Faculty Publications
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Item Risk factors associated with work-related musculoskeletal disorders among dumper operators: A machine learning approach(Elsevier B.V., 2023) Kar, M.B.; Mangalpady, M.; Kunar, B.M.Aims: This study aimed to determine the risk factors associated with work-related musculoskeletal disorders (WRMSDs) among dumper operators working in Indian iron ore mines. Methods: A total of 246 dumper truck operators meeting inclusion and exclusion criteria were chosen for data collection. A self-report custom and the standard Nordic questionnaire were used for collecting data about risk factors and WRMSDs. The data were pre-processed and analyzed using machine learning (ML) algorithms (such as logistic regression ( LR), support vector machines (SVM), decision trees (DT), gradient boosting machine (GBM) and random forest (RF)). Results: RF model was found to outperform the other algorithms with high accuracy (0.71), precision (0.75), recall (0.78), F1 score (0.76), and area under the receiver operating characteristic curve (0.82). The mean rank of the risk factors showed that age is the most critical parameter, followed by awkward posture, experience in mines, job demand, alcohol consumption, smoking cigarettes, work design, and marriage status. Conclusion: Overall, the study provides valuable insights into the risk factors associated with WRMSDs among dumper operators and suggests that measures should be taken to address these risk factors to prevent WRMSDs in the dumper operator population. © 2023 The Author(s)Item Predictive Analysis of Whole Body Vibration Exposure of the Hydraulic Rock Breaker Operators working in Indian Quarries(World Researchers Associations, 2025) Vikram, P.; Mangalpady, M.This study aims to identify the various factors affecting Whole Body Vibration (WBV) exposure among operators of track-mounted hydraulic rock breakers in mechanized quarries. The objective is to develop a statistical model that predicts WBV exposure by considering rock properties, operator’s personal characteristics and equipment specifications. Data on personal factors, equipment specifications and WBV were collected from 84 hydraulic rock breaker operators. A univariate analysis was conducted to determine the association between independent factors and the dependent variable Vibration Dose Value (VDVz). Significant parameters including experience in mines, hydraulic working oil pressure, hydraulic oil flow, hammer blow rate and instantaneous cutting ratio (ICR) were identified. These parameters were then used to develop a multivariate linear regression model. The findings of the multivariate linear regression analysis revealed that among the risk factors, both ICR and hammer blow rate had a negative impact on VDVz. However, experience in mines and hydraulic working oil pressure positively influenced the outcome. The most impactful parameters were ICR (-0.67), experience in mines (0.13), hydraulic working oil pressure (0.097) and hammer blow rate (-0.006). This study recommends implementing vibration dampers to reduce VDVz while ensuring that ICR is maintained at a level that does not compromise productivity. © 2025, World Researchers Associations. All rights reserved.