A framework for multi-objective optimisation of 3D part-build orientation with a desired angular resolution in additive manufacturing processes

ABSTRACT

In additive manufacturing processes, the part build orientation (PBO) is one of the most important factors that can affect the characteristics of the quality product such as the amount of support structure and the surface roughness. In most previous methods, the optimal PBO cannot be determined with high precision and accuracy in 3D space. In this paper, to find the precise and accurate optimal PBO with a desired angular accuracy, a new Taguchi-based method, called the Zooming-Taguchi method, is proposed. The proposed simulation-based method can precisely find the optimal PBO in absence of the noise effects. In order to find the optimal PBO with the desired angular resolution, the zooming procedure is iteratively carried out on factor levels through a clustering strategy. Finally, to validate the proposed method, two case studies are considered and the obtained results are compared with conventional methods in the literature and the experimental results.

KEYWORDS:

• Additive manufacturing
• part build orientation
• multi-objective optimal design
• Taguchi-based method

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Amir Hosein Golmohammadi received the M.Sc. degree in Mechanical Engineering from Sharif University of Technology, Tehran, Iran (2017). He is currently a research assistant in the Precision Manufacturing Lab at Sharif of University of Technology. His main research interests are Additive Manufacturing Processes, Optimal Multidisciplinary Design, and Optimization Algorithms.

Saeed Khodaygan received the Ph.D. degree in Mechanical engineering from Sharif University of Technology in Iran (2011). He is currently working as an Assistant Professor in Department of Mechanical Engineering at Sharif University of Technology, Tehran, Iran. His major research interests are Optimal Multidisciplinary Design, Computer-aided Tolerance Design, Design for Additive Manufacturing, Measurement Systems and Instrumentation, Mechanical System Identification, Applications of Artificial Intelligence to Engineering.