Work

Self-trained CAD assistance for constraining assemblies based on decision trees and support vector classification

Year: 2021

Type: article

Abstract: In this publication a concept for a self-trained assistance is presented, which places a part, selected by the designer, into an assembly and fixates it with constrains. Therefor all selectable parts are classified by the assistance beforehand. In the process of developing the classification several algorithm were tested and compared regarding speed and precision. To place and constrain the parts, decision trees for supervised learning were arranged in a multi-step structure. Furthermore, the implementation in the CAD environment Fusion 360 as well as the limitations and potentials of the concept are discussed.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2021.11.322

Authors: Thomas Dasbach, Robin Lohr, Florian Muth, Reiner Anderl

Institution: Technische Universität Darmstadt

Language: English

Topic: Manufacturing Process and Optimization

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W3215200717

FWCI: 0.109

Cites: 7

Cited by: 1

Related to: 10