Comparison of observational ergonomic methods: a case study in the automotive industry

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Conference Proceedings
Authors: André CardosoHatice K GonçalvesGuilherme Deola BorgesAna PombeiroAna ColimPaula CarneiroPedro Arezes

Abstract: The increased automation of the car manufacturing process, in which much of the assembly has been delegated from man to machine, has done much to relieve workers of the burden of heavy lifting. However, despite ergonomic improvements in the workplace, many jobs still require workers to perform repetitive tasks [1]. In the automotive industry, Work-related Musculoskeletal Disorders (WMSD) are one of the most common occupational problems due to repetitive working tasks. Workers that perform manual work are often prone to awkward postures, repetitive movements, forceful exertions, and overextensions, which are some of the main factors for the arising of WMSD [2]. Besides, these work-related factors, also the personal factors contribute to the occurrence of this kind of injury, making WMSD a complex condition that involves contributions from many factors [3,4]. The current study aims to compare different observational methods commonly used to assess the WMSD risk in repetitive tasks. To accomplish this goal a case of study in assembly workstation of an automotive company in Portugal was applied. It was selected methods that are widely used by ergonomists and are validated for implementation in the industry [5,6]. Therefore, the following methods were applied to an assembly workstation: (i) Rapid Upper-Limb Assessment (RULA), (ii) Occupational Repetitive Actions (OCRA), (ii) Key Indicator Method – Manual Handling Operations (KIM-MHO), and (iv) Revised Strain Index (RSI) This multi-method approach was very important, as it allowed for a more comprehensive assessment, which will support the proposals for improvement The results show that workstation present a considerable WMSD risk in 3 of 4 methods applied. These results suggest that a change to the workstation is necessary. A possible solution would be to implement a Human-robot collaboration solution, in order to reduce the physical demands associated with repetitive movements [7] to which workers are subjected. [1]Spallek, M.; Kuhn, W.; Uibel, S.; Van Mark, A.; Quarcoo, D. Work-Related Musculoskeletal Disorders in the Automotive Industry Due to Repetitive Work - Implications for Rehabilitation. J. Occup. Med. Toxicol. 2010, 5 (1), 1–6. https://doi.org/10.1186/1745-6673-5-6.[2]Naik, G.; Khan, M. R. Prevalence of MSDs and Postural Risk Assessment in Floor Mopping Activity Through Subjective and Objective Measures. Saf. Health Work 2020, 11 (1), 80–87. https://doi.org/10.1016/j.shaw.2019.12.005.[3]Park, J.; Kim, Y.; Han, B. Work Sectors with High Risk for Work-Related Musculoskeletal Disorders in Korean Men and Women. Saf. Health Work 2018, 9 (1), 75–78. https://doi.org/10.1016/j.shaw.2017.06.005.[4]Thetkathuek, A.; Meepradit, P.; Sa-ngiamsak, T. A Cross-Sectional Study of Musculoskeletal Symptoms and Risk Factors in Cambodian Fruit Farm Workers in Eastern Region, Thailand. Saf. Health Work 2018, 9 (2), 192–202. https://doi.org/10.1016/j.shaw.2017.06.009.[5]Dempsey, P. G.; Mcgorry, R. W.; Maynard, W. S. A Survey of Tools and Methods Used by Certified Professional Ergonomists. Appl. Ergon. 2005, 36, 489–503. https://doi.org/10.1016/j.apergo.2005.01.007.[6]Pascual, S. A.; Naqvi, S. An Investigation of Ergonomics Analysis Tools Used in Industry in the Identification of Work-Related Musculoskeletal Disorders An Investigation of Ergonomics Analysis Tools Used in Industry in the Identification of Work-Related Musculoskeletal Disorders. Int. J. Occup. Saf. Ergon. 2015, 3548 (2), 237–245. https://doi.org/10.1080/10803548.2008.11076755.[7]Colim, A.; Faria, C.; Cunha, J.; Oliveira, J.; Sousa, N.; Rocha, L. Physical Ergonomics Improvement and Safe Design of an Assembly Workstation with Collaborative Robotics. Saf. (Unpublished under-review) 2021, 1–19.

Keywords: Assembly tasks, Automotive industry, Ergonomics, Observational methods, Multi-method assessment

DOI: 10.54941/ahfe1002650

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