Ergonomic Risk Analysis of Indian Auto Rickshaw Drivers Using RULA and REBA

Suryavanshi , Lalit (2018) Ergonomic Risk Analysis of Indian Auto Rickshaw Drivers Using RULA and REBA. MTech thesis.

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Abstract

The aim of this research is to determine the ergonomic risks and the musculo skeletal disorders that are associated with the Indian auto-rickshaw drivers during driving and suggest the necessary modifications and improvements that can be implemented for the development of a new auto-rickshaw that is better suited ergonomically for the drivers. The ergonomic risk is measured by analysing the different postures attained by the drivers. The main tools that I have used for this purpose are RULA (Rapid Upper Limb Assessment) and REBA (Rapid Entire Body Assessment). A total of 20 auto-rickshaw drivers were interviewed and questions were asked about the problems that they were facing during driving. A questionnaire was prepared to collect data on their demographics, work history and musculoskeletal pain history. A REBA score of 6-7 considering the different postures of the drivers signifies that there is a medium risk of developing a musculoskeletal disorder, further investigation is needed and the changes may be applied as soon as possible. Assessment of ergonomic risks using the method RULA gave a score of 5-6 considering different postures which suggests that necessary changes must be implemented immediately. The analysis of the work related musculo skeletal disorders (WMDs) using the RULA and REBA shows that the workers are under threats of musculo-skeletal disorders and there is a need to implement necessary changes as soon as possible in order to prevent the musculo-skeletal disorders.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Working postures; Musculo-skeletal disorders; RULA and REBA method; Drivers
Subjects:Engineering and Technology > Industrial Design > Design
Divisions: Engineering and Technology > Department of Industrial Design
ID Code:9905
Deposited By:IR Staff BPCL
Deposited On:01 Jul 2019 16:19
Last Modified:01 Jul 2019 16:19
Supervisor(s):Lal, Mohit

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