1. Introduction
Prevention of work-related musculoskeletal disorders (WR-MSDs) remains a challenge in the industrial settings. Establishing a successful prevention approach consisting of different workplace interventions might reduce the onset or prevalence of WR-MSDs [
1,
2]. Organizational workplace interventions such as the distribution of work tasks, scheduling, and additional variation in physical exposure might contribute to the mitigation of harmful exposure to physical risk factors (e.g., repetition, force, and awkward postures) [
3]. Physical variation has gained increasing interest in the ergonomic research and practice as an organizational method to reduce exposure to physical risk factors [
4,
5,
6]. According to Mathiassen (2006), variation is “the change in exposure across time”. Variation in physical exposure allows transmission of workload to other muscles and increases utilization of different body regions [
4]. However, very little empirical research has reported the possible effects of variation on exposure to physical risk factors, and the conclusion and suggestions are vague [
6,
7,
8]. Furthermore, the critical questions are: how much and which kind of variation would sufficiently reduce these risk factors?
Physical variation can be separated into different types [
4]. Extrinsic variation is associated with differences in exposure between tasks, jobs and vehicle models (e.g., temporal variation, job rotation, and rationalization). Manufacturers often believe that this type of variation is beneficial for WR-MSDs, but previous studies have not yet confirmed the positive effects of extrinsic variation on reducing pain or fatigue, except for improved subjective feelings [
6,
7]. Another type of variation is motor variability that addresses kinetic and kinematic of movements (e.g., joint angles, velocities, and joint torques) or muscle activities across repeated cycle times within and between individuals [
9]. The effect of motor variability on WR-MSDs symptoms is unclear in the literature [
9,
10,
11,
12]. The third type of variation results from the concept of “coping strategy” and many French-language studies have concentrated on this concept [
13,
14,
15,
16]. An operator usually develops strategies to perform assigned tasks that are adapted and regulated to cope with the environment in a way that achieves the objectives of production and preserves his/her health [
13,
16]. This strategy reflects behaviors, characteristics, strength or fatigue, preferences, attitudes, expertise, and the attention of an operator. Increasing operational leeway enables operators to develop specific strategies in a work context and manage work activity [
16]. Coping strategies (operators-developed strategy) can lead to a variability of exposure to physical risk factors across time. For example, exposure to physical risk factors between subjects might be different in two similar and consecutive cycle times, due to the difference in coping strategy.
Industrial companies show a tendency to eliminate operational leeway, particularly following implementation of the lean principle. A trend in automotive industries indicates the increase of work standardization (use of element sheets for workstations), best practice (performing the tasks in the same way), and limiting operational leeway (coping strategy) [
17]. Furthermore, in-house ergonomic methods often evaluate workstations and not individuals, and the assessment is based on the way an experienced operator does a particular job. Interventions are also implemented based on the assessment for a workstation and an experienced operator [
18].
The challenge is whether manufacturers should take into account the variability of exposure to physical risk factors due to operational leeway in design and production. By limiting operational leeway, they believe that operators have to perform their tasks in the same manner, and the current assessment approach overlooks the variability of exposure by assessing only one operator in specific cycle time. This study, therefore, aims to investigate the variability of exposure to physical risk factors within and between operators in repeated executions of the same prescribed tasks.
4. Discussion
We found a variability of exposure to physical risk factors between and within operators in the repeated execution of the same prescribed tasks. Our findings show a higher variability of exposure to the number of red and yellow assessments between and within operators at the Mounting SCR Tank workstation. The characteristics of the workstations might be a reason for the difference in the variability of exposure. The more red and yellow assessments were found in a workstation, the more operators used different strategies for performing the tasks, which led to more variability of exposure. Gaudez et al. (2016) in a review article mentioned that work characteristics are the source of variability [
12].
Exposure to physical risk factors at both workstations was higher in this study than our previous study in which we evaluated only an operator in one cycle time [
18]. It might be worth considering that the worst evaluation of each risk factor in the repeated execution of several cycle times by an operator was the final evaluation, which increased the number of red and yellow assessments. The exposure to physical risk factors within operators changed in the repeated execution of several cycle times, and the more we observed the repeated cycle times, the more variability of exposure was found. However, we did not see an increasing trend of risk factors from CT1 to CT8.
We evaluated all of the participants at the same period of the day (10–12 a.m.) but not during the same day of a week. It was impossible to evaluate all of the cases on the same day because we needed the operator to work on the frequent type of truck in a given workstation between 10 a.m. and 12 a.m. These conditions were often impossible in a real setting. These results could not confirm that physical risk factors decrease or increase with the execution of consecutive cycle times across the different days.
The operators in this study executed their tasks differently, which might relate to operational leeway in the workstations. Compared to the typical automotive industries, these workstations provided more operational leeway because of various tasks in a cycle and more cycle time. A coping strategy due to having operational leeway for performing a job might be a reason for the variability of exposure between operators, as this variability was high in posture category risk factors of our assessment tool. Recent studies have shown that coping strategies enable operators to adapt and regulate their gestures and movements, which might be beneficial for reducing work-related musculoskeletal pains [
13,
14,
15,
16]. However, it is a matter of debate in the literature whether exposure to physical risk factors decrease or increase due to coping strategy. Roquelaure et al. (2001) found inter-individual variability due to coping strategies between female operators performing repetitive tasks, but they found a non-significant relationship between operators’ developed strategies and WR-MSDs [
19]. Major and Vezina (2015) reported different strategies among female crab-plants to perform the tasks that help them to manage pain and discomfort [
13]. However, they showed that operators’ strategies could provide overexposure, depending on their work context [
13,
16]. Manufacturers believe that standardization and less operational leeway allow fewer errors in work activity and that they improve quality and productivity. The challenge is to find an appropriate balance between standardization, which assures quality and productivity and the optimal level of operational leeway, which allows the operators to adapt the strategies for performing their tasks.
The variability of exposure found in this study might also associate with motor control variability (intrinsic variability) [
9,
10,
11,
12,
20]. According to motor control models and theories, an operator chooses his strategy for performing a task from various available models of movement based on personal and professional characteristics [
12,
21].
Our results show that the current approach of WR-MSD risk measurement based on the assessment of a workstation and an experienced operator is a debatable one. Assessing different operators in several cycle times proved that the type and level of exposure changed with the primary assessment performed in our previous study [
18]. The practitioners must be cautious in considering only one evaluation with an observational checklist, as the exposure of all operators in a specific job because various factors (e.g., coping strategy, movement variability, and individual characteristics) influence the type and level of exposure to physical risk factors [
22].
A possible limitation of this study is that we assessed the operators during different days and the variability of exposure might be related to the mood of an operator during that specific time instead of being related to their coping strategy and motor variability. For example, operator two at the Mounting SCR tank workstation had several red risk factors on Tuesday, while his assessment had less red risk factors on Friday. The psychological conditions of the operator may influence on his activities in different days. Furthermore, we could not include the same sample of observations for the participants, but we attempt to have at least two observations on the same day for a participant. The difference in the number of observations between both workstations might influence the variations of yellow and red assessments.