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

Dasbach, Thomas ; Lohr, Robin ; Muth, Florian ; Anderl, Reiner (2021)
Self-trained CAD assistance for constraining assemblies based on decision trees and support vector classification.
In: Procedia CIRP, 104
doi: 10.1016/j.procir.2021.11.322
Article, Bibliographie

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.

Item Type: Article
Erschienen: 2021
Creators: Dasbach, Thomas ; Lohr, Robin ; Muth, Florian ; Anderl, Reiner
Type of entry: Bibliographie
Title: Self-trained CAD assistance for constraining assemblies based on decision trees and support vector classification
Language: English
Date: 2021
Publisher: Elsevier B.V.
Journal or Publication Title: Procedia CIRP
Volume of the journal: 104
DOI: 10.1016/j.procir.2021.11.322
URL / URN: https://www.sciencedirect.com/science/article/pii/S221282712...
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.

Uncontrolled Keywords: CAD, Machine Learning, SVC, Decision Trees, Assembly
Additional Information:

Part of special issue: 54th CIRP CMS 2021 - Towards Digitalized Manufacturing 4.0

Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Department of Computer Integrated Design (DiK) (from 01.09.2022 renamed "Product Life Cycle Management")
Date Deposited: 09 Dec 2021 06:16
Last Modified: 09 Dec 2021 06:16
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