Integrating RNLE and REBA to Evaluate Manual Handling Risks among Semiconductor Technicians
DOI:
https://doi.org/10.11113/humentech.v5n1.129Keywords:
Work-related musculoskeletal disorders (WMSDs), Ergonomic risk assessment, Semiconductor wafer fabrication, Revised NIOSH Lifting Equation (RNLE), Rapid Entire Body Assessment (REBA)Abstract
Manual handling of wafer pods persists in semiconductor fabrication despite high levels of automation, exposing technicians to work-related musculoskeletal disorders (WMSDs). This case study evaluated ergonomic risks associated with lift-and-load wafer pod tasks in the Fab Integration Department of a semiconductor facility in northern Malaysia. Eight technicians performing routine transfers from upper and lower trolley levels to tool loading ports were assessed using direct observation, task analysis, and physical measurements. Lifting demands were quantified using the Revised NIOSH Lifting Equation (RNLE) to determine the Recommended Weight Limit (RWL) and Lifting Index (LI), while postural risk was evaluated using the Rapid Entire Body Assessment (REBA). RNLE analysis showed LI values ranging from 1.01 to 2.00, indicating increased to high lifting risk, particularly for lower trolley tasks. Excessive horizontal reach and asymmetric trunk rotation were identified as the main contributors, reflected by reductions in the Horizontal Multiplier (HM) and Asymmetry Multiplier (AM). Postural assessment revealed high REBA risk levels (scores 6–8) associated with trunk flexion, neck extension, and asymmetric lifting. Based on these findings, targeted ergonomic interventions were proposed, including limiting twisting angles, maintaining safe horizontal reach distances, adopting squatting techniques for low-level lifting, and providing ergonomics training. The integrated RNLE–REBA approach offers a practical framework for identifying high-risk manual handling tasks in semiconductor manufacturing. Future research should extend this assessment to other departments and evaluate digital ergonomic monitoring tools for continuous risk management.



