Manufacturing processes are based on human labour and the symbiosis between human
operators and machines. The operators are required to follow predefined sequences
of movements. The operations carried out at assembly lines are repetitive, being identified
as a risk factor for the onset of musculoskeletal disorders.
Ergonomics plays a big role in preventing occupational diseases. Ergonomic risk
scores measure the overall risk exposure of operators however these methods still present
challenges: the scores are often associated to a given workstation, being agnostic to the
variability among operators. Observation methods are most often employed yet require a
significant amount of effort, preventing an accurate and continuous ergonomic evaluation
to the entire population of operators. Finally, the risk’s results are rendered as index
scores, hindering a more comprehensive interpretation by occupational physicians.
This dissertation developed a solution for automatic operator risk exposure in assembly
lines. Three main contributions were presented: (1) an upper limb and torso
motion tracking algorithm which relies on inertial sensors to estimate the orientation of
anatomical joints; (2) an adjusted ergonomic risk score; (3) an ergonomic risk explanation
approach based on the analysis of the angular risk factors. Throughout the research, two
experimental assessments were conducted: laboratory validation and field evaluation.
The laboratory tests enabled the creation of a movements’ dataset and used an optical
motion capture system as reference. The field evaluation dataset was acquired on an automotive
assembly line and serve as the basis for an ergonomic risk evaluation study. The
experimental results revealed that the proposed solution has the potential to be applied
in a real environment. Through direct measures, the ergonomic feedback is fastened, and
consequently, the evaluation can be extended to more operators, ultimately preventing,
in long-term, work-related injuries
