Volume 18, Issue 3 (2018)                   Modares Mechanical Engineering 2018, 18(3): 115-125 | Back to browse issues page

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Golmohammadi A H. Comparison of analytical and experimental design -based optimization methods to determine the optimum part build orientation in rapid prototyping processes. Modares Mechanical Engineering. 2018; 18 (3) :115-125
URL: http://mme.modares.ac.ir/article-15-6772-en.html
1- Department of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Abstract:   (3497 Views)
Rapid prototyping (Additive manufacturing or 3D printing) is defined as the process that can build 3D physical part from the designed model in CAD software by joining materials directly. In the RP process, the orientation pattern of the part is one of the most important factors that significantly affect the product properties such as the build time, the surface roughness, the mechanical strength, and the amount of support material. The build time and the surface roughness are the more imperative criteria than others that can be considered to find the optimum orientation of parts. In this paper, two algorithms based on analytical and empirical optimization methods are presented to determine optimum part build orientation in order to minimize build time and surface roughness. To implement this method, the user's part is received in standard triangle language (STL) format. Then, using the geometric characteristics and type of part orientation, the build time and the average of surface roughness is calculated. In order to determine the optimum part build orientation, two analytical (NSGA-II method) and experimental (new and developed Taguchi method) optimization methods have been used. After introducing the steps of these two methods, in order to determine optimum part build orientation, the steps of these two proposed algorithms are implemented on a part as a case study and obtained results are compared and discussed.
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Article Type: Research Article | Subject: Manufacturing Methods
Received: 2017/11/13 | Accepted: 2018/02/3 | Published: 2019/02/23

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