Robust Multi-objective Optimisation of Weld Bead Geometry for Additive Manufacturing

Mehnen, J.^{1, a}; Trautmann, H.^{2, b}

1)

Decision Engineering Centre, University Cranfield, Cranfield, United Kingdom

2)

Lehrstuhl Computergestützte Statistik, Technische Universität Dortmund, Vogelpothsweg 87, 44227 Dortmund

a) j.mehnen@cranfield.ac.uk; b) trautmann@statistik.tu-dortmund.de

Kurzfassung

Additive manufacturing is a technique for generating complex shaped rigid metal workpieces. During the welding process material is deposited in a sequential layer-by-layer fashion to build up workpieces in a highly efficient manner. Due to technical fluctuations the process is prone to noise influencing the weld bead quality properties of depth of penetration or undercut. Controlling these contradicting properties is necessary for generating high quality workpieces. Capturing manufacturer’s experience via desirability functions and utilizing a new robust multi-objective evaluation technique in an evolutionary environment it is possible to generate robust best compromise solutions in this complex noisy real-world application.

Schlüsselwörter

Additive Manufacturing, Multi-objective Optimisation, Desirability Function, Robust Evaluation, Noise

Veröffentlichung

In: ICME 2008, 23.7.-25.7. 2008, Naples, Italy