Temperature profile and melt depth in laser powder bed fusion of Ti-6Al-4V titanium alloy

Progress in Additive Manufacturing, Aug 2017

In this paper, the prediction of temperature profile and melt depth for laser powder bed fusion (L-PBF) of Ti-6Al-4V titanium powder material was performed by numerically solving the heat conduction-diffusion equation using a finite difference method. A review of the literature in numerical modeling for laser-based additive metal manufacturing is presented. Initially, the temperature profile along the depth direction into the powder material is calculated for a stationary single pulse laser heat source to understand the transient behavior of the temperature rise during L-PBF. The effect of varying laser pulse energy, average power, and the powder material’s density is analyzed. A method to calculate and predict the maximum depth at which localized melting of the powder material occurs is provided.

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Temperature profile and melt depth in laser powder bed fusion of Ti-6Al-4V titanium alloy

Temperature profile and melt depth in laser powder bed fusion of Ti-6Al-4V titanium alloy Luis E. Criales 0 1 Tug˘rul O¨ zel 0 1 Titanium 0 1 0 Manufacturing Automation Research Laboratory, Department of Industrial and Systems Engineering, Rutgers State University of New Jersey , 96 Frelinghuysen Road, Piscataway, NJ 08854 , USA 1 & Tug ̆rul O ̈ zel In this paper, the prediction of temperature profile and melt depth for laser powder bed fusion (L-PBF) of Ti-6Al-4V titanium powder material was performed by numerically solving the heat conduction-diffusion equation using a finite difference method. A review of the literature in numerical modeling for laser-based additive metal manufacturing is presented. Initially, the temperature profile along the depth direction into the powder material is calculated for a stationary single pulse laser heat source to understand the transient behavior of the temperature rise during L-PBF. The effect of varying laser pulse energy, average power, and the powder material's density is analyzed. A method to calculate and predict the maximum depth at which localized melting of the powder material occurs is provided. Lasers; Powder bed fusion; Thermal; Modeling 1 Introduction Laser-based additive manufacturing (3-D printing) technology has been rapidly growing and finding applications in various industries including medical implants, automotive and aerospace parts with complex geometries and structures [ 1 ]. Specifically, laser powder bed fusion (LPBF) processes such as direct metal laser sintering (DMLSTM), selective laser melting (SLMTM), LaserCUSINGTM, direct metal production (DMPTM), and laser metal fusion (LMFTM) have been receiving a lot of attention [ 2 ]. However, the build part quality and process performance, structural integrity, mechanical properties and related processing times are not at the desired industryready levels. Predictive process modeling and optimization for improved dimensional quality, product reliability, and overall productivity are of great interest to the current, ongoing research efforts [ 3–7 ]. This work gives a rapid calculation technique for predicting temperature profile and melt depth of metal powder material during laser melting. It uses pulsed laser heat source to acquire transient temperature behavior and enables studying the influence of process input parameters and powder material properties on the depth of melted material which is very practical for industrial applications. Selective laser melting is an additive manufacturing process that directly and rapidly fabricates three-dimensional parts by focusing and fully melting metallic powders at selective locations and subsequently allowing for solidification. In laser melting process, the powder material is completely melted and solidified, as opposed to laser sintering processes where metal powder material is sintered, or partially melted [ 5, 8, 11 ]. Both groups of processes utilize similar operational set-ups typically requiring a high power fiber laser source, a beam delivery lens system, a scanning mirror, a metal powder supply, a recoater roller or blade, and a build platform, (see Fig. 1). When comparing laser melting to other manufacturing techniques, the L-PBF process has some clear advantages which can be listed as (1) high flexibility in manufacturing complex shapes, (2) quick process set-up avoiding the need for tooling, and (3) high suitability for product customization and use of different powder materials. These advantages allow for quick transition between manufacturing products of different geometries within the same station. The most attractive feature of laser powder bed fusion is the ability to use this process to produce highly complex geometries and structures that would normally not even be feasible using conventional manufacturing processes. However, laser melting has a major disadvantage: the laser heating process is known for its rapid heating times and unstable cooling times, which result in the formation of pores and voids in the microstructure, which often lead to reduced material density and loss of dimensional accuracy and process repeatability. 2 Literature review Temperature distribution possesses a significant factor in the resulting properties of the fabricated components using laser powder bed fusion or laser cladding processes. Therefore, accurately describing the temperature distribution during and after the process is vital to obtaining highquality samples. The temperature distribution for L-PBF can be calculated using either an analytical solution approach or a numerical solution approach. Furthermore, a numerical solution can be obtained two-fold with a finite element analysis (FEA) approach, and by means of applying the finite difference method (FDM). L-PBF and SLS processes use powder material which has different thermal properties when compared to the bulk (fully dense) material. Gusarov et al. [ 9 ] established a model to cal (...truncated)


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Luis E. Criales, Tuğrul Özel. Temperature profile and melt depth in laser powder bed fusion of Ti-6Al-4V titanium alloy, Progress in Additive Manufacturing, 2017, pp. 1-9, DOI: 10.1007/s40964-017-0029-8