Analytical modelling for prediction and prevention of overflow occurrence in wire-based additive manufacturing
Year: 2025
Type: article
Abstract: Increasing deposition rate is essential for higher productivity of additive manufacturing (AM). However, a high deposition rate usually requires high heat input to fully melt the fast-fed material, which could lead to defects due to molten material overflow. This paper presents a thermo-capillary-gravity model for predicting the overflow occurrence based on the analytically calculated reciprocal Bond number, 1/Bo. Comprehensive experiments show that when the 1/Bo is no greater than 0.74, or the bead height is no less than 1.16 times the capillary length, overflow is highly likely to occur. Two different steel wire-based AM processes were employed to validate the model, demonstrating an overall accuracy of 84%-93%. It is found that both energy and material inputs per unit length significantly affect the molten material overflow, and hence they can be adjusted to prevent overflow. The validated analytical modelling approach enables efficient prediction and control of overflow for a high deposition rate wire-based AM process.
Source: Virtual and Physical Prototyping
Authors: Alireza M. Haghighi, Jialuo Ding, Yongle Sun, Wojciech Suder, Chong Wang, Paul Poulain, Xin Chen, Stewart Williams
Institution: Cranfield University
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,070
OpenAlex ID: W4413835329