Multi-Objective Optimization of Additive Manufacturing Process - Archive ouverte HAL Access content directly
Journal Articles IFAC-PapersOnLine Year : 2018

Multi-Objective Optimization of Additive Manufacturing Process

(1, 2) , (1, 2) , (1)
1
2

Abstract

This paper presents an approach to analyze the critical drawbacks and attributes of Additive Manufacturing (AM) simultaneously to find the best manufacturing parameters to fabricate the AM products. In this study, Fused Deposition Modeling (FDM) is investigated as a common AM technology. For this purpose, a multi-optimization problem is formulated according to the analysis of FDM technology. In this problem, layer thickness and part orientation are determined as the decision variables which are the important parameters of manufacturing. As objective functions, production time and material mass are considered and the surface roughness of FDM products and mechanical behavior of material are defined as the constraint functions. Different methodologies are developed to model the AM criteria according to these decision variables. To find the optimal solutions for manufacturing, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is used. Finally, a case study highlighted the reliability of the proposed approach.

Dates and versions

hal-02279465 , version 1 (05-09-2019)

Identifiers

Cite

Elnaz Asadollahi-Yazdi, Julien Gardan, Pascal Lafon. Multi-Objective Optimization of Additive Manufacturing Process. IFAC-PapersOnLine, 2018, 51 (11), pp.152-157. ⟨10.1016/j.ifacol.2018.08.250⟩. ⟨hal-02279465⟩

Collections

CNRS UTT
27 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More