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Human performance measures such as discomfort and joint displacement play an important role in product design. The virtual human Santos™, a new generation of virtual humans developed at the University of Iowa, goes directly to the CAD model to evaluate a design, saving time and money. This paper presents an optimization-based workspace zone differentiation and visualization. Around the workspace of virtual humans, a volume is discretized to small zones and the posture prediction on each central point of the zone will determine whether the points are outside the workspace as well as the values of different objective functions. Visualization of zone differentiation is accomplished by showing different colors based on values of human performance measures on points that are located inside the workspace. The proposed method can subsequently help ergonomic design.

Using multi-objective optimization, we develop a new human performance measure for direct optimizationbased posture prediction that incorporates three key factors associated with musculoskeletal discomfort: 1) the tendency to move different segments of the body sequentially, 2) the tendency to gravitate to a comfortable neutral position, and 3) the discomfort associated with moving while joints are near their respective limits. This performance measure operates in real-time and provides realistic postures. The results are viewed using Santos™, an advanced virtual human, and they are validated using motion-capture. This research lays groundwork for studying how and why humans move as they do.

An optimization-based method for layout design (also called equipment layout) is presented that is based upon kinetic functions also introduced in this paper. The layout problem is defined by the method whereby positions of target points are specified in the environment surrounding a human. The problem is of importance to ergonomists, vehicle/cockpit packaging engineers, designers of manufacturing assembly lines, and designers concerned with the placement of lever, knobs, and controls in the reachable workspace of a human, but also to users of digital human modeling code, where digital prototyping has become a valuable tool. The method comprises kinematically-driven constraints for reaching the target points and for satisfying the joint ranges of motion. The algorithm is driven by a cost function (also called objective function) that is kinetic in nature to minimize approximate energy consumption and visual discomfort.