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A MULTI-CRITERIA DECISION-MAKING APPROACH TO OPTIMIZE THE PART BUILD ORIENTATION IN ADDITIVE MANUFACTURING

Published online by Cambridge University Press:  19 June 2023

Mikhailo Sartini ,
Manuguerra Luca ,
Favi Claudio  and
Mandolini Marco
Mikhailo Sartini*
Affiliation:
Università Politecnica delle Marche;
Manuguerra Luca
Affiliation:
Università Politecnica delle Marche;
Favi Claudio
Affiliation:
Università Politecnica delle Marche
Mandolini Marco
Affiliation:
Università Politecnica delle Marche;
*
Sartini, Mikhailo, Università Politecnica delle Marche (UNIVPM), Italy, [email protected]

Abstract

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The part build orientation is a manufacturing variable that must be considered when designing a product to maximise AM opportunities. There are several approaches to selecting the best print direction in the scientific literature by considering different criteria. However, most of the studies are focused on specific AM technologies. It is missing a general method that evaluates a widespread number of criteria. Furthermore, such approaches expect designers establish weights for technical criteria that are too specific, especially during the preliminary design steps. Designers are familiar with criteria like cost-effectiveness, productiveness, quality and mechanical strength.

The paper presents a multi-criteria decision-making approach to optimise the build part orientation in additive manufacturing. The method considers five decision-making criteria (cost-effectiveness, rapidity, productiveness, quality and mechanical strength) and seventeen specific technical criteria. TOPSIS is the method used to optimise the build part orientation. A case study of three components exemplifies the five steps of the procedure.

Keywords

Design for Additive Manufacturing (DfAM)Additive ManufacturingDecision makingTOPSISBuild Part Orientation
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 293 - 302
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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