Experimental and modeling approaches to optimize repetitive task analysis in the automotive industry

Despite being a significant predictor of musculoskeletal injury, mitigating muscle fatigue in automotive assembly remains a significant challenge. Administrative controls, such as job rotation and work relief, are often employed
to reduce fatigue exposures, but little guidance is available on their optimal use-cases. The first objective of this project is to evaluate different relief/rotation schedules for several automotive manufacturing tasks using a
mathematical model that predicts muscle fatigue. Additionally, many ergonomics assessment tools rely on accurate measures of force, repetition and effort duration to determine acceptable force limits. However, accurately determining the duration of each effort is more difficult to quantify, but may dramatically influence recommendations when compounded hundreds of time per day. Consequently, the second sub-project aims to develop a library of force durations for common automotive manufacturing manual exertions. These two related sub-projects will produce very applied, real-world solutions for industry looking to mitigate worker muscle fatigue.

Faculty Supervisor:

Nicholas La Delfa

Student:

Partner:

Cort Research and Innovation Inc.

Discipline:

Engineering

Sector:

Manufacturing; Professional, scientific and technical services

University:

University of Ontario Institute of Technology

Program: