Analytical modelling for prediction and prevention of overflow occurrence in wire-based additive manufacturing

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, (Formula presented.). Comprehensive experiments show that when the (Formula presented.) 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.