Effect of Wire Arc Additive Manufacturing Process Parameters on Deposition Behavior of Steel

2021 ◽  
pp. 426-435
Author(s):  
A. A. Kulikov ◽  
A. E. Balanovskii ◽  
M. V. Grechneva
Keyword(s):  
Additive Manufacturing ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Deposition Behavior ◽  
Wire Arc Additive Manufacturing

scholarly journals A High-Throughput Method to Define Additive Manufacturing Process Parameters: Application to Haynes 282

2021 ◽  
Author(s):  
Zahabul Islam ◽  
Ankur Kumar Agrawal ◽  
Behzad Rankouhi ◽  
Collin Magnin ◽  
Mark H. Anderson ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
High Throughput ◽  
Process Parameters ◽  
Manufacturing Process ◽  
High Throughput Method

Learning Algorithm Based Modeling and Process Parameters Recommendation System for Binder Jetting Additive Manufacturing Process

2015 ◽  
Author(s):  
Han Chen ◽  
Yaoyao F. Zhao
Keyword(s):  
Additive Manufacturing ◽  
Product Quality ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Process Model ◽  
Recommendation System ◽  
Powder Materials ◽  
Quality Properties ◽  
Binder Jetting ◽  
Printing Time

Binder Jetting (BJ) process is an additive manufacturing process in which powder materials are selectively joined by binder materials. Products can be manufactured layer by layer directly from 3D model data. It is not always easy for manufacturing engineers to choose proper BJ process parameters to meet the end-product quality and fabrication time requirements. This is because the quality properties of the products fabricated by BJ process are significantly affected by the process parameters. And the relationships between process parameters and quality properties are very complicated. In this paper, a process model is developed by Backward Propagation (BP) Neural Network (NN) algorithm based on 16 groups of orthogonal experiment designed by Taguchi Method to express the relationships between 4 key process parameters and 2 key quality properties. Based on the modeling results, an intelligent parameters recommendation system is developed to predict end-product quality properties and printing time, and to recommend process parameters selection based on the process requirements. It can be used as a guideline for selecting the proper printing parameters in BJ to achieve the desired properties and help to reduce the printing time.

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