Additive manufacturing (AM) is a layer-by-layer manufacturing process that is termed as the next industrial revolution. AM technology has the potential to accelerate innovation, compress supply chains, minimize materials and energy usage, and reduce waste. The most significant benefit of AM technology is its design freedom to address design complexity with no required additional tooling or assembly. In this technology, 3D structures are fabricated layer upon layer by slicing the CAD model. Selective Laser Melting (SLM) is an additive manufacturing technique widely used to fabricate complex 3D components. SLM has been used successfully in different applications including biomedical, aerospace, automotive, and jewelry industries [
1,
2,
3,
4,
5]. In this process, a laser is scanned over a powder layer and after building one layer, the build plate is lowered by a distance equal to the thickness of the fused layer, and this process of building layers is repeated until fabrication of the whole component is completed [
6].
Figure 1 shows a schematic diagram of the SLM process where the main components are a powder bed or base plate, a powder delivery system, an enclosed chamber for operation in a vacuum or an inert gas, and a laser system [
7]. The chamber or the build plate can be preheated if necessary.
Figure 2 shows the major energy transport mechanisms: conduction, convection, and radiation that results in transient heat distribution in the processed zone. Melt pool dynamics is also influenced by the interaction between the laser and liquid metal during solidification process. The spatial and temporal distribution of temperature within and around the melt pool affects microstructure and process induced residual stress in the final product. The finite element analysis (FEA) approach is used by many researchers to model the SLM process, thereby developing process maps and predicting microstructure and residual stress [
8,
9]. However, there are many difficulties to accurately capture all the features of the SLM process by finite element modeling. Shi et al. [
10] mentioned about a splash of powder particle in laser beam track. King et al. [
11] discussed strong dynamics of the melted material flow propelled by Marangoni convection during laser melting. Fu et al. [
12] performed comparative analysis of melt pool geometry for SLM of Ti-64 alloy and have found a significant difference between FEA and experimental results. In their work, multiple factors such as the accuracy of the thermal input, temperature-dependent properties of both powder and bulk Ti-64, and laser–material interactions were considered to model the SLM process. Yadroitsev et al. [
3] investigated experimentally measured melt pool dimensions with theoretical calculations at different irradiation time and found a significant difference between these methods. Verhaeghe et al. [
13] created a model for SLM of Ti-64 alloy by considering shrinkage and laser light penetration effects, and studied the influence of incorporating or neglecting evaporation effect in SLM process. Results were not consistent enough to make a conclusion from this study.
Since the SLM is a thermal process, the FEA predicted melt pool temperature and geometry heavily depend on the thermal-mechanical properties of metal powders and melt pool liquid metal. It is thus important to understand the sensitivity of FEA predicted melt pool temperatures to thermal–mechanical–physical properties of SLM materials that can help in filling the gap between experimental and simulation results. This analysis will also be useful in any laser melting process where phase change phenomena (e.g., laser welding process) such as solid–liquid–solid occurs [
14,
15,
16,
17]. In this paper, sensitivity analysis is performed by creating a finite element model in ABAQUS and by monitoring the melt pool peak temperature by perturbing the properties of Ti-6Al-4V such as specific heat, density, and thermal conductivity. The FEA result is first compared with the experimentally measured temperature using an infrared (IR) camera to understand whether the FEM scheme captures the right trend of the melt pool temperature. Then, each material property is perturbed within the FEM code for several combinations of process parameters such as laser power and laser scanning speed and change in peak temperature is recorded. Only high and low laser powers of 400 W and 91 W, and laser scanning speeds of 1100 mm/s and 200 mm/s are considered in this case. At the end, recommendations on which material property/properties have the most significant effect on melt pool peak temperature during SLM build process are provided.