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Digital Human Modeling in Ergonomic Risk Assessment of Working Postures using RULA.

Authors :
Hussain, M. Manzoor
Qutubuddin, S. M.
Katuru Phani Raja Kumar
Reddy, Ch. Kesava
Source :
Proceedings of the International Conference on Industrial Engineering & Operations Management; 3/5/2019, p2714-2725, 12p
Publication Year :
2019

Abstract

Digital Human Modeling (DHM), the process of CAD representation of human body form, is an emerging tool used to simulate workplaces in order to provide solutions for ergonomics related problems. Digital humans/manikins are being incorporated in the software, can be manipulated easily and assessed for work related discomfort, injuries and workplace design. Manual workers in small scale industries are often exposed to work related discomfort and pain while performing work. These exposures may lead to development of work related musculoskeletal disorders (WRMSDs) and low back pain (LBP), affecting the efficiency of workers and productivity of the industry. The main objective of current study is to analyze the working postures of manual workers in small scale industries by using Rapid Upper Limb Assessment (RULA) assessment in CATIA V5R20 software. The workers in stone cutting and polishing industry were selected, and found to be working in awkward postures involving heavy manual lifting, bending, twisting and turning of the trunk. Most of the postures indicated a high risk score of 7, indicating changes in the posture to be done immediately. Ergonomic interventions were suggested and the improved posture was evaluated using RULA and the posture indicated a score of 3, indicating low risk. The manual lifting task was also assessed using NIOSH lifting equation at the origin and destination of lift, using CATIA V5R20. The ergonomic interventions reduced the value of lifting index from 1.79 to 0.98, indicating safe limit. The results indicate that awkward working posture risks can be minimized by effectively using ergonomic interventions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21698767
Database :
Complementary Index
Journal :
Proceedings of the International Conference on Industrial Engineering & Operations Management
Publication Type :
Conference
Accession number :
137667451