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Ergonomic analysis of selected lifting tasks


Ergonomic analysis of selected lifting tasks

Pasha, Saba (2008) Ergonomic analysis of selected lifting tasks. Masters thesis, Concordia University.

Text (application/pdf)
MR42525.pdf - Accepted Version


Lifting is a common task that many people face every day. Some jobs, like manual garbage collecting, require considerably more frequent lifting. Heavy weight, improper posture and repetition can apply excessive forces to different body parts, especially on the lower back, which is one of the most affected parts during lifting. The current study focuses on infrequent, symmetric lifting. A box, weight 2, 60, or 130 N, is picked up from the floor and lifted to different heights using either knee or hip lifting. Ergonomic checklists are used to evaluate these lifts. They typically take into account body posture, weight lifted and frequency. WISHA determined that all lifting tasks were acceptable, REBA identifies most as medium or high risk. Biomechanical analyses, using LifeMOD, 3DSSPP and CATIA, are used determine loading of the lower back and shoulder when a female lifts 2 or 60 N. OptiTrack hardware and software were used to obtain 3D body marker coordinates during these lifting tasks. LifeMOD calculates higher lumbar moment and compression force in hip lifting compared to knee lifting. 3DSSPP shows that lumbar moment, compression force and shear force are all higher in hip lifting than in knee lifting. CATIA calculates lower compression forces and higher shear forces in hip lifting than in knee lifting, while there is little change in the lumbar moment. LifeMOD, 3DSSPP and CATIA all show that when a heavier load is lifted, lumbar moment, compression force and shear force increase

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical and Industrial Engineering
Item Type:Thesis (Masters)
Authors:Pasha, Saba
Pagination:xiv, 110 leaves : ill. ; 29 cm.
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical and Industrial Engineering
Thesis Supervisor(s):Gouw, Gerard J
ID Code:976016
Deposited By: Concordia University Library
Deposited On:22 Jan 2013 16:18
Last Modified:18 Jan 2018 17:41
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