Systems and assistive equipment for workers are designed to optimise their performance in performing their tasks by supporting or enhancing their abilities and skills. However, for the same task, a wide variety of these equipments is available to support the worker, each with its own constraints and risks in terms of ergonomics as well as occupational health and safety (OHS). It is therefore crucial to identify, on the one hand, the assistive equipment with the least ergonomic, occupational health and safety risks. On the other hand, it is essential to determine optimally the most suitable assistance equipment for a specific group of workers in a given workplace and for specific tasks. However, the literature indicates very few studies that highlight an approach allowing a systematic selection of assistive systems/equipment.
In addition, in the context of complex assemblies such as in the aeronautics sector, it has been observed that technicians responsible for maintenance operations (disassembly, inspection, assembly) frequently face restrictive conditions: restricted workspace, high-rise and hard-toreach components. Workers are thus forced to adopt low or non-ergonomic postures, sometimes including a combination of static muscular work and lateral flexion or torso torsion. This creates poor biomechanics of the upper limbs and an increased risk of musculoskeletal disorders (MSD).
The objective of this study is therefore to provide a digital mechanical equipment design approach for a workstation in a context of complex assembly in limited space. An approach that simultaneously addresses the problem of workstations not adapted to workers' abilities and needs for a systematic selection of assistance equipment for workers.
The result of this study is a three-phase approach: the physical ergonomics, cognitive ergonomics and residual risk assessment phases. During this study, this approach was applied to a realistic case which thus: 1) significantly improves the ergonomics in the assembly station of module 8 of the gas turbine of the industrial partner, reducing the risk of musculoskeletal disorders; 2) reduces the risk of shock injuries to the internal walls of the turbine; 3) provides an optimal choice of the appropriate assistive equipment for the assembly station.
Finally, it should be noted that the main limitation of our study is that it is a case study. Therefore, the generalisation of our results can only be established after multiple case studies.
| Date | 2 Jan 2025 |
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| Original language | French |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Sylvie Nadeau (Supervisor) & Kurt Landau (Co-supervisor) |
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Eko’ola, R. V. (Author),
Nadeau (Supervisor) & Landau (Co-supervisor),
2 Jan 2025Student thesis: Master's thesis › Master in Engineering: Automated Manufacturing Engineering