Journal of Health and Safety at Work

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Introduction: In addition to direct and indirect costs of occupational accidents imposing on production companies, they impact the productivity of labor, too. However, gaining more profits and having less costs is always the main concern among industrial managers. Considering safety measures can be effective way to reduce occupational accidents and costs as well as negative impacts on production systems.

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Material and Method: In this paper, a risk assessment method using fuzzy and MATLAB software is presented to determine the safety level of production environments. The main parameters of this model include three items: accident probability, accident severity and current safety level. For this purpose, the statistical data of accidents and their causes published by Social Insurance Organization have been used in this study. Furthermore, expert judgments of safety and health professional have been used to determine the severity of accidents. In the fuzzy method, the Mamdani deductive fuzzy model has been adapted due to its easy applicability. Application of the model has been shown using a practical instance.

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Result: The defuzzified value for RL is found to be 3.48. Linguistic risk level expression is 100% substantial high risk that is full membership for fuzzy average set.

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Conclusion: The application of the proposed method can reveal which safety items and factors are most important in improving workers safety, and therefore decide where to concentrate resources in order to improve the safety of the work environment.

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Introduction: Due to the increasing population and the need for setting in cities, we witness an increase in high-rise building in Iran. Moreover, because of the ambiguity and complexity, they have various risks potential. Health problems are among this risks for the residents. These risks have short term or long term effects,which can cause illness or even death.

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Material and Method: In the present study, health risks in high-rise buildings are identified, assessed and ranked. Health issue are identified by conducting interview with experts in high-rise building an using specific health and safety related checklists. Due to ambiguous nature of risks and existence of uncertainly, fuzzy logic technique with trapezoidal distribution was used for quantification. Finally, after risk evaluation and calculation of critical degree of each risk, the risks were ranked.

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Result: Risk factors obtained over 0.5 for most of the risks that indicate the importance of Health in high-rise projects during construction phase. The results also showed that the health risks should be assessed before the start of the project in order to reduce or eliminate their impacts.

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Conclusion: Safety risks in High-rise Building projects is very important. These risks have many impacts directly and indirectly on the time, quality and costs of projects. Therefore, evaluating and controlling each health risk in the design and implementation phases are essential. Most of the risks factors identified in this study, can be prevented by using personal protective equipment. The role of the training people involved in this projects are essential to use personal protective equipment.

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Introduction: Due to the presence of extreme hazard sources and high intrinsic risk in refineries and process industry sectors, different layers of protection are being used to reduce the risk and avoid the hazardous events. Determining Safety Integrity Levels (SILs) in Safety Instrumented Systems (SISs) helps to ensure the safety of the whole process. Risk Graph is one of the most popular and cost effective techniques to do so. Despite Risk Graph simplicity it’s a qualitative method which is highly subjective and suffers from interpretation problems that can lead to inconsistent or conservative SILs.

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Material and Method: In this paper, Improved Risk Graph (IRG) method was presented and evaluated, and using Fuzzy Logic a novel approach namely Fuzzy Improved Risk Graph (FIRG) was suggested. In the proposed method consequence levels which were defined as qualitative terms were transformed into quantitative intervals. Having those numerical values, risk graph table was converted to a quantitative one. Finally, applying the presented approach and using three experts’ opinions and attributing weight factors, an ultimate numeric value was produced.

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Conclusion: as a result of establishing the presented method, identical levels in conventional risk graph table are replaced with different sublevels that not only increases the accuracy in determining the SIL, but also elucidates the effective factor in improving the safety level and consequently saves time and cost significantly. The proposed technique has been employed to develop the SIL of Tehran Refinery ISOMAX Center. IRG and FIRG results have been compared to clarify the efficacy and importance of the proposed method

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Introduction: Air health is an important environmental issue which has been endangered in recent years due to application of advanced technologies used for improving the financial welfare and relative prosperity of humans. Making use of pollution control systems and refinement methods are some general ways to control environmental pollution. Since several different techniques of control, each with its advantages and disadvantages are employed in order to mitigate the spread of air pollution, the aim of current study was to design a fuzzy multi-attribute decision making model to select the most appropriate air pollution control equipment in Mashhad Shargh Cement Company.
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Material and Method: After identifying the desired industry and also the production process, all factors affecting decision-making process including environmental factors, technical factors and economic factors were considered by utilizing Fuzzy Analytic Hierarchy Process method. Importance weight of these criteria was calculated and subsequently the priority of model choices were also determined using this approach.
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Result: Among main criteria of the model, economic criteria was identified as the most important factor influencing the selection of the type of air pollution control equipment, with the wight of 0.555. Environmental and technical factors with weighting of 0,286 and 0,159 also gained the next priorities, respectively. Final weights of Electro filter, Baghouse and Hybrid filter technologies were calculated 0.256, 0.415 and 0.329 in cement mill unit and 0.291, 0.374 and 0.334 in material grinding and furnace unit, respectively.
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Conclusion: Finally, the proposed model that is based on the Fuzzy Analytic Hierarchy Process indicates that the Baghouse Technique is the most appropriate technique for the purpose of dust filtration in major sources of air pollution spread in Shargh Cement Company.

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Introduction: High-rise building projects are increasing due to the population growth, urban development, and migration of people to the major cities. High-rise buildings have special importance in terms of HSE risks rather than other projects since these projects are located in the cities and in the direct contact with people. However, in most incidents and events, organizations do not have enough insight into the true cost. Therefore, identification and assessment of management of HSE risks is essential.

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Material and Methods: In this research, HSE risks in high-rise buildings that have harmful effect on human health and environment were identified, assessed and ranked. The Risks were identified and assessed through checklist and interview with experts. Considering the uncertainty and the ambiguous nature of the risks, the combination of fuzzy numbers and Analytical Hierarchy Process (AHP) method were employed for quantitative analysis. Finally, the estimated risks were ranked for control.

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Results: Using AHP Method, the weight of health, safety, and environment were obtained 0.346, 0.3, and 0.354,respectively, which shows the higher importance of environmental and health risks in construction projects comparing to safety risks.

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Conclusion: Findings in this research indicated that HSE risks are very critical and they should be controlled before start of the project. Moreover, many of HSE risk are due to lack of appropriate HSE culture in the organization and projects that can be reduced by culture-building practices.

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Introduction: Electrical industries are among high risk industries. The present study aimed to assess safety risk in electricity distribution processes using  ET&BA technique and also to compare with both VIKOR & TOPSIS methods in fuzzy environments.
 

Material and Methods: The present research is a descriptive study and ET&BA worksheet is the main data collection tool. Both Fuzzy TOPSIS and Fuzzy VIKOR methods were used for the worksheet analysis.
 

Result: Findings revealed that overhead low and medium voltage power distribution networks had the highest risk among the other network types of transmission and distribution of electricity. Also, it was found that TOPSIS and VIKOR methods are appropriate to rank the safety risks with somehow similar results.
 

Conclusion: The height and electricity are of the main causes of accidents in electricity transmission and distribution industry which caused the overhead power networks to be ranked as high risk. Application of decision-making models in fuzzy environment minimizes the judgment of assessors in the risk assessment process.

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Introduction: Nowadays, gas and oil account for 60 percent of world energy resources. Transporting crude oil and its products are accomplished through a number of ways among which pipelines are of the utmost significance. Considering the extent of pipelines in installation and residential areas and also high potential for damage, the safety of these pipes and application of risk management principles have undeniable importance. Bow-tie risk assessment method is one of the ways to determine safety level. The tool is a qualitative and semi-quantitative method the data of which are implemented by specialists and experts via conducting surveys.
 

 Method and material: In the present study, Bow-tie technique was employed having been combined with fuzzy logic in which Likret Scale was applied to quantify the qualitative (verbal) data to reduce the uncertainty of risk evaluation of Amaak No.10 gas pipeline and Bongestan No.12 petroleum pipeline. In this way, factors affecting the pipeline safety were at first, recognized through the checklists. Then, the risk evaluation of pipplines was conducted using the mentioned method.
 

Results: The results of the study showed that third party damages, initial defects in materials, and constructing pipeline with failure possibility of 0.0484 stood at the highest in terms of importance (equivalent to 12.32%) in destroying oil and gas pipelines. In addition, the toxic impacts and environmental damages with occurrence possibility of 0.00327 were the most striking consequences of gas and oil leakage based on event tree analysis.
 

Conclusion: Considering the recognized factors leading to destruction of pipelines and their most notable outcomes, instructions on how to control and reduce the potential consequences were suggested, with emphasis on the removal of the most probable causes.

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Introduction: Resilience engineering (RE), as a new approach in the system safety domain, is intended to preserve the performance of socio-technical systems in various conditions; and accentuates the positive activities instead of the failure modes. The aim of this study was to develop a new framework for safety assessment on the basis of RE, using the Fuzzy Analytical Hierarchy Process (AHP) method.  

Material and Method: Current study is an analytical cross-sectional survey performed in a petrochemical industry. Initially, six RE indicators were selected, including top management commitment, just culture, learning culture, awareness, flexibility and emergency preparedness and accordingly an assessment framework was established. Then, the selected RE indicators were evaluated and validated by experts in a specialized panel. Following, an indicator was proposed named “resilience early warning indicator”. Finally, the RE indicator score of the total process was determined using the fuzzy evaluating vector.   

Result: Findings revealed that top management commitment and learning indicators have the most and the least effects on the RE level of the process, respectively. Besides, the flexibility (C3) indicator was located in orange early warning zone (OEWZ) while other indicators were positioned in the no early warning zone (NEWZ). Furthermore, the overall resilience level of the process was evaluated as level III (NEWZ).

Conclusion: Management commitment and emergency preparedness are two main indicators of RE and can carry out the most important effect for remaining the RE in the NEWZ level.

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Introduction: To evaluate heat stress in the workplace different indices are used. But, none of these measures have been widely accepted. The aim of this study was to determine effective criteria in selecting a heat stress index and weighting of these criteria.

Material and Method:  This study is a qualitative study that was designed and conducted within 10 stages. In the current study, effective criteria for choosing a heat stress index was determined by using Delphi technique and expert’s opinions (30 people), and then the fuzzy analytic hierarchy process was used for weighting and prioritization of these criteria.

Results: Analyzing the completed questionnaires by the experts and according to the percentage of respondents, 11 criteria were finally selected. “Simplicity” criteria by %76.6 had the highest percentage of response. But, the relative weight of this criteria was 0.041, and had the lowest weight after the “low cost” criteria.  The criteria relating to the “Standard” item was 0.141as the highest relative weight.

Conclusion: It can be concluded that the first step to have a reliable and accurate measurement is to choose a proper and correct index. Based on specialists and expert’s opinions, standardization of the index is the most important selection criteria. Other criteria that must be considered were accuracy, reliability and good correlation with the physiological strain indices.

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Introduction: FMEA method is one of the most used techniques in risk assessment and prioritization. But, due to several reasons, its application has been limited to the real-world settings. The aim of this study was to deal with these restrictions using the combined fuzzy (in terms of the Z-numbers) and grey (in terms of the grey relational analysis) theories.

Material and Method: The current study is an analytical cross-sectional survey that was performed to prioritize the failure modes of the overhead cranes. Initially, an FMEA team including 4 specialists was established. Then, the opinions of the team members were gathered in terms of the Z-numbers and the weights of the risk factors (O، S, and D) were determined using the fuzzy AHP method. Finally, the failure modes were prioritized using the GRP method.

Result: From 13 cases of the identified failure modes, the conventional FMEA was assigned equal priority to the 7 cases and as a result 9 risk priorities were determined. But, in the proposed method, because of the elimination of the restrictions of conventional FMEA, 13 risk priorities were assigned to the failure modes.

Conclusion: Relying upon the fuzzy AHP, Z-numbers and GRP method, the proposed method dealt with the equal weights of the risk factors, fuzziness of the data (expert’s judgments) and the prioritization of the failure modes. The proposed method has more capabilities in relation to the conventional FMEA for prioritization of the failure modes.

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Introduction: Safety in construction needs not only operating the executive laws and instructions but also the safety culture of all the workers in workshops. Safety culture is a factor by which all the workers are committed to having a positive share in the safety of their coworkers and themselves. Therefore, the aim of this study is identification of safety culture factors and ranking occupations in jobsites in order to improve the safety condition and promote the safety culture of high-rise projects.

Material and Method: In this descriptive-analytical study, first, safety culture criteria in construction projects are identified by a literature review. Then, 8 factors of safety culture are weighted using fuzzy analytic hierarchy process. Finally, 10 different occupations in high-rise workshops are ranked from the point of view of safety culture using fuzzy TOPSIS method.  

Result: Results of ranking the criteria show that the most important criteria are safety attitude, supervision, policy of organization and safety training. Moreover, in high-rise construction the site superintendent and supervisor occupations have the highest and laborers have the lowest safety culture.

Conclusion: In this study, after evaluating different construction occupations by hybrid FTOPSIS-FAHP method, the results are compared with the results of previous researches. Here, it was found that the findings are consistent with previous studies. On the other hand, low level of safety culture of construction laborers among the investigated occupations shows weakness in safety training and attitude; hence, the factors such as more safety supervision and training must be considered in order to create a positive safety culture for the workers.

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Introduction: Resilience engineering is a novel approache to risk management and is the inherent ability of a system to adapt their work before, during and after the changes and adverse events in such a way that maintain the system performance under predictable and unpredictable conditions. The aim of this study was to identify indicators of organizational resilience of refineries and ranking them using fuzzy TOPSIS technique.  

Material and Method: A qualitative study was done to identify organizational resilience indicators of refinery complex. The main method of data collection was semi-structured interviews. Indicators were determined using qualitative content analysis and literature review. Weighting and ranking identified indicators was performed using fuzzy TOPSIS technique.   

Result: Eleven indicators were identified as follows: management commitment, performance management system, flow of information/communication, involvement culture, error management culture, education, preparedness, flexibility, innovation culture, change management, and human resource management.

Conclusion: Critical sociotechnical organizations especially refinery complexes in order to improve safety management and resilience situation should focus on effective indicators. Monitoring and improving them will increase safety and the resilience level of organization

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Introduction: Choosing maintenance strategy is one of the most complex and essential processes that can affect the safety and cost of equipment. The main aim of this study was to determine a risk-based maintenance policy for improvement of the safety and maintenance indices.

Material and Method: According to literature reviews and constraints associated with the studied industry, a number of safety and maintenance indices were selected and their values were measured. Next, in order to promote the selected indices, the best policy was implemented on nine critical machines of the company based on criteria such as cost, risk and availability in the framework of the fuzzy network analysis process. Finally, after six months period, the indices were re-measured. The Wilcoxon test was used to assess the changes in the indices.

Result: In the implementation of the model, condition based maintenance was more effective than other strategies. Following the intervention, the improvement of safety and maintenance indices was statistically significant. The statistical analyses demonstrated that indices like reliability, availability, mean time between failures, and the number of dangerous failures all were improved significantly (P<0.05).

Conclusion: The results showed that the simultaneous use of three criteria, i.e. cost, risk and availability in maintenance planning could reduce equipment-related accidents. Finally, the recommended model can improve the efficiency and competitiveness of organizations by increasing availability and reducing equipment costs

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Introduction: Safety at workplaces is an important issue, and lack of effective and efficient safety management methods based on scientific studies could cost the construction industry. An effective accident investigation and root causes analysis could prevent the occurrence of incidents at minimum cost and time.
Material and Method: First, major accidents in road construction projects were identified by interview and literature reviewing techniques. Then, fault tree was drawn for each main risks. In the next step, in order to calculate occurrence probability and severity of each accident type, a questionnaire was designed and distributed among the participants. Fuzzy logic was employed in calculations, due to the existence of uncertainty in linguistic variables. Fuzzy Fault Tree Analysis (FFTA) was used for calculating the occurrence probability, and importance of each criterion was determined using Fuzzy Analytical Hierarchical Process (FAHP) to calculate the severity of each accident. Finally, risk factors for each accident type was calculated and the risks were ranked accordingly.
Result: Accidents related to crusher and asphalt plant, traffic accidents, heat exhaustion and lack of hygiene and hit by machinery were identified as the most important risks among the eleven investigated accident types.
Conclusion: The findings in this research and also implementing effective safety management techniques, could be helpful on reduction of the probability of accidents root causes and to mitigate related risks.

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Introduction: Noise is one of the most harmful industrial agents and there are different methods to control it. Fuzzy analytical hierarchy process is an appropriate technique for selecting the best choice among several control methods. Therefore, the aim of this study was the selection of the most suitable sound control method using fuzzy hierarchical analysis (FAHP) technique in a refinery plant.
Material and Method: The present study was a cross-sectional research in a refinery plant. After identifying the main sources of the noise in the studied palnt, five criteria and ten noise control methods were selected using a questionnaire and Delphi methods. Then, Fuzzy hierarchy analysis was applied for the selection of the best noise control alternative.
Result: The results showed that the performance with a final weight of 0.277 and the non-interference in the process with a final weight of 0.06 were most and least important criteria, respectively. Meanwhile, worker enclosure had highest score (0.207) of the control methods.
Conclusion: In general, the results showed that best criterion for selection of the suitable noise control method is performance. What’s more, based on the results, worker enclosure was selected as best noise control method in the refinery.

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Introduction: Working in hot and harsh weather conditions can cause heat related diseases and in some cases, even can lead to death. Risk assessment of heat stress in these environments is of particular importance. As there are many factors that could affect the heat stress, therefore, an index should be applied that could properly reflect the effect of all of these factors.
Material and Method: Initially a five-member expert team was established. Then, the weight of each variable was determined by the fuzzy analytical hierarchy process (FAHP) method. In next step, five work stations of the casting process evaluated applying fuzzy TOPSIS (FTOPSIS) method and the risk of heat stress prioritized in these stations. Lastly, the Pearson’s correlation coefficient was used to determine correlation between the results of proposed method with WBGT index.
Result:  The weights of three main variables including task characteristics, working environment, and worker characteristics was determined as 0.279, 0.526, and 0.195. The risk priority of the five work stations including, stocking, melting furnace, pouring and casting, polishing, and warehousing was established as S1= 4, S2= 2, S3= 1, S4= 3, and S5= 5. The Pearson’s correlation coefficient between the similarity index (CCi) and WBGT was 0.97.
Conclusion: From three main variables that can affect the heat stress, “Working Environment” has main impact in the risk assessment process; therefore, the most efforts must be focused on controlling this variable. The proposed method in this study has the capability of concurrent quantitative and qualitative assessment of factors that could affect the heat stress and can minimize the uncertainties in the risk assessment process relying upon the fuzzy sets.

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Introduction: Skin disease caused by exposure to the chemicals is one of the major health-related problems in the workplaces. This study has done to prioritize the strategies for skin exposure with chemical in a painting company.
Material and Method: In this analytical cross-sectional study 7 criteria and 8 selection control methods were initially chosen by surveying the existing records and through the assessments of expert panel and checking the result of previous studies. Subsequently, control strategies were prioritized according to the criteria using Fuzzy Analytical Hierarchy process & Topsis.
Result: Results of the paired comparison showed that the safety of the control strategy (w=0.298) and it’s up to date (w=0.0138) were the most and least important criteria for skin control strategies. Among skin control strategies for chemical exposure, the highest and lowest importance were for training (w=0.817) and work-rest schedule (w=0.233), respectively.
Conclusion: In this study, training was determined as the best control strategies for skin chemical exposure in the studied painting company according to the investigated criteria. This decision-making process could be applied for promotion of the skin health among workers.

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Introduction: Todays, the improvement and optimization of the safety performance are essential and important for control and prevention of accidents in the industry. The purpose of this research was to assist a hybrid cycle power plant for identification and prioritization of the influencing factors in enhancing safety in order to reduce risks and to improve system performance.  
Material and Methods: In this descriptive-analytical study, influencing factors were classified within three main categories of human, equipment, and managment, and 14 sub-factors was screened and selected by experts using Fuzzy Delphi method. Then, fuzzy DEMATEL method was adopted to determine the relationships, the intensity of affecting and being affected factors, and the analytical network process method for weighting and prioritization the factors.
Results: The findings of the fuzzy DEMATEL method showed that “Managerial”, “equipment” and “human” factors are respectively influencing factors on the improvement of safety performance. “Managerial factors” is the most influencing and “Human factors” is the most influenced one. Based on the results of fuzzy analysis network process method, “human factors” is the first priority among the main factors, and “employee motivation”, “system of control and prevention”, “work team spirit”, “individual skills” and “Individual protection equipment” sub-factors are respectively the first to fifth priorities were according to their weight.
Conclusion: “Human factors” re the most influenced factor and the main problem of the organization, which can be improved by the most influencing “managerial” factor. The success or failure of the safety performance in the power plant depends on better management of the “human factors” and managers need to motivate employees to improve safety performance.

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Introduction: Evaluating environmental risks in the oil and gas industry is essential to prevent irreparable damage to the environment. Using classical methods for prioritizing environmental risks does not achieve high-reliable results. Therefore, the aim of this study is to minimize the limitations of classical methods in a typical oil and gas production zone, by using fuzzy logic and Multi Attribute Decision Making (MADM) approach.  
Material and Methods: After forming an identification and assessment team including experienced experts from different organizational units in a region of exploitation of oil and gas, values of each risk factor (likelihood of occurrence, severity and detectability) related to identified environmental risks are determined according to their qualitative opinions represented by linguistic variables. Relative weights of the risk factors are calculated by applying the group Analytic Hierarchy Process (AHP) in a fuzzy environment on expert opinions. Then, fuzzy aggregation in the linear form by considering the weight of the risk factors and a method that is developed based on the center of gravity are employed in evaluation and ranking of the risks.
Results: In this study, the severity factor has the most important contribution in risk assessment compared to the other risk factors, since it has the highest relative weight. Raw sewage aspect resulted from absence of appropriate treatment system has the highest priority and spilling over of acid that is caused by chiller cleaning stands at the second position in the identified environmental risks.
Conclusion: The results demonstrate that although the proposed methodology requires greater time than classical methods, it is able to determine the risk ranking more practically because of minimizing the limitations of classical methods: high sensitivity to judgmental errors, considering some risks in the same index group and ignoring uncertainty in experts’ opinions. Proposed method is a proper alternative for classical environmental risk assessment technique, and capable of prioritization and evaluation risks in terms of safety and health.

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Introduction: Damage to occupational health is one of the major challenges in the industry. Various studies have shown that productivity in industries has a significant relationship with occupational health. In addition, employee’s health in the workplace can be affected by a variety of variables i.e., job stress, job satisfaction, and work in unconventional shifts. Therefore, the purpose of this study was to evaluate the causal relationships of shift work, job stress, job satisfaction with the occupational health level in a petrochemical industry.
Material and Methods: This cross-sectional study was implemented in 2017. The study sample consisted of 20 HSE experts selected using purposeful judgment sampling. A 4×4 matrix questionnaire consisting of four main parameters i.e., shift work, job stress and job satisfaction with occupational health level, was used for data acquisition. Data analysis was done using MATLAB software and Fuzzy DEMATEL method. Also, for each variable, two key values of D+R and D-R were calculated. These values show the degree of interaction and the type of interaction of the variable with other variables, respectively.
Results: Sixty percent of the experts participating in this study were male and 40.0% were female. Only 10.0% of the participants had a PhD degree. In addition, the mean age and the mean work experience of the subjects were 39.64±9.34 and 10.22±7.10 years, respectively. The parameters of shift work and job satisfaction were identified as an effective factor due to the positive values of D-R while occupational health variable with negative value of D-R, was considered as an affected factor. In addition, these results showed that the effect of these parameters on health is different with both direct and indirect mechanisms.
Conclusion: Using the Fuzzy DEMATEL method, our findings indicated that occupational health in the large industries can be influenced by different parameters with different sizes. Considering the interactions among these parameters in health analysis and the affecting factors, therefore, is very important. So, the health level in challenging industrial environment such as petrochemical industries can be affected by shift work as a root cause. This root cause, along with job satisfaction, has a significant effect on increasing stress levels and reducing health levels. Accordingly, any action to increase the health level should focus on improving shift patterns and increasing the level of job satisfaction of employees as a pivotal root and affecting causes on health level.