VR–MOCAP-Enabled Ergonomic Risk Assessment of Workstation Prototypes in Offsite Construction

Abstract

Workers in offsite construction facilities are often exposed to repetitive motion and awkward body postures that are associated with the risk of developing work-related musculoskeletal disorders despite the use of automated equipment on production lines. To reduce the exposure to these risks, an investigation of the physical demands that workstations impose on workers’ bodies is needed. Since traditional methods used to collect human body motions have limitations, such as workplace interruptions and biased results due to subjective observation, this paper proposes a virtual reality (VR)–motion capture (MOCAP)-based ergonomic assessment method to evaluate ergonomic risks in a laboratory setting during the design phase of workstation development. It is expected that the number of iterations of physical workstation prototypes would be reduced if ergonomic risk ratings are identified proactively in the initial phases of workstation design, which would thereby reduce the cost and time required to develop and implement an improved workstation design. The present study includes a feasibility analysis of the proposed method in which participants representative of specific percentiles of the population based on their physical stature were invited to voluntarily participate in a research experiment. The results obtained demonstrate that the proposed method can successfully simulate the elemental motions, referred to as therbligs, of reaching and positioning (Pearson’s correlation coefficient is found to equal 0.80 and 0.94, respectively), while the simulation of the assembling therblig requires further investigation. The contribution of this study is a virtual reality–motion captured-enabled ergonomic risk assessment method applied to workstation design for offsite construction production lines. In addition, the deployment of the proposed method allows a holistic ergonomic assessment that considers objective and subjective parameters.