Injecting Human Factors into Early-Phase Design 

Although computational design tools, such as generative design (GD), have paved the way for products with improved mechanical performance (e.g., improving fuel efficiency by reducing part weight), many fall short of considering human factors, isolating HFE principles from early design activities.

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The D-HIL design framework injects human factors engineering principles into the computational or virtual environment via digital human modeling (DHM) research. Experimental- and simulation-based DHM strategies, along with emerging technologies (e.g., virtual reality, motion capture), help facilitate the prediction of human well-being and overall system performance early in the design process. 

Digital Human Modeling 

Within the D-HIL framework, conceptual design ideas iteratively modified through DHM and computer-aided engineering (CAE) in a parallel sequence - before ever getting into the prototyping phase. This way, human needs, abilities, and limitations are considered early in the design process. Design errors or human-product incompatibilities can be captured before prototyping begins.

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Data related to human attributes can come from experimental or computational methods. For example, human posture data can come from either a manual anthropometric setup or various digital systems (motion capture, eye-tracker, a motion prediction model). If manual methods are used, descriptive task parameters (e.g., push-pull distance, lift-lower height) are inserted manually to generate ergonomics evaluations. The CAE model can be updated parametrically, depending on the changes required after each ergonomic and structural assessment. The effects of variations on the CAE model in terms of ergonomics and structural integrity can be cross-checked simultaneously.