Comparison of Design Automation and Machine Learning algorithms for creation of easily modifiable splines

DS 101: Proceedings of NordDesign 2020, Lyngby, Denmark, 12th - 14th August 2020

Year: 2020
Editor: Mortensen, N.H.; Hansen, C.T. and Deininger, M.
Author: Gustafsson, Erik Anton; Persson, Johan Alexander; Ölvander, Johan Rolf
Series: NordDESIGN
Institution: Link
Section: Design Support
Page(s): 12
DOI number: https://doi.org/10.35199/NORDDESIGN2020.55
ISBN: 9781912254088

Abstract

To enable easy modification and fine tuning of optimization results in a CAD tool by an engineer a flexible representation of the geometry is needed. Two methods based on machine learning and design automation are compared on the task of creating an easily modifiable spline using a few well-placed control points to approximate a center curve representing an optimized hose route.

Keywords: computer aided design (CAD), design automation, design optimisation, machine learning

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