. Category II: Marginal. The risk has a great potential to constitute a threat to injury or to result in a failure of the system. Category I: Catastrophic. The risk is quite high and has a great potential to cause serious damage or failure of the system. Phase 3. Risk evaluation and reduction. In this step, risk reduction, validation analysis, and an audit are conducted. Based on the risk magnitude, a set of control measurements are utilized in order to provide risk reduction. For the control measurements, one of the following strategies is preferred: i. Elimination of the hazard: The hazard source is omitted from the system in order to remove the hazard from the workplace. In order to achieve this, the process type should be changed. It is difficult to execute this strategy. ii. Substitution of the hazard: In this strategy, the substitute of the current process which includes less risk is preferred. iii. Hazard control: This strategy includes engineering applications, managerial applications, and personal protective equipment sub- strategies and these strategies are applied to reduce the current risk. 4. Analysis In the literature, some of the potential hazards in warehouse operations are identified as failure to conduct conveyor belt maintenance, vehicle exhaust fumes, not providing personal protective equipment to employees, falls from a height, slip and trips, undetermined forklift road lines, use of forklifts by employees without a driver’s license, potential explosion due to recharging of forklift truck batteries, overloading the forklift, and improper loading / unloading postures and movements of employees (Larsson & Rechnitzer, 1994; Saric et al., 2013; Example risk assessment for a warehouse, 2007; Basahel, 2015). Hazards in a warehouse are classified in Table 3, and then, the pairwise comparisons of these hazards are performed. IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 248 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 Table 3 Classification of hazards for warehouses H1 Physical and Chemical Hazards H11 Lighting H12 Air Circulation (for vehicle exhaust fumes) H13 Loud sounds H14 Temperature H15 Chemical materials H2 Mechanical Hazards H21 Failure to conduct conveyor belt maintenance H22 Failure to conduct forklift maintenance (refueling and periodic maintenance) H23 Overloading the forklift H24 Recharging of forklift truck batteries – potential explosion by release of hydrogen, spillage of acid H3 Workplace Hazards H31 Falls from a height (Working height) H32 Wet floors (Slips, trips, and falls) H33 Undetermined forklift / pedestrian road lines H34 Accidents caused by docks H35 Improperly stored materials H4 Human Related Hazards H41 Not providing personal protective equipment to employees H42 Use of forklifts by employees without driver’s license H43 Stretching the body by lifting heavy objects H44 Not following safety procedures for picking up, putting down and stacking loads H45 Not following safety procedures for speed limits of forklift Pairwise comparisons, obtained in the linguistic form for the hazards in warehouse, and corresponding consistency ratios are provided in Tables 4-13. Consistency ratios of the pairwise comparison matrices are calculated as in the classical AHP method by using the crisp numbers corresponding to these linguistic terms. IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 249 Vol. 10 Issue 2 2018 ISSN 1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 Table 4 Pairwise comparison of main hazards for probability Hazards H1 H2 H3 H4 H1 E VH H L H2 VL E L VL H3 L H E L H4 H VH H E CR 0.074 Table 5 Pairwise comparison of main hazards for severity Hazards H1 H2 H3 H4 H1 E VL L VL H2 VH E E VL H3 H E E VL H4 VH VH VH E CR 0.100 Table 6 Pairwise comparison of sub-hazards of H1 for probability H1 H11 H12 H13 H14 H15 H11 E L L H VL H12 H E H VH L H13 H L E H L H14 L VL L E VL H15 VH H H VH E CR 0.072 Table 7 Pairwise comparison of sub-hazards of H1 for severity H1 H11 H12 H13 H14 H15 H11 E L L H VL H12 H E H VH L H13 H L E H L H14 L VL L E VL H15 VH H H VH E CR 0.072 Table 8 Pairwise comparison of sub-hazards of H2 for probability H2 H21 H22 H23 H24 H21 E L VL H H22 H E L H H23 VH H E VH H24 L L VL E CR 0.076 Table 9 Pairwise comparison of sub-hazards of H2 for severity H2 H21 H22 H23 H24 H21 E L H VL H22 H E H L H23 L L E VL H24 VH H VH E CR 0.076 Table 10 Pairwise comparison of sub-hazards of H3 for probability H3 H31 H32 H33 H34 H35 H31 E L VL VL L H32 H E L VL H H33 VH H E L H H34 VH VH H E VH H35 H L L VL E CR 0.081 Table 11 Pairwise comparison of sub-hazards of H3 for severity H3 H31 H32 H33 H34 H35 H31 E VH H VH L H32 VL E L L VL H33 L H E H L H34 VL H L E VL H35 H VH H VH E CR 0.081 IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 250 Vol. 10 Issue 2 2018 ISSN1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 Table 12 Pairwise comparison of sub-hazards of H4 for probability H4 H41 H42 H43 H44 H45 H41 E H L VL L H42 L E VL VL L H43 H VH E L H H44 VH VH H E H H45 H H L L E CR 0.072 Table 13 Pairwise comparison of sub-hazards of H4 for severity H4 H41 H42 H43 H44 H45 H41 E H VH VH H H42 L E H VH H H43 VL L E H L H44 VL VL L E L H45 L L H H E CR 0.072 The probability weights and severity weights of these hazards are given in Tables 14 and 15. Then, a risk assessment is made by using Table 2 and categories of hazards are provided in Table 16. Table 14 Probability Weights H1 0.295 H2 0.161 H3 0.230 H4 0.314 H11 0.051 H21 0.036 H31 0.031 H41 0.054 H12 0.070 H22 0.043 H32 0.045 H42 0.042 H13 0.059 H23 0.054 H33 0.054 H43 0.074 H14 0.039 H24 0.028 H34 0.061 H44 0.081 H15 0.076 H35 0.039 H45 0.063 Table 15 Severity Weights H1 0.158 H2 0.270 H3 0.231 H4 0.341 H11 0.027 H21 0.061 H31 0.057 H41 0.088 H12 0.037 H22 0.072 H32 0.031 H42 0.080 H13 0.032 H23 0.047 H33 0.046 H43 0.059 H14 0.021 H24 0.091 H34 0.038 H44 0.046 H15 0.041 H35 0.059 H45 0.068 IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 251 Vol. 10 Issue 2 2018 ISSN1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 Table 16 Results of risk assessment in warehouses H1 Physical and Chemical Hazards H11 Lighting Category III H12 Air Circulation Category II H13 Loud sounds Category III H14 Temperature Category III H15 Chemical materials Category II H2 Mechanical Hazards H21 Failure to conduct conveyor belt maintenance Category II H22 Failure to conduct forklift maintenance (Refueling and periodic maintenance) Category II H23 Overloading the forklift Category II H24 Recharging of forklift truck batteries – potential explosion by release of hydrogen, spillage of acid Category II H3 Workplace Hazards H31 Falls from a height (Working height) Category III H32 Wet floors (Slips, trips, and falls) Category III H33 Undetermined forklift / pedestrian road lines Category II H34 Accidents caused by docks Category II H35 Improperly stored materials Category III H4 Human Related Hazards H41 Not providing personal protective equipment to employees Category I H42 Use of forklifts by employees without driver’s licence Category I H43 Stretching the body by lifting heavy objects Category II H44 Not following safety procedures for picking up, putting down and stacking loads Category I H45 Not following safety procedures for speed limits of forklift Category I As a result of the proposed assessment, the most critical hazards are identified as H41, not providing personal protective equipment to employees; H42, use of forklifts by employees without driver’s license; H44, not following safety procedures for picking up, putting down and stacking loads; and H45, not following safety procedures for speed limits of forklift. Since these hazards are identified as catastrophic, operations or activities involving these hazards must be terminated immediately until these hazards are eliminated. Marginal hazards in warehouses are identified as H12, air circulation; H15, chemical materials; H21, failure to conduct conveyor belt maintenance; H22, failure to conduct forklift maintenance; H23, overloading the forklift; H24, recharging of forklift truck batteries – potential explosion by release of hydrogen, spillage of acid; H33, undetermined forklift / pedestrian road lines; H34, accidents caused by docks; and H43, stretching the body by lifting heavy objects. Since these hazards have a great potential to IJAHP Article: Cebi, Ilbahar/Warehouse risk assessment using interval valued intuitionistic fuzzy AHP International Journal of the Analytic Hierarchy Process 252 Vol. 10 Issue 2 2018 ISSN1936-6744 https://doi.org/10.13033/ijahp.v10i2.549 constitute a threat in a warehouse, even if activities involving these hazards are not terminated, they must be constantly monitored. The rest of the hazards are identified as insignificant, indicating that they can be neglected. 5. Conclusions Warehouses are significant components of a supply chain management system. Efficiently functioning warehouses facilitate the ability of companies to carry out their operations smoothly. An accident occurring in a warehouse can damage both the health of the employees and the operations of the company. Therefore, identification of potential hazards in a warehouse and classification of these hazards are required to be able to take necessary actions. In this paper, a new approach in which hazards are categorized based on probability and severity weights calculated through IVIF-AHP is proposed. The advantages of the proposed method can be explained as follows: (I) It includes an expert inference system to obtain risk magnitude. As distinct from the matrix type risk assessment method, this method presents robust and sufficient results for a safety specialist. (II) The risk matrix utilized to obtain the risk magnitudes presents a sensitive and adequate scale. (III) The results obtained from the analysis are more comprehensive than the conventional methods. In a work environment, some activities might be dependent on each other and the obtained risk magnitude for these activities can be affected by these interdependencies. Therefore, in future research, the proposed method can be extended to evaluate the interdependencies among the risks in a work environment. 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