Task Time Estimations in an Optimization-based Digital Human Modelling Tool - A Case Study

Paper i proceeding, 2025

Optimization-based digital human modelling (DHM) can compute manikin motions for unique work tasks, requiring no motion capturing or motion data manipulation to simulate new work tasks. Also, optimization-based DHM can consider prevailing force and torque exertions, e.g. pushing or twisting, in the motion computations. This makes optimization-based DHM well suited for assessing workstation designs early in virtual development phases. When using optimization-based DHM to simulate work tasks and determine task times in settings such as manual assembly, it is crucial that the manikin motion durations can be set to comply with predetermined motion time systems (PMTS) data. As part of realizing this objective, this study compares assembly times generated by an optimization-based DHM tool, where durations of discrete manikin motions are determined based on PMTS data, against an industrial use case with known assembly times, determined according to the company standard. The comparison aims to identify the differences between the times generated by the DHM tool and the times determined in accordance with the company standard, understand why they occur and how they potentially can be addressed. The findings support establishing a road map for future research and development for improving task time estimations in optimization-based DHM.