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When designing a workplace with manual material handling tasks, it is important to consider both production and ergonomics. We developed an automated workplace design methodology that addresses production and ergonomics for tasks involving a handled mass of up to 23 kg. This process combines optimisation and a Digital Human Modelling (DHM) simulation, which yield the production and ergonomic measures. The task cycle time in current DHM simulations is based on Predetermined Motion Time Systems (PMTS). To address reservations about the time prediction accuracy of PMTS, we developed a new time prediction model that takes the influence of the handled mass into consideration. Our model and optimisation process were evaluated by using a case study of a box conveying workplace design. The time prediction model results did indeed agree with the real mass handling behaviour. Three design approaches (objective functions) were compared: considering only production, only ergonomics and both production and ergonomics. Each approach resulted in a different optimal solution.

This study investigated the hypothesis that the length-tension relation of the torso erectors would be linear, mirroring the observed linear increase in extension strength capability toward full flexion. The effect of torso extension velocity on the tension capability of these muscles was also investigated for common motion speeds. A myoelectric-based approach was used wherein a dynamic biomechanical model incorporating active and passive tissue characteristics provided muscle kinematic estimates during controlled sagittal plane extension motions. A double linear optimization formulation from the literature provided muscle tension estimates. The data of five male subjects supported the hypothesis of a linear length-tension relation toward full flexion for both the erector spinae and latissimus muscles. Velocity trends agreed with the predicted by Hill's exponential relation, although linear trends were found to fit the data almost as well. The results have implications for muscle tension estimation in biomechanical torso modeling, and suggest a possible low back pain injury mechanism through tissue strain while lifting in fully flexed postures.

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Detailed anthropometric data are valuable in making well-informed and responsible design decisions. However, such data are available only for a few user populations around the world. More widely-available information is in the form of summary statistics (e.g., means and standard deviations) and the values of body measures at certain key percentiles (e.g., 5 th , 50 th , 95 th). Such information, while useful, is not suitable for in-depth analyses of a population's variability, since it does not allow for the consideration of correlations between different body measures, does not describe irregular distributions of body dimensions, etc. This paper presents a new methodology that utilizes values of body measures at different percentiles in synthesizing a detailed anthropometric database for a virtual population of users. The procedure is demonstrated in the context of Japanese civilian youth and U.S. military, and is shown to be simple, accurate, easy to use, and applicable across these two anthropometrically dissimilar populations. The case study shows that the virtual population is statistically equivalent to the actual target population in a number of ways. In addition to achieving statistical equivalence with the actual population's body dimensions, the method also ensures that the synthesized individuals are composed of appropriate and realistic body proportions and combinations of anthropometry.

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