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Digital human modelling and the ageing workforce

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posted on 2015-09-16, 13:30 authored by Keith Case, Amjad Hussain, Russell MarshallRussell Marshall, Steve SummerskillSteve Summerskill, Diane GyiDiane Gyi
Digital human modelling (DHM) has often focused on user populations that could be characterised as able-bodied and in the working age group. It is clear however that demographic changes are resulting in older populations in developed countries but this is also becoming increasingly true even in developing countries. The economic pressures of increased life expectancy are resulting in demands for workers to remain in employment well past what would previously have been considered a normal retirement age. In many countries legislation is increasing retirement ages for entitlement to state pensions, and enforceable retirement ages are being outlawed. As a consequence older working populations can be expected. Age in the workforce has many positive aspects including increased experience, wisdom, loyalty and motivation, but an inevitable consequence of ageing is negative effects such as the loss of capabilities in strength, mobility, vision and hearing. The challenge of including older workers is recognised as an important aspect of Inclusive Design and DHM is recognised as a potentially useful method for its implementation. Today’s highly demanding and competitive working environments require the highest levels of productivity from individuals so that overall operational and business objectives can be achieved. DHM-based workplace risk assessment methods have successfully been used to improve working environments by conducting virtual posture based ergonomic risk analysis. Older workers are significantly different from younger workers in terms of their physical, physiological and cognitive capabilities and these capabilities directly or indirectly affect human work performance. This article suggests the use of human capability data in a virtual environment to explore the level of acceptability of a working strategy based on real capability data (joint mobility in this case) of older workers. A case study shows that the proposed DHM-based inclusive design method is useful recommending working strategies that are acceptable for older workers in terms of work productivity, well-being and safety.



  • Mechanical, Electrical and Manufacturing Engineering

Published in

Procedia Engineering


CASE, K. ... et al., 2015. Digital human modelling and the ageing workforce. Procedia Manufacturing, 3, pp. 3694 – 3701.


© The Authors. Published by Elsevier B.V.


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This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

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This paper was presented at the 6th International Conference on Applied Human Factors and Ergonomics AHFE 2015 and the Affiliated Conferences, Caesar's Palace, Las Vegas, USA and published in Procedia Manufacturing by Elsevier under a CC BY NC ND licence.




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