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Simulation and Ergonomic Analysis of a Very Tall Male Driving an Excavator in RAMSIS

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HCI International 2022 – Late Breaking Papers: Ergonomics and Product Design (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13522))

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Abstract

This paper aims to analyze the comfort level of a very tall mall driving an excavator. An ergonomic analysis is then performed on the manikin to examine areas of discomfort while in the driving position. This analysis is particularly interesting to people in industries where excavators are used, but it can also be applied to the general population as cars have a similar interior setup consisting of a steering wheel, seat, and the floor between. Therefore, the conclusions drawn and recommendations made at the end of this paper could be made applicable to standard driving scenarios. This model was made in Human Solution’s RAMSIS and the analysis was performed using the same software. It was found through the “Comfort Feeling” analysis that discomfort occurred mostly in the shoulders and neck as well as in the left and right legs. The only areas that did not experience as much discomfort were the right and left arms, back, and buttocks. It is worth noting however that this could be due to most of the strain being put on the previously mentioned areas that experience the highest discomfort. There was an overall very high discomfort feeling of 6.46 (compared to a discomfort threshold of 3.5), with uncomfortable fatigue and health values. Recommendations to reduce these include seat adjustment and steering wheel adjustment.

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References

  1. Sánchez, A.: The Importance of Ergonomics in Industrial Engineering. Industrial Engineering & Management 03(01), OMICS (2014)

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Correspondence to Vincent G. Duffy .

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Buisson, P., Duffy, V.G. (2022). Simulation and Ergonomic Analysis of a Very Tall Male Driving an Excavator in RAMSIS. In: Duffy, V.G., Rau, PL.P. (eds) HCI International 2022 – Late Breaking Papers: Ergonomics and Product Design. HCII 2022. Lecture Notes in Computer Science, vol 13522. Springer, Cham. https://doi.org/10.1007/978-3-031-21704-3_8

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  • DOI: https://doi.org/10.1007/978-3-031-21704-3_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-21703-6

  • Online ISBN: 978-3-031-21704-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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