scholarly journals Build Orientation Optimization Problem in Additive Manufacturing

2018 ◽  
pp. 669-682 ◽  
Author(s):  
Ana Maria A. C. Rocha ◽  
Ana I. Pereira ◽  
A. Ismael F. Vaz
Keyword(s):  
Additive Manufacturing ◽  
Optimization Problem ◽  
Build Orientation ◽  
Orientation Optimization

Part Build Orientation Optimization and Neural Network-Based Geometry Compensation for Additive Manufacturing Process

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Sushmit Chowdhury ◽  
Kunal Mhapsekar ◽  
Sam Anand
Keyword(s):  
Neural Network ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Surface Finish ◽  
Quality Measurement ◽  
Dimensional Accuracy ◽  
Build Orientation ◽  
Part Quality ◽  
Heating And Cooling ◽  
Orientation Optimization

Significant advancements in the field of additive manufacturing (AM) have increased the popularity of AM in mainstream industries. The dimensional accuracy and surface finish of parts manufactured using AM depend on the AM process and the accompanying process parameters. Part build orientation is one of the most critical process parameters, since it has a direct impact on the part quality measurement metrics such as cusp error, manufacturability concerns for geometric features such as thin regions and small fusible openings, and support structure parameters. In conjunction with the build orientation, the cyclic heating and cooling of the material involved in the AM processes lead to nonuniform deformations throughout the part. These factors cumulatively affect the design conformity, surface finish, and the postprocessing requirements of the manufactured parts. In this paper, a two-step part build orientation optimization and thermal compensation methodology is presented to minimize the geometric inaccuracies resulting in the part during the AM process. In the first step, a weighted optimization model is used to determine the optimal build orientation for a part with respect to the aforementioned part quality and manufacturability metrics. In the second step, a novel artificial neural network (ANN)-based geometric compensation methodology is used on the part in its optimal orientation to make appropriate geometric modifications to counteract the thermal effects resulting from the AM process. The effectiveness of this compensation is assessed on an example part using a new point cloud to part conformity metric and shows significant improvements in the manufactured part's geometric accuracy.

A reliable build orientation optimization method in additive manufacturing: the application to FDM technology

2020 ◽  
Vol 108 (1-2) ◽  
pp. 263-276 ◽  
Author(s):  
Luca Di Angelo ◽  
Paolo Di Stefano ◽  
Azam Dolatnezhadsomarin ◽  
Emanuele Guardiani ◽  
Esmaile Khorram
Keyword(s):  
Additive Manufacturing ◽  
Optimization Method ◽  
Build Orientation ◽  
Orientation Optimization

Build orientation optimization for multi-part production in additive manufacturing

2015 ◽  
Vol 28 (6) ◽  
pp. 1393-1407 ◽  
Author(s):  
Yicha Zhang ◽  
Alain Bernard ◽  
Ramy Harik ◽  
K. P. Karunakaran
Keyword(s):  
Additive Manufacturing ◽  
Build Orientation ◽  
Orientation Optimization ◽  
Part Production

Orientation Optimization in Additive Manufacturing: Evaluation of Recent Trends

2021 ◽  
Author(s):  
Jannatul Bushra ◽  
Hannah D. Budinoff
Keyword(s):  
Additive Manufacturing ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Practical Implementation ◽  
Objective Functions ◽  
Build Orientation ◽  
Computational Optimization ◽  
Build Time ◽  
Orientation Optimization

Abstract Build orientation in additive manufacturing influences the mechanical properties, surface quality, build time, and cost of the product. Rather than relying on trial-and-error or prior experience, the choice of build orientation can be formulated as an optimization problem. Consequently, orientation optimization has been a popular research topic for several decades, with new optimization methods being proposed each year. However, despite the rapid pace of research in additive manufacturing, there has not been a critical comparison of different orientation optimization methods. In this study, we present a critical review of 50 articles published since 2015 that proposes a method for orientation optimization for additive manufacturing. We classify included papers by optimization methods used, AM process modeled, and objective functions considered. While the pace of research in recent years has been rapid, most approaches we identified utilized similar objective functions and computational optimization techniques to research from the early 2000s. The most common optimization method in the included research was exhaustive search. Most methods focused on broad applicability to all additive manufacturing processes, rather than a specific process, but a few works focused on powder bed fusion and material extrusion. We also identified several areas for future work including integration with other design and process planning tasks such as topology optimization, more focus on practical implementation with users, testing of computational efficiency, and experimental validation of utilized objective functions.

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