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Assembly operators are rarely observed performing one-handed tasks where the unutilized hand is entirely inactive. Therefore, this study was designed to determine the forces applied to supporting hands, by automotive assembly operators, during common one-handed tasks such as hose installations or electrical connections. The data were computed as a percentage of body weight and a repeated measures analysis of variance (ANOVA) (p<0.05) was conducted. Supporting hand forces were observed to range from 5.5% to 12.1% of body mass across a variety of tasks. The results of this study can be used to account for these supporting hand forces when performing a biomechanical/ergonomic analysis.

Due to the challenges in quantifying hand loads in manufacturing environments it is often assumed that the load is evenly distributed between the hands, even when handling parts with non-uniform mass distribution. This study estimated hand loads for six female subjects, when handling a custom part in 8 different configurations (2 weights, 4 CofM locations). The calculated hand loads varied from 20 to 50% of the weight being handled. The magnitude of asymmetrical hand loading depended on both the part orientation and the location of the CoM. Based on this study the knowledge of part weight, CofM location and hand positioning will allow the users of digital human models to perform more realistic and reliable task analysis assessments as the force distributions will be more representative of the actual loading rather than simply assuming the load is evenly distributed between the hands.

The use of digital human models (DHM) to perform geometric evaluations of hand clearances and reach zones has become common practice at Ford Motor Company. Moreover, DHMs have also been used for performing strength evaluations to ensure ergonomically acceptable jobs. A process called Hose Connections Acceptability Ratings (HCAR) was developed to establish insertion force targets in the early phases of product design. Once targets are set, design and release engineers provide design intent data to achieve sign off from manufacturing engineering. The process is complete when the hose efforts are confirmed at physical part validation build events.

Digital Human Models are used extensively in virtual manufacturing to evaluate hand clearance and reach. Spatial assessments of accommodation are typically conducted using digital human models representative of the manufacturing population. Unfortunately, these models are often based on anthropometry gathered from sources that are not representative of the actual target worker population. For example, the size and shape might be based on data from the U.S. military, which differs in .fitness, age, and race distributions from the typical automotive manufacturing population. Ford ergonomists traced errors in accommodation predictions to these inaccurate representations. Using a recently developed statistical methodology incorporating principal components analysis, the anthropometry of the target worker population was synthesized. Using these new data, Ford updated the anthropometry of their digital human models to reflect changes due to secular trends in the U.S.