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Project Overview

Project Code: ED 12

Project name:

Metamodelling of the free-form bending process

TUM Department:

ED - Mechanical Engineering

TUM Chair / Institute:

Chair of Metal Forming and Casting

Research area:

Metal forming, Process optimisation, Metamodelling

Student background:

Computer EngineeringComputer Science/ InformaticsMathematicsMechanical Engineering

Further disciplines:

Planned project location:

Technical University of Munich
Walther-Meißner-Straße 4
85748 Garching
Germany

Project Supervisor - Contact Details


Title:

M.Sc.

Given name:

Lorenzo

Family name:

Scandola

E-mail:

lorenzo.scandola@utg.de

Phone:

+49 89 289 13804

Additional Project Supervisor - Contact Details


Title:

Prof. Dr.-Ing.

Given name:

Wolfram

Family name:

Volk

E-mail:

info@utg.de

Phone:

+49 89 289 13791

Additional Project Supervisor - Contact Details


Title:

Given name:

Family name:

E-mail:

Phone:

Project Description


Project description:

Motivation

Free-form bending is an innovative manufacturing process for realising structural frames for the automotive sector. It allows to arbitrarily bend complex geometries, consisting of variable bending radii and angles as well as splines, with the employment of a single tool.

(Chair webpage, Media, Video: Free-form bending at utg)



Aims and objectives

The free-form bending process starts with the definition of the target bending line geometry, which is read from a CAD file and turned into a NURBS curve. After the determination of the machine kinematics the part is produced and measured with an optical system, resulting in an .stl mesh file.

In order to be able to compare the target and the obtained part, the experimental measurement must be reconstructed in a NURBS curve exploiting the same model used for the target. In order to do so, a metamodel able to describe the target and the obtained curves with just a different set of parameters is to be developed and implemented.

In this work you will learn to apply an algorithmic solution to a industrial manufacturing process and to validate your results. Possible milestones could be:

Extraction and filtering of relevant data points
Alignment and orientation of the fitting data with respect to the target
Investigation of different interpolation and approximation algorithms featuring regularisation
Evaluation of artificial intelligence tools for the definition of the metamodel

Working hours per week planned:

40

Prerequisites


Required study level minimum (at time of TUM PREP project start):

3 years of bachelor studies completed

Subject related:

Prerequisites
Experience in Python
Independent way of working and initiative

Other:

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