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Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.

Efficient methods for simulating operators performing part handling tasks in manufacturing plants are needed. The simulation of part handling motions is an important step towards the implementation of virtual manufacturing for the purpose of improving worker productivity and reducing injuries in the workplace. However, industrial assembly tasks are often complex and involve multiple interactions between workers and their environment. The purpose of this paper is to present a series of industrial simulations using the Human Motion Simulation Framework developed at the University of Michigan. Three automotive assembly operations spanning scenarios, such as small and large parts, tool use, walking, re-grasping, reaching inside a vehicle, etc. were selected.

This paper will initiate a discussion on automotive industry requirements and associated standardization of digital human modeling software (DHMS) as applied to manufacturing operations. Industry benefits of standardization are vast, making it difficult to identify and provide an exhaustive list. High value benefits will be listed for the purpose of this discussion. Industry users of DHMS will benefit by the standardization of an application programming interface, classification of anthropometry and simulation data translation. A list of high value standardization goals will be provided for the purpose of this discussion. Two examples of standardization goals include 1) a reduction in the time and cost required to integrate research results into commercial software and 2) improved simulation data transfer and linkages between DHMS to simplify the use of multiple tools when analyzing a single problem. This paper will provide an introduction to and proposal for standardization of DHMS.