4.3.1. Primary Assessment Calculation

The calculations pertaining to biomechanical aspects are shown below.

$$\begin{array}{c} \mathbf{W}\_{11} = \begin{bmatrix} & 0.2 & 0.2 & 0.2 & 0.2 & 0.2 \end{bmatrix} \\\\ \mathbf{F}\_{11} = \begin{bmatrix} 7 & 9 & 8 & 7 \\ 8 & 8 & 8 & 7 \\ 8 & 8 & 8 & 8 \\ 6 & 9 & 8 & 7 \end{bmatrix} \end{array}$$

9898

The index pertaining to biomechanical aspects is given by HFI11 = W11 × F1. HFI11 = (7.6, 8.2, 8.4, 7.4) Similarly, the index for each criterion is calculated and listed below. HFI12 = (8.4, 8, 8.4, 7.8) HFI13 = (7, 7, 6, 6.5) HFI21 = (8.5, 7.25, 8.25, 8.25) HFI22 = (8.5, 9, 9, 9) HFI23 = (8.25, 7, 7.75, 7.75) HFI24 = (9, 8.5, 9, 8) HFI31 = (7.5, 8, 8, 6.5) HFI32 = (7.5, 8, 8, 7.5) HFI33 = (6, 6, 6.5, 5.5) HFI34 = (8, 7.5, 8, 7.5) HFI35 = (9, 8, 9, 8) HFI41 = (7.5, 8, 6, 5.5) HFI42 = (9, 8, 9, 8) HFI43 = (8.5, 8, 8.5, 8.5)


**Table 9.** Fuzzy index.

#### 4.3.2. Secondary Assessment Calculation

The index pertaining to physiological factors is calculated as shown below.

$$\text{HFI}\_1 = \text{W}\_1 \times \text{F}\_1$$

$$\text{W}\_1 = [0.5, 0.25, 0.25]$$

$$\text{HF}\_1 = \begin{bmatrix} 7.6 & 8.4 & 8.2 & 7.4\\ 8.4 & 8 & 8.4 & 7.8\\ 7 & 7 & 6 & 7.5 \end{bmatrix}.$$

$$\text{HFI}\_1 = \begin{bmatrix} 7.65 & 7.95 & 7.69 & 7.92 \end{bmatrix}$$

Similarly, the indexes for other enablers are calculated below.

$$\text{HFI}\_2 = \text{(8.56, 7.93, 8.5, 8.25)}$$

$$\text{HFI}\_3 = \text{(7.2, 7.125, 7.55, 6.625)}$$

$$\text{HFI}\_4 = \text{(8.335, 8, 7.88, 7.345)}$$

#### 4.3.3. Tertiary Assessment Calculation

Finally, the total HFI is calculated as shown below.

$$\begin{array}{c c c c} \text{W} = \begin{bmatrix} 0.4 & 0.2 & 0.2 & 0.2 \end{bmatrix} \\ \text{F} = \begin{bmatrix} 7.65 & 7.95 & 7.69 & 7.92 \\ 8.56 & 7.93 & 8.5 & 8.25 \\ 7.2 & 7.125 & 7.55 & 6.625 \\ 8.335 & 8 & 7.88 & 7.345 \end{bmatrix} \\ \text{HFI} = \text{W} \times \text{F} \\ \text{HFI} = \begin{bmatrix} 7.879 & 7.791 & 7.862 & 7.612 \end{bmatrix} \end{array}$$

The HFI is the average of (7.879, 7.791, 7.862, 7.612), which is equal to 7.786.

HUMAN FACTOR INDEX = 7.786 (6, 8)

A human factor index of 7.86 was determined using a multigrade fuzzy approach, which means that the organization is ERGONOMIC.

#### **5. Results and Discussion**

The observations made in this study are presented below.

A cross-impact matrix multiplication applied to classification (MICMAC) analysis was used to study the dependence power and driving power of the variables considered in the study [46]. The results indicate that two independent performance variables, namely, the safety factors and environmental factors, show a strong driving power and weaker dependence power. Hence, these were identified as the "key factors" in this ergonomic assessment study. In addition, it was found that the dependent variables, i.e., the physiological and psychological factors, are weak trainers and depend strongly on one another. The results of the MICMAC analysis are shown in Figure 4.

The fit indices for the current case were determined as follows: a value of 0.91 is found for the goodness of fit, indicating that the model is a good fit [47]. The normed-fit index value was 0.70. A value as low as 0.80 is recommended for this index [47]. The relative/normed χ<sup>2</sup> ratio (χ2/df) value was 10.45. The Cronbach's ∝ for the ergonomic performance variables was acceptable and indicates that the variables are reliable.

**Figure 4.** MICMAC analysis.

The ergonomic assessment was performed using the multigrade fuzzy approach. A human factor index of less than 5 indicates that the organization cannot be considered a good candidate to implement an ergonomic work environment that would contribute to better quality and maximum productivity [3]. The human factor index of 7.786 determined for the automotive industry case in this study reveals that the industry is a suitable candidate for operating in a good ergonomic environment. However, it was found that there is scope for improving the work environment of the organization.

It was found that a major gap is perceived for the criterion "biomechanical aspects". This is followed by "housekeeping", "temperature/climate", and "energy expenditure". Management can take measures to improve the ergonomic conditions, such as the use of material handling equipment to prevent the manual movement of materials, equipment designs that would allow for comfortable reaches and posture, the use of personal protective equipment while working, application of the 5S (sort, set in order, shine, standardize, sustain) scheme to improve the housekeeping facilities, and providing proper a work–rest schedule for workers to sustain a normal heart rate and basal metabolic rate.

#### **6. Conclusions**

Ergonomic risks and bad work postures can lead to various types of MSDs and worker fatigue, which hamper the efficiency of manufacturing organizations and lead to a loss in productivity. This study aims to provide insight into the modeling and analysis of ergonomic risk factors in the Indian automotive industry. A combined ISM, SEM, and multigrade fuzzy approach was proposed to determine the human factor index for ergonomic evaluation of industries. The ISM model reveals the driving and dependence among the ergonomic factors, which enables managers to understand the interrelation among ergonomic factors in the automotive component sector. Moreover, management should also consider the dependence among factors in the ISM. Therefore, survey data were analyzed using VPLS software. The SEM-PLS technique was used to verify the seven hypotheses. Furthermore, evaluating the various ergonomic performance factors using the multigrade fuzzy approach facilitated an understanding of the contribution of these factors to safety and productivity improvement. A case study demonstrated the practicability of implementing these approaches in an industrial situation. Manual computation using

a multigrade fuzzy approach is time-consuming and error-prone, and a computerized decision-support system (DSS) can be developed. The application of an integrated model for ergonomic assessment is not limited to the manufacturing industry and can be extend to evaluation in industries such as the software and healthcare. In addition to that, several other forms of ergonomic risks factors such as technological factors and process factors can be added to the measurement model to obtain more robust results.

**Author Contributions:** Methodology, K.V.; Supervision, P.R.; Writing—original draft, K.V.; Writing review & editing, P.R. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Conflicts of Interest:** The authors declare no conflict of interest.
