Automatic assembly sequencing and visualization tools are valuable in determining the best assembly sequences, but without Human Factors and Figure Models (HFFMs) it is difficult to evaluate or visualize human interaction. In industry, accelerating technological advances and shorter market windows have forced companies to turn to an agile manufacturing paradigm. This trend has promoted computerized automation of product design and manufacturing processes, such as automated assembly planning. However, all automated assembly planning software tools assume that the individual components fly into their assembled configuration and generate what appear to be perfectly valid operations, but in reality some operations cannot physically be carried out by a human. For example, the use of a ratchet may be reasoned feasible for an assembly operation; however, when a hand is placed on the tool the operation is no longer feasible, perhaps because of inaccessibility, insufficient strength or human interference with assembly components. Similarly, human figure modeling algorithms may indicate that assembly operations are not feasible and consequently force design modifications, however, if they had the capability to quickly generate alternative assembly sequences, they might have identified a feasible solution. To solve this problem, HFFMs must be integrated with automated assembly planning which allows engineers to quickly verify that assembly operations are possible and to see ways to make the designs even better. This paper presents a framework for integrating geometry-based assembly planning algorithms with commercially available human figure modeling software packages. Experimental results to selected applications along with lessons learned are presented.
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