Initial Investigation into Design Best Practices of Wire Arc Additive Manufacturing

Wire arc additive manufacturing (AM) has garnered attention in recent research, yet a comprehensive set of "best practices" for design remains notably absent in the literature. This research initiative, conducted at Mississippi State University and funded through the US Army Corp of Engineers Engineering Research and Development Center, sought to address this gap by exploring the Wire arc AM process's intricacies. Focusing on the inter-relationships between machine parameters, geometric outcomes, and overall build quality, our team utilized ES 120S-G steel to print six distinct geometric shapes. These shapes, including a single thin wall, cylinder, S-wall, rectangular block, ramp, and block figure 8, were chosen for their simplicity in programming the Wire arc AM robot and their coverage of essential geometric variables such as overall weld bead thickness, sharpness of corners, edge smoothness, straightness, and concentricity. By employing various machine parameters, our study aimed to uncover insights that contribute to the identification of overarching design rules or "best practices" for Wire arc AM. In this paper, we delve into the lessons learned from these six simple builds, showcasing the iterative process of refining machine parameters and extracting knowledge from each geometric shape. Our goal is to advance the understanding of ER 120S-G steel behavior during Wire arc welding, ultimately establishing guidelines for optimizing machine parameters. Beyond contributing to the ongoing refinement of Wire arc AM processes, these findings set the groundwork for informed design considerations, thereby fostering advancements in additive manufacturing and elevating the overall quality of Wire arc AM designs.

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Publication Details

Published
2024-10-01
DOI
https://doi.org/10.21872/2024iise_6842
Primary Topic
Additive Manufacturing Materials and Processes
Type
article
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article

Initial Investigation into Design Best Practices of Wire Arc Additive Manufacturing

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Additive Manufacturing Materials and Processes
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Initial Investigation into Design Best Practices of Wire Arc Additive Manufacturing

Emily Wall, Gehendra Sharma, Elton Freeman, John Austin, Walker Jarrell
article en

Abstract

Wire arc additive manufacturing (AM) has garnered attention in recent research, yet a comprehensive set of "best practices" for design remains notably absent in the literature. This research initiative, conducted at Mississippi State University and funded through the US Army Corp of Engineers Engineering Research and Development Center, sought to address this gap by exploring the Wire arc AM process's intricacies. Focusing on the inter-relationships between machine parameters, geometric outcomes, and overall build quality, our team utilized ES 120S-G steel to print six distinct geometric shapes. These shapes, including a single thin wall, cylinder, S-wall, rectangular block, ramp, and block figure 8, were chosen for their simplicity in programming the Wire arc AM robot and their coverage of essential geometric variables such as overall weld bead thickness, sharpness of corners, edge smoothness, straightness, and concentricity. By employing various machine parameters, our study aimed to uncover insights that contribute to the identification of overarching design rules or "best practices" for Wire arc AM. In this paper, we delve into the lessons learned from these six simple builds, showcasing the iterative process of refining machine parameters and extracting knowledge from each geometric shape. Our goal is to advance the understanding of ER 120S-G steel behavior during Wire arc welding, ultimately establishing guidelines for optimizing machine parameters. Beyond contributing to the ongoing refinement of Wire arc AM processes, these findings set the groundwork for informed design considerations, thereby fostering advancements in additive manufacturing and elevating the overall quality of Wire arc AM designs.

Openalex Percentile: Top 70%
Additive Manufacturing Materials and Processes
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