An analytical model for estimating process parameters input in L-DED based on bead geometry

Abstract

Additive manufacturing of metal alloys via laser Directed Energy Deposition (L-DED) has been gaining popularity due to its potential to repair and create new features/components, enabling new applications for built parts. The success of L-DED operations hinges on the precise control of printing parameters, including laser power, scanning speed, and powder feed rate. These parameters significantly influence heat distribution during printing, directly impacting the quality of the resulting parts. Thus, defining an efficient methodology to find a good correlation between these parameters for the printing process is crucial to boost part production, as it reduces the time-consuming trial-and-error parameter tuning process. In this context, our study introduces an analytical model that predicts printing parameters based on the deposited material volume along track lines. Deposition was carried in stainless steel 316L with different values for laser power (ranging from 500 to 750W with 50W increments), scanning speed (from 400 to 700mm/min with 100mm/min increments), and powder feed rate (6.4,8.0 and 10.0g/min). The experimental data verified the effectiveness of the proposed model, demonstrating its potential to standardize the first step of printing process and expedite the initial search for optimal printing parameters in L-DED. The model provided accurate initial estimates of laser power, with a maximum relative error of 12%, particularly for the optimum mass flow rate (ṁ) of 8.0g/min. Beyond its benefits to the L-DED process, this analytical solution contributes to experimental practices by offering an efficient method for predicting material deposition volume during printing. Thus, our work underscores the significance of optimizing printing parameters to achieve high-quality parts and provides a valuable reference for future research and studies in the field of L-DED.