Research Papers

Multi-Objective Build Orientation Optimization for Powder Bed Fusion by Laser

[+] Author and Article Information
Salah Eddine Brika

Mechanical Engineering Department,
ADML McGill University,
212, 5000 Bourret Avenue,
Montreal, QC H3W 1L4, Canada
e-mail: sleh.brika@mail.mcgill.ca

Yaoyao Fiona Zhao

Mechanical Engineering Department,
ADML McGill University,
Room 148, 817 Sherbrooke Street West,
Montreal, QC H3A 0C3, Canada
e-mail: yaoyao.zhao@mcgill.ca

Mathieu Brochu

Mining and Materials Engineering Department,
McGill University,
Room 2640, 3610 University Street,
Montreal, QC H3A 0C5, Canada
e-mail: mathieu.brochu@mcgill.ca

Justin Mezzetta

Mining and Materials Engineering Department,
McGill University,
3610 University Street,
Montreal, QC H3A 0C5, Canada
e-mail: justinmezzetta@hotmail.com

Manuscript received July 19, 2017; final manuscript received August 1, 2017; published online September 13, 2017. Editor: Y. Lawrence Yao.

J. Manuf. Sci. Eng 139(11), 111011 (Sep 13, 2017) (9 pages) Paper No: MANU-17-1452; doi: 10.1115/1.4037570 History: Received July 19, 2017; Revised August 01, 2017

This paper proposes an integrated approach to determine optimal build orientation for powder bed fusion by laser (PBF-L), by simultaneously optimizing mechanical properties, surface roughness, the amount of support structure (SUPP), and build time and cost. Experimental data analysis has been used to establish the objective functions for different mechanical properties and surface roughness. Geometry analysis of the part has been used to estimate the needed SUPP and thus evaluate the build time and cost. Normalized weights are assigned to different objectives depending on their relative importance allowing solving the multi-objective optimization problem using a genetic optimization algorithm. A study case is presented to demonstrate the capabilities of the developed system. The major achievements of this work are the consideration of multiple objectives and the establishment of objective function considering different load direction and heat treatments. A user-friendly graphical user interface was developed allowing to control different optimization process factors and providing different visualization and evaluation tools.

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Fig. 1

Optimization algorithm diagram

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Fig. 2

Facet angle computation

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Fig. 3

Minimum angle of overhangs

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Fig. 4

Extrusion offset algorithm

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Fig. 5

Case study of a Ti–6Al–4V part

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Fig. 6

Load direction according to different build orientations

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Fig. 7

Surface roughness evaluation

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Fig. 9

Graphical user interface

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Fig. 10

Requirements frame

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Fig. 11

Optimization results frame

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Fig. 12

Selective laser melting evaluator

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Fig. 13

Optimum build orientation part 1

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Fig. 14

Optimum build orientation part 2




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