Application of REBA and QEC Methods in Redesigning Clamping Workstations to Enhance Ergonomic Performance

In the context of PT. Xyz, an international company operating in the oil & gas sector, the procurement process involves the production of drilling equipment. Some of these tools are manufactured in-house using Computer Numerically Controlled (CNC) machines to achieve high levels of accuracy and smoothness. Additionally, certain tools are outsourced to vendors based on factors like lower costs, less complexity, and processes that cannot be done in-house, such as coating and threading [1]. Outsourcing in the oil and gas industry is a common practice, where minor suppliers may have limited influence on the supply chain. Locally owned firms can benefit from outsourcing newer and more efficient technologies to enhance technical and allocative efficiency, leading to higher profits [2]. Moreover, logistics outsourcing in the oil and gas sector faces challenges that can be overcome through strategic management, including the provision of standard equipment, effective communication, staff motivation, quality assurance, and project monitoring [3]. The use of Industry 4.0 technologies, such as digitalization and intelligence, can bring significant benefits to oil and gas companies. This model, known as "Oil and Gas 4.0," emphasizes the digital transformation and smart technologies in the industry [4]. Furthermore, the application of blockchain technology in the oil and gas sector offers opportunities for improved storage, ordering, transportation, and distribution of products through various industry channels [1]. In the machining process using CNC machines, the operator has a very important role in the workpiece mounting system. The operator is responsible for placing the workpiece according to the setup-sheet in order for the CNC program to run correctly. In addition, the operator must also ensure that the workpiece does not move during the machining process. For this reason, the operator places the workpiece and tightens it manually in a standing working position or attitude. The height difference between the platform and the work table on a CNC machine can lead to discomfort and fatigue for operators due to repetitive processes like tightening workpieces. In a scenario where the average worker height is 165 cm and the height difference is 60 cm, ergonomic issues can arise, impacting productivity. Operators spend significant time setting up the machine, with a setup time of 15 minutes before each of the 9 tightening processes per shift. Additionally, operators take a 10-minute break after setup, resulting in non-value-added time totaling 90 minutes per shift. This reduces productive working hours to 9 out of the 10.5 total hours, affecting efficiency and potentially leading to operator discomfort and fatigue. To address these ergonomic concerns and improve efficiency, it is crucial to consider the design and setup of CNC machines. Proper maintenance [5] is essential for ensuring optimal performance and longevity of CNC machines. Additionally, study [6] emphasizes the significance of analyzing body posture to enhance work effectiveness and prevent musculoskeletal issues among operators. Ergonomic design considerations [7] can significantly impact worker health and productivity, especially when tailored to anthropometric data. the utilization of simulation tools like the Swansoft CNC Simulator [8] can aid in training operators effectively, especially during circumstances like the COVID-19 pandemic. This can enhance learning outcomes and operational proficiency. Furthermore, research on optimizing cutting processes [9] showcases the continuous efforts to enhance CNC machine operations for better performance and quality output. From the results of interviews and observations of operators who operate CNC machines, there are complaints of pain in the neck, hips, back, and hands due to work postures that are not in accordance with the body. This can cause discomfort and musculoskeletal disorder in the operator. Ergonomics studies show that non-ergonomic work postures can cause discomfort and risk of injury to workers [6, 10-12]. Work posture analysis methods such as OWAS and RULA are used to evaluate the operator's posture while working. The results of analysis using the OWAS method show that some operators require improved work posture to reduce the risk of injury [12, 13]. In addition, education and muscle stretching exercises have been shown to reduce musculoskeletal complaints in workers, such as pain in the shoulders, neck, hands, waist, and back [14]. Ergonomic workbench design based on work posture risk analysis can help reduce operator discomfort and risk of injury. Studies show that adjusting work posture to a suitable workbench can improve worker comfort and health [15, 16]. In addition, ergonomic laptop chair and desk design is also important to prevent postural discomfort when working with a computer [9]. In the context of CNC machines, optimization of machine parameters such as cutting speed and depth of cut can affect production process time and operator comfort. Research shows that optimization of machine parameters can improve the efficiency of the production process and reduce the risk of injury to operators. The issue of non-value-added time in the workplace, such as inefficient processes like tightening workpieces, can lead to musculoskeletal problems among workers, increasing the risk of permanent disabilities [17]. This is particularly concerning as studies have shown that work-related musculoskeletal disorders are prevalent among manufacturing industry workers [18]. Such disorders not only affect the workers but also have consequences for employers and society at large [17]. In the long term, these musculoskeletal issues can contribute to permanent work disability, impacting workers' ability to return to work and affecting their earnings and employment patterns [19]. Research indicates that workers with permanent impairments may experience challenges in returning to work and maintaining long-term employment [20]. Additionally, individuals with permanent work-related impairments face long-term mortality risks, highlighting the serious implications of such disabilities [21]. Efforts to address these issues include the need for workplace safety improvements, as highlighted in a study on back pain and disability among automotive industry workers in Ethiopia, where a lack of a safety culture was noted [22]. Implementing ergonomic interventions, as seen in a study on ergonomic risk factors among workers in a medical manufacturing company, can help enhance safety and productivity [20], the study [1] showed an example how to cite a journal article in press. This is a case of one author only. [2] showed an example how to cite a journal article in press. This is a case of one author only. However, produced different results. it is crucial to consider the economic impact of disabilities on workers. Studies have shown that workers with disabilities may face challenges in accessing workplace wellness programs and may require strategies to ensure equitable access to such programs [23]. Return to Work (RTW) programs play a vital role in mitigating the economic and personal consequences of long-term sickness absence. In this context, ergonomic risk assessments are essential to ensure a safe and supportive work environment for returning employees. This study offers a novel contribution by simultaneously integrating two established ergonomic assessment tools—Rapid Entire Body Assessment (REBA) and Quick Exposure Check (QEC)—to evaluate posture and ergonomic risk exposure. The combined application of REBA and QEC is rarely found in previous research, especially within the heavy manufacturing industry. Most prior studies have tended to use these methods in isolation. For example, some studies have focused solely on comparing REBA and RULA, while others have relied exclusively on QEC for assessing workstations in the light manufacturing sector. By integrating both REBA and QEC in a single framework, this study aims to provide a more comprehensive and nuanced understanding of ergonomic risks in heavy manufacturing settings.

Therefore, the combined REBA-QEC approach adopted in this study facilitates a more holistic and comprehensive assessment of musculoskeletal risks, particularly in CNC machine operations that involve static postures and repetitive movements. Furthermore, the integration of local anthropometric data enhances the relevance and precision of ergonomic evaluations, allowing for redesign strategies that are better aligned with the actual physical characteristics of the workers. This integrative approach ultimately contributes to more effective ergonomic interventions and supports sustainable return-to-work efforts in the heavy manufacturing sector.

Based on the recapitulation of the answers to the observer and worker questionnaires, the exposure score is then calculated, where the exposure score is calculated for each part of the body such as the back, shoulders/arms, wrists and neck by considering ± 5 combinations/interactions, namely posture with force/load, movement with force/load, duration with force/load, posture with duration and movement with duration. Here is one of the exposure score calculations in workpiece tightening activities (Figure 3).

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Figure 3. Exposure score results on workpiece tightening activities

Table 5 is a recapitulation of the results of the exposure score calculation for all operators in workpiece tightening activities and the determination of exposure scores based on Table 5.

Table 5. Recapitulation of exposure score

Observed Limbs	Exposure Score Value						Average	Display Score
	Oprt 1	Oprt 2	Oprt 3	Oprt 4	Oprt 5	Oprt 6
Back (Moving)	40	40	40	40	40	40	40	High
Shoulders/Arms	32	32	32	32	32	32	32	High
Wrist	26	26	26	26	26	26	26	Medium
Neck	10	10	10	10	10	10	10	Medium
Total Exposure Check value	108	108	108	108	108	108	108

After obtaining the exposure score for each limb studied during the workpiece tightening activity for each operator, the next step is to calculate the exposure level. This exposure level helps determine the necessary actions related to the observed work activity to reduce the risk of injury.

$E \%=\frac{X}{X_{\max }} \times 100$

where:

X = Total score obtained for exposure to the risk of injury to the back, shoulders/arms, wrists, and neck, calculated from the questionnaire.

X_max = Maximum total score for exposure to potential injury for the back, shoulders/arms, wrists, and neck. X_max is constant for certain jobs. For manual handling work (such as lifting, pulling, or carrying objects), the possible X_max value is 176.

Example of Exposure Level Calculation:

For example, if the total exposure score (X) is 108 and X_max is 176:

$E \%=\frac{108}{176_{\operatorname{Max}}} \times 100=60.8 \%$

Thus, the exposure level would be 60.8%, which indicates the level of risk in the observed work activity.

E = 61% (need further research and changes)

The following is a recapitulation of the exposure check level calculation for all operators in workpiece tightening activities based on Table 5, which can be seen in Table 6.

The following is a description of the five interaction combinations used in the Quick Exposure Check (QEC) analysis, which are arranged in an integrated and interrelated manner to provide a complete understanding of the potential ergonomic risks in the workplace:

1) Posture with Load assesses the effects of non-neutral postures when applying pressure to a workpiece, which increases the statistical stress of the muscles.

2) Posture with Duration assesses the impact of maintaining awkward postures for a long time on muscle fatigue.

3) Movement with Load considers the risk, repeated movements simultaneously with compressive forces, especially on the wrist and arm.

4) Movement with Duration measures the effects of fatigue due to long-term repetition without rest.

5) Posture with Movement assesses the risk when rapid posture changes are performed in dynamic and unstable working positions.

3.1 REBA score sheet of work attitude and posture

From Figure 4, it can be seen that the angles of the left and right legs of the workers differ. In this case, the author selected the data from the left foot, as it showed the greatest angular deviation.

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Figure 4. Measurement angle of REBA method for workpiece tightening activity

1. Group A posture (trunk stability)

Group A includes the posture of the neck, trunk, and legs, which are essential for maintaining body stability during work.

a. Neck Posture

The neck forms an angle of 38°. According to the REBA assessment, the score is 2.

b. Leg Posture

Both feet support the body weight evenly, giving a base score of 1. However, both legs form an open angle of about 100°, which adds 2 points. Therefore, the total score for the leg section is 3.

c. Trunk Posture

The trunk forms an angle of 120°. Based on the REBA scoring system, the posture receives a score of 4.

A summary table of REBA score calculations for Group A body parts across all operators is provided in Table 7.

2. Group B posture (upper extremities)

Group B includes the posture of the upper extremities, namely the upper arm, lower arm, and wrist, which are crucial for gripping activities.

a. Wrist Posture

The wrist is aligned straight with the lower arm, resulting in a score of 1.

b. Lower Arm Posture

The lower arm forms a 43° angle with the upper arm. This posture is given a score of 2.

c. Upper Arm Posture

The upper arm forms an angle of 95°. Based on the REBA criteria, the score is 4.

Table 8 is a recapitulation of the results of the calculation of REBA scores on group B limbs for all operators.

Table 9 is a recapitulation of the results of calculating the total REBA score for all operators.

Table 10 is a recapitulation of risk levels and actions to be taken based on Table 10.

Calculation example:

1) (amount of data) = Number of anthropometric data calculations of operators 1 – 6

2) = 284 - 47.33 = 236.67

3) = 236.672 = 56012.69

4) (Standard deviation)

$=\sqrt{\frac{\sum\left(x_i-\bar{x}\right)^2}{n}}=\sqrt{\frac{(284-47.33)^2}{6}}=96.62$

Furthermore, the calculation uses SPSS to find out whether the data is distributed normally or not.

Based on the output of the Test of Normality above, the Shapiro-Wilk test results show the significance values for TSB (0.415), TPB (0.404), JTD (0.421), RT (0.463), and LB (0.505). Since all the significance values for TSB, TPB, JTD, RT, and LB are greater than 0.05, it can be concluded that the anthropometric data are normally distributed.

The data obtained from Table 12 consists of the anthropometric measurements of workers in a standing position, which are required for this study. The next step involves calculating the mean, standard deviation, control limits, and percentiles for these data. The statistical results from the processing of the workers' anthropometric data, as performed by the author, can be seen in Table 13.

3.3 Proposed work platform height design

The following are the proposed dimensions for the work platform design, based on the anthropometric data processed by the author in Table 13. The dimensions, along with their explanations, can be seen in the following Figure 5.

Table 12. Table output test of normality

Variable	Kolmogorov-Smirnov (Statistik)	df	Sig. (KS)	Shapiro-Wilk (Statistik)	df	Sig. (SW)
TSB	0.209	6	0.200*	0.907	6	0.415
TPB	0.217	6	0.200*	0.905	6	0.404
JTD	0.223	6	0.200*	0.908	6	0.421
RT	0.241	6	0.200*	0.914	6	0.463
LB	0.180	6	0.200*	0.920	6	0.505

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Figure 5. Proposed work platform design

Table 13. Statistical calculation results of workers' anthropometric data