Occupational musculoskeletal disorders management using Fuzzy TOPSIS Assessment of Repetitive Tasks (ART)

Abstract

BACKGROUND: In order to evaluate occupational disorders and ergonomic problems in a workplace, Multiple Criteria Decision Making (MCDM) problem solving methods such as Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) can be utilized.

OBJECTIVE: In this paper, Musculoskeletal Disorder (MSD) risk factors were evaluated in a manufacturing company in Iran by a method called Assessment of Repetitive Tasks (ART) of the upper limbs integrated with Fuzzy TOPSIS in order to prioritize the corrective actions.

METHODS: This study was done with a descriptive-analytical approach. The company under study had 240 employees who were working in seven different shops. Out of all tasks, 13 tasks were included in the study. Required information was gathered by a demographic questionnaire and ART method. Also, Fuzzy TOPSIS was utilized for the prioritization of the company shops based on the ergonomic control needs.

RESULTS: Data analysis from ART indicated that 74.6% of the reviewed tasks were high risk. Based on the F- TOPSIS-ART results, Production shop prioritized as the highest need for MSD control.

CONCLUSIONS: Because there is time and financial resources limit in ergonomic control activities, a fuzzy prioritization approach such as Fuzzy TOPSIS ART can be used to take advantage of the available resources and control risks to as low as reasonably practicable (ALARP) level.

Keywords

MCDM decision-making posture occupational ergonomics TOPSIS

1 Introduction

Automation and technology advancement have changed the way employees work in factories. Work-related musculoskeletal disorders (WRMSDs) in upper limbs have been boosted during the recent decades. Subsequently, it puts more pressure on workforces.

Long time working in non-ergonomic stations and keeping awkward postures may lead to muscles fatigue in back, shoulder, and neck. WRMSDs cause 34% of Lost Work Day (LWD) in the US [1] that shows how workforces are being deteriorated by repetitive tasks. Studies shows that, in 2000, direct cost of WRMSDs in Iran was around 1.13% of the national budget [2]. On the other hand, indirect cost such as: decrease in production, quality, productivity and loss of customer satisfaction were estimated to be four times more than the estimated direct costs [3]. Therefore, optimizing environment and workplace conditions to make a balance between employees and workplaces conditions is a big deal for ergonomic specialists. Considering ergonomic principles in workplaces may solve many issues and bring safer and healthier conditions for employees resulting in higher productivity for the organization [4]. Repetitive movements, high force exertion, awkward postures, vibration and static works may result in WRMSDs that a comprehensive action plan should be utilized to minimize the risk factors [5].

Repetitive movements are prevalent and one of the most important causes of musculoskeletaldisorders [6]. In order to manage the effects of these sorts of disorders, it is critical to prioritize factors/criteria based on their importance. Subsequently, corrective actions should be implemented in the form of a reasonably defined plan such as: PDCA (Plan, Do, Check, Act) cycle [7]. Decision-making is a process of finding the best among different alternatives. Nearly, all decision-making cases face challenges due to multiple criteria involved in the assessments. In fact, other activities such as planning, organizing and controlling, are all based in decision making. That’s why decision-making is the main focus in management. However, using expert systems and decision-making supportive systems are progressing in various sciences [8, 9], systematic decision making is practiced rarely in Iran, as a developing country, and few papers can be found in this field, especially in the field of ergonomics and managing its risk factors [10 –12]. Researchers in the field of decision making have concentrated on Multiple Criteria Decision Making (MCDM) during recent decades [13]. In most cases of decision-making, managers optimize a bunch of criteria both qualitative and quantitative, such as: maximizing benefits, job satisfaction and productivity or minimizing workload. It is obvious that these criteria are not comparable and are not even in contrast because of their nature of having different scales. For an alternative, a rise in one of these criteria may result in the reduction of another one. Accordingly, in MCDM it is desirable to find an optimum alternative in which all criteria are in the best state. MCDM utilizes mathematical analysis to formulate knowledge systematically. Then, it presents the results based on mathematical functions. Although Weights of criteria are practiced in conventional MCDM methods, the results come with uncertainty. As subjective estimations made by humans are vague, classical MCDM methods are not the most efficient choice to make decision in these cases [14]. To overcome this problem, fuzzy logic has been used [9]. When there are lots of factors with high complexities, fuzzy logic is utilized. Fuzzy sets were presented by Zade in 1965 [15].

Most decisions are made in a situation in which the pertinent data and the sequences of possible actions are not precisely known. Therefore, it is very important to adopt fuzzy data to express such situations in decision-making problems. Many studies have been conducted using fuzzy TOPSIS in various fields. Chen and Wang used fuzzy numbers in TOPSIS first in 1992 and developed Fuzzy-TIOSIS [16]. Considering TOPSIS as a well-known classical technique to find solutions in management, a fuzzy approach makes it less subjective and more appealing to solve problems [17, 18].

In the field of ergonomics, there are various methods, such as: RULA, REBA, LUBA and OCRA to analyze ergonomic risk factors, but number of factors assessed by them is limited. On the other hand, ART method is a comprehensive method to study repetitive tasks based on 13 different criteria. In real world, companies face limited time and financial resources to control occupational ergonomic risk factors. Therefore, there is a question for a decision maker to identify which unit of a manufacturing company is more important to start corrective actions. Definitely, ART method as an ergonomic assessment tool cannot answer this question. Prioritization of the corrective actions is needed beside ART method. Therefore, in this study ART method was combined with MCDM method (TOPSIS) and Fuzzy logic as F-TOPSIS-ART to get better and more reliable results. F-TOPSIS-ART is a method to both assess the ergonomic risk factors and prioritize the action plans needed to control risk factors. In this study, F-TOPSIS-ART determines the high priority shops in a manufacturing company that are in need of ergonomic control measures. This comes more vital when there is a tight budget and limited time to control the identified risk factors. That’s why a Multi Criteria Decision Making (MCDM) method such as Fuzzy TOPSIS is utilized the steps of this method is illustrated in Fig. 1. In the field of fuzzy logic, trapezoidal fuzzy is more applicable than other sorts of fuzzy numbers [19]. So, data was assumed trapezoidal in the study.

The present research assessed ergonomics risk factors in an Iranian manufacturing company during the year of 2014. Prioritization of the needed corrective actions was done based on Fuzzy TOPSIS ART results.

2 Methods

This cross-sectional study was done in a manufacturing company with 7 shops that employed 240 Thirteen tasks were identified to be studied and prioritized based on the previous Job Hazard Analysis (JHA). These tasks were mostly resulting in occupational disorders such as: arthritis, disc herniation, fracture and pain.

Participants were interviewed and data was gathered in a self-reporting manner. A questionnaire was used to gather demographic data such as: age, sex, work experience, ergonomic, and/or work-related trainings. Ergonomics risk factors were assessed by utilizing assessment of repetitive tasks (ART) of the upper limbs method. This tool was developed by health and safety laboratory in collaboration with Health and Safety Executive (HSE) in England. It is an acceptable technique to survey upper limbs in repetitive tasks [20]. Its efficiency and utilization were approved in the past studies [20]. ART contains four main stages [21]: frequency and repetition of movements, force, awkward postures and additional factors. These factors are evaluated based on both qualitative and quantitative criteria. In a qualitative analysis, they will be sorted into three groups of: Green color or Low, Amber color or Medium and Red color or High level of risk. But in quantitative one, each situation will have a specific score and final score is within the range of 0–72. Zero to indicate Low risk, 12–21 shows Medium and more than 22 is Highrisk [21].

The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is a method to reach the optimum solution by getting close to the ideal alternative. This technique has two basic facts. First, the desirability of each criterion should be in a way that more rij be the better the ideality and vice versa (their value needs to be steady). Then, the best value of criterion is its (positive) ideal and the worst value is its negative ideal. Secondly, distance of an alternative from the ideal (or from negative ideal) can be calculated using Euclidean distance (from the power of two) or like the sum of absolute magnitude from linear distances. It depends on exchange and replacement rate among criteria.

Based on TOPSIS concepts in Multi Criteria Decision Making problems, fuzzy ideal solution and fuzzy negative ideal solution were defined. Next was the fuzzy numbers of ranking approach; the distance between two fuzzy numbers was calculated. Using this method, distance of each alternative (production shops in this study) from fuzzy ideal solution to fuzzy negative ideal solution was measured. Finally, closeness coefficient (CC) was computed and alternatives have been put in priorities for corrections. Higher amount of CC shows a closer alternative to fuzzy ideal solution and more distance from fuzzy negative ideal solution [19, 22].

It should be noted that Fuzzy TOPSIS steps are essential to discard less important shops in the study. Based on this technique, manufacturing shops that were in more demand of ergonomic risk reduction efforts were identified. Subsequently, less important shops were identifies so that ergonomic control measure would not emphasis in those shops.

3 Results

It was revealed that 124 respondents (51.67%) out of 240 were females and others males. Mean and standard deviation (SD) of their ages were calculated as 28.02 and 5.53 years respectively, with youngest and oldest of 18 and 57 years. Work experience had a mean as 4.54 with SD of 3.72 years. In addition, their attendance was 0.64 (±0.71) ergonomics and/or work related trainings in average. Two hundred and twenty five (225, 93.8%) employees were right-handed and the others were left handed. Table 1 shows information regarding studied shops and educational levels.

ART’s final score was 30.07±12.43 and in the range of 6–39. Totally, 179 cases (74.6%) were located in high levels of risk, 33 of them (13.8%) in medium level, and 11.7% (28 cases) in low levels of risk. Among studied shops, only Degradation shop was in medium level and risk in the Pars Naghsh shop was low, others were high risk. Table 4 presents the total score of ART and its factors in different shops and total number of employees. Arm movement and repetition were in unacceptable state in various shops, the high score of 6 was frequent for them.

In TOPSIS method if we assume m alternatives (A1,… , Am) and n criteria (X1,… , Xn), decision matrix will be shaped (Table 2) and all alternatives will be evaluated. At the end and based on results of the ART method, mean score (rmn) of each factor (or criteria in this study) in seven studied shops, is shown in Table 3.

As digits in the third table are definite amounts of criteria, they need to be fuzzified. Trapezoidal fuzzy numbers were used in this study; therefore, it is essential to define four amounts ranging from X1 to X2 for each number considering Fig. 2 and Equation 1. Trapezoidal fuzzy number is a fuzzy set which is defined based on R and its membership function is as shown below: $\begin{matrix} \tilde{A} (x) = {\begin{matrix} \frac{x - A^{l} + α}{α}, A^{l} - α \leq x \leq A^{l} \\ 1, A^{l} \leq x \leq A^{u} \\ \frac{A^{u} + β - x}{β}, A^{u} \leq x \leq A^{u} + β \\ 0, otherwise \end{matrix} \end{matrix}$ (1) Because of data dispersion, mean scores of more than one data have been used. Large data dispersion leads to larger range of trapezoidal number and vice versa. Data about the ART’s factors in this study had a variance equal to zero. Consequently, there is just a point instead of range of numbers. Measured number would be neither fuzzy nor trapezoidal. Therefore, mean (M) was used to calculate the range. Also, 0.1 and 0.3 were derived from normal table. X1 to X4 which could be measured as shown below:(Equation 2):

$\begin{matrix} X 1 = M - 0 . 3 M, X 2 = M - 0 . 1 M, \\ X 3 = M + 0.1, X 4 = M + 0 . 3 M \end{matrix}$ (2) For example, A1 value for tempering unit was (7.8, 6.6, 5.4, and 4.2). Therefore, fuzzy version of Table 3 (definite decision-making table) was computed (Table 4). In the next step, it was required to know the weight of factors of ART. Weights were reported in Table 5 according to the use of Entropy method. Factors that made lower difference between alternatives have gained lower weights. If a criterion gets the same value in all alternatives, its weight will be 0 and would be removed from calculations. Calculating distances of each alternative from the ideal solution (d+) and the negative-ideal solution (d–) is the next stage. Then, relative closeness of each alternative to the ideal solution (CC) was estimated and alternatives were ranked based on their priority for correcting actions. All related data are shown in Table 6. It is critical to say that robins function has been used to defuzzification of trapezoidal fuzzy number. All criteria were negative and any increment would worsen the situation. Results show that the Leher shop was the first saloon that required interventions in order to improve ergonomic conditions.

4 Discussion

Nowadays, the occupational ergonomic challenges have crossed geographical boundaries and are considered as global issue. More than a third of occupational diseases recorded in America and Japan are in the category of ergonomic disorders. In Canada, Finland, Sweden and the UK, musculoskeletal disorders (MSDs) resulted in absenteeism and disability, more than other occupational diseases. Psychosocial factors such as: high job demands, communication trends in organization, low control of work accompanied with repetitive work, lack of adequate rest, heavy and bulky loads in manual activities, high force, awkward posture, vibration and exposure to adverse weather conditions, are considered as the most important risk factors [23]. The relationship between the force and frequency as well as their joint impact on ergonomic-related disorders has been well documented [24]. Like other chronic diseases, MSDs have occupational and non-occupational risk factors. Daily life aspects such as: sports, driving, working at home, and life stresses were included in ergonomic disorders. Risk of injury by age, sex, socioeconomic status and ethnicity were altered. Obesity and smoking were considered as the other risk factors [25].

In this research, a manufacturing company in the tableware goods industry was selected due to the high loaded duties and repetitive activities. All 240 employees of the company were included in the study. So far, a large number of the methods have been introduced to musculoskeletal disorders management [26]. After assessing the ergonomic aspects of the tasks by ART, the next was to assess biomechanical aspects which focus on psychosocial factors. However, because most methods of evaluation focus on biomechanical factors, psychosocial factor consideration was an advantage. Consequently, desirability of method would be high [27]. Despite its recent introduction, the method still has not been universal [28 –32]. However, all ergonomic assessment methods must lead to interventions to control work conditions and to optimize mental and physical aspects of workers.

After each evaluation process, occupational specialists had to face the selection process, decision-making and prioritization. Selection of the best choices for control issues [33], selection of an appropriate educational plan for workforces, selection of suitable personal protective equipment [34], selection of the best occupational health promotion procedures among available choices, decision-making about the allocation of limited funds for continuous development planning [35] and prioritization of the factory shops for corrective measures were significant examples that have been discussed in the fields of occupational health, safety and ergonomics. One of the systematical ways for these processes is using the multiple criteria decision analysis(MCDA) [36]. These methods as part of operational research and mathematical design of computational tools for supporting of subjective performance evaluation and organizational productivity have grown increasingly [37]. Many studies have been conducted to develop these methods [38] and have been used to solve engineering problems [37] and science and technological challenges [39] successfully.

Different methods were also used in safety management issues such as AHP, TOPSIS, SMART, MAVT, MAUT, UTA, FUZZY, ELECTRE, PROMETHEE and ORESTRE [22]. Khandan et al. in the field of ergonomics used Entropy method for the weighting and prioritizing of ergonomic behavior in a petrochemical company [40]. Also used in their other work was ELECTRE method for selection of the best shift work group [10].

Based on our findings, subjects under research were in their young age (28.02±5.53) and had a history of work between 4–5 years. It had been documented that increasing age leads to an increase in complaints of musculoskeletal disorders, especially in the upper limbs [41]. Based on this and our results (the hazard level for 10% of samples were low), it is anticipated that a huge wave of disorders and complaint would be created in future for these employees. In this situation, an emergency planning for MSDs prevention and management would be vital for the policy makers of developing countries such as Iran. Financial budget allocated to the health and safety department in the industry is limited so this budget should be planned in a way that best of human health, performance, local and national law and regulation and business economy are satisfied. The results show that women in this industry had a significant percentage of work forces as (51.67%). Thus, there should be more considerations towards women at work because they are more susceptible to work-related injuries and accidents [42, 43]. International Labor Organization (ILO) in order to development of solutions for culture of prevention throughout the world, have focused on workers gender in 2015.

Based on the results shown in Table 6, the Leher Shop was the highest priority for implementing corrective actions. In this shop, the product after leaving the molding machine enters into Leher machine and face gradual decrease in temperature resulting in the unbroken nature of the tableware. In this situation, the operator is responsible for collecting and grading the products from the conveyor. As a corrective action, repetitive movements in this hall should be analyzed as the first priority and to be controlled and optimized. Packaging shop was located in the second priority. Heavy and harsh Manual handling and unsuitable work station in the Packaging shop were topics to be studied in the future. Decoration Shop was placed in the third level based on the F-TOPSIS ART. The risk of lower back pains was significant due to lack of suitable work-rest regime and long time sitting on the non-standard chairs. Tempering was the next priority. Based on our observation and data obtained from the study, the risk of musculoskeletal disorders in the shoulder, arm and neck in this shop had increased due to repetitive motions with forces and longtime standing at work. In this trend, Pars-pack, Pars-naghsh and Gradation shops must be considered respectively. In the Gradation shop, employees would be more susceptible to musculoskeletal disorders of the neck region because they needed to focus on products.

The important point to be considered is that the control measures in ergonomic is similar to other fields in the occupational health and safety that without the participation of the employees, improvement will not happen. It should be noted that beside engineering controls such as use of sit-stand desks (SSDs) in workplaces [44] for WRMSDs prevention, it should be noted that administrative controls have important role in health and safety promotion. Previous researches revealed that integration of biomechanical and ergonomic controls in the Cross Self-Confrontation framework promote WRMSDs prevention in the workplace [45]. Use of procedures such as: wellness programs, proper training, enhancement of mental health and physical health of workers, including the most important control measures were complementary. As well as Worksite Health Promotion Programs (WHPP) in order to improving employees’ health and lifestyle (i.e., physical activity, healthy eating, weight loss, relaxation, smoking, and drug/alcohol use) was recommended [46].

In the studied company, 81.3% of workers didn’t have colleague education, hence designing and implementation of multimedia-based education courses, followed by repetition in appropriate intervals as well as the use of a participation programming may help to reduce the number of disorders in the company [47]. It should be noted that, after the execution of each ergonomic management program, implementing proactive ergonomic principles, are recommended. This program focused on prevention and identification of the risks in sources [48]. Although application of multiple criteria decision-making techniques especially fuzzy methods is in their early stage of development in the last decades, Progress have been made in the application of this methods in real world challenges. Given that TOPSIS is one of the best methods of decision making that is being used in the decision making science [49 –51], this study was based on scores acquired from ART method for prioritization of risk and corrective actions in a manufacturing company. Application of fuzzy algorithms, especially with TOPSIS, to overcome the uncertainties in the area of occupational health and safety would be suitable [52 –57], hence in this study, we used hybrid Fuzzy TOPSIS.

There is no doubt that in order to optimize resources used to improve the health of workers and workplace conditions, there is a need for safety, ergonomic professionals to utilize decision-making techniques. It is therefore necessary to encourage safety and ergonomic professionals to do more scientific research in the field of decision making [58]. The results of this research can assist ergonomists to do effective control in the field of musculoskeletal disorders management. This is more important in the developing countries, because tight budget associated with an unstable economy pose challenging issue for health and safety managers. However, it seems that by applying methods like what is used here, Health, Safety and Environmental (HSE) managers are empowered to plan for health and safety improvement in their organizations, considering the budget limitation. In order to create essential background in the field of applied ergonomics, application of fuzzy MCDM in similar studies in other fields of ergonomic issues is recommended.

Conflict of interest

None declared.

Funding

Qom University of Medical Sciences, Qom, Iran.

Footnotes

Acknowledgments

The authors would like to appreciate Qom University of Medical Sciences for funding and supporting this project. The authors also thank all candidate employees for their kind participation. Many thanks as well to Hussein Hosseini Tabar for his English writing editorial assistance.

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