A Machine Learning-Based Approach for Quick Evaluation of Live Simulations in Embodiment Design

Sauer C, Gerschütz B, Bernsdorf J, Schleich B, Wartzack S (2022)


Publication Type: Journal article

Publication year: 2022

Journal

Book Volume: 2

Pages Range: 1757-1766

DOI: 10.1017/pds.2022.178

Abstract

Supporting product developers in early design phases with Live-Simulation can enhance the quality of early product designs. Live-Simulation can also facilitate a democratization of simulation and puts away pressure from simulation experts. In this paper, a machine learning based quick evaluation tool is proposed to support product developers in interpreting Live-Simulation results. The proposed tool enables a quick evaluation of the Live-Simulation results and enables product developers to further enhance their simulations. The tool is shown within a use case in bike rocker switch design.

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How to cite

APA:

Sauer, C., Gerschütz, B., Bernsdorf, J., Schleich, B., & Wartzack, S. (2022). A Machine Learning-Based Approach for Quick Evaluation of Live Simulations in Embodiment Design. Proceedings of the Design Society, 2, 1757-1766. https://doi.org/10.1017/pds.2022.178

MLA:

Sauer, Christopher, et al. "A Machine Learning-Based Approach for Quick Evaluation of Live Simulations in Embodiment Design." Proceedings of the Design Society 2 (2022): 1757-1766.

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