Reliable and optimized additive manufacturing through numerical process modelling

Goal: Using numerical process modelling in tandem with statistical process design methodologies and dedicated experimental campaigns to establish reliable and optimized AM processes.

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Sankhya Mohanty
added 2 research items
Most commercially available laser powder bed fusion (L-PBF) systems are limited to process one material at a time. The ability to spatially apply multiple materials within the same component will strongly expand the available design space for engineers. A typical problem with multi-material components is stress concentration at discrete material interfaces. Functionally graded interfaces could be used to overcome this limitation. In this work, an open-architecture L-PBF system from Aurora Labs was used to mix and process stainless steel 316L and maraging steel MS1 powder. Thereby, continuous and discrete interfaces between both materials were generated and characterized regarding microstructure, micro-hardness, and elemental composition. An L-PBF process window was found to gradually change the composition of 316L to MS1 creating a continuous interface. The controlled mixing of the powders in each layer indicates the versatility of the powder dispensation setup for multi-material combinations. This contribution will further pave the way towards the development of functionally graded L-PBF components. Metal additive manufacturing, multi-material, functionally graded components, adaptive process control, MS1, 316L
The increasingly complex shapes and geometries being produced using additive manufacturing necessitate new characterization techniques that can address the corresponding challenges. Standard techniques for roughness and texture measurements are inept at characterizing the internal surfaces in freeform geometries. Hence, this work presents a new methodology for extracting and quantitatively characterizing the roughness on internal surfaces. The methodology links X-ray CT with complete roughness characterization of channels manufactured by laser powder bed fusion through a novel image analysis approach of X-ray CT data. Global and local orientation parameters are defined to enable a full 360° description of the roughness inside additively manufactured channels. X-ray CT data is analyzed to generate 3D deviation data – based on which multiple local roughness profiles are extracted and analyzed in accordance with the ISO 4287:1997 standard. To demonstrate the proposed methodology, seven circular 17-4 PH stainless steel channels produced at different inclinations and with a diameter of 2 mm are investigated as a case study. Qualitative and quantitative characterization of the roughness is obtained through the use of the proposed methodology. A strong dependence of the local roughness on the corresponding α and β orientations is found. A simple regression model is subsequently extracted from the calculated roughness values and allows prediction of Ra-values in the channels for the ranges between 0° ≤ α ≤ 90° and 80° ≤ β ≤ 280°. In addition to decreasing the effective hydraulic diameter of a cooling channel, the surface roughness also influences the local Nusselt number, which is quantified using the extracted regression model.
Sankhya Mohanty
added a project goal
Using numerical process modelling in tandem with statistical process design methodologies and dedicated experimental campaigns to establish reliable and optimized AM processes.
Sankhya Mohanty
added an update
Anne-Françoise Obaton and Christopher G. Klingaa presented results from a collaborative project on defining a reference standard for XCT measurements of AM parts at the ICT 2020 conference this month. Find the article here:
Sankhya Mohanty
added 14 research items
The entire process chain of selective laser melting of Ti-6Al-4V is analysed. First, a thermo-fluid dynamical model is used to investigate the temperature profile during the process and estimate the size and shape of the melt pool. The inclusion of the Marangoni effect improves upon previous work by showing the liquid velocity in the melt pool. Next, this information allows us to estimate the morphology of the grains of a part produced by selective laser melting. Finally, a cellular automata is used to model the microstructural evolution during a uniform heat treatment at the beta transus temperature. It is shown that the model shows good agreement with earlier experimental results.
Numerical modelling is increasingly supporting the analysis and optimization of manufacturing processes in the production industry. Even if being mostly applied to multistep processes, single process steps may be so complex by nature that the needed models to describe them must include multiphysics. On the other hand, processes which inherently may seem multiphysical by nature might sometimes be modelled by considerably simpler models if the problem at hand can be somehow adequately simplified. In the present article, examples of this will be presented. The cases are chosen with the aim of showing the diversity in the field of modelling of manufacturing processes as regards process, materials, generic disciplines as well as length scales: (1) modelling of tape casting for thin ceramic layers, (2) modelling the flow of polymers in extrusion, (3) modelling the deformation process of flexible stamps for nanoimprint lithography, (4) modelling manufacturing of composite parts and (5) modelling the selective laser melting process. For all five examples, the emphasis is on modelling results as well as describing the models in brief mathematical details. Alongside with relevant references to the original work, proper comparison with experiments is given in some examples for model validation.
Metal additive manufacturing, despite of offering unique capabilities e.g. unlimited design freedom, short manufacturing time, etc., suffers from raft of intrinsic defects. Porosity is of the defects which can badly deteriorate a part’s performance. In this respect, enabling one to observe and predict the porosity during this process is of high importance. To this end, in this work a combined numerical and experimental approach has been used to analyze the formation, evolution and disappearance of keyhole and keyhole-induced porosities along with their initiating mechanisms, during single track L-PBF of a Ti6Al4V alloy. In this respect, a high-fidelity numerical model based on the Finite Volume Method (FVM) and accomplished in the commercial software Flow-3D is developed. The model accounts for the major physics taking place during the laser-scanning step of the L-PBF process. To better simulate the actual laser-material interaction, multiple reflection with the ray-tracing method has been implemented along with the Fresnel absorption function. The results show that during the keyhole regime, the heating rises dramatically compared to the shallow-depth melt pool regime due to the large entrapment of laser rays in the keyhole cavities. Also a detailed parametric study is performed to investigate the effect of input power on thermal absorptivity, heat transfer and melt pool anatomy. Furthermore, an X-ray Computed Tomography (X-CT) analysis is carried out to visualize the pores formed during the L-PBF process. It is shown, that the predicted shape, size and depth of the pores are in very good agreement with those found by either X-CT or optical and 3D digital microscopic images.
Sankhya Mohanty
added 3 research items
The microstructure of parts produced by sective laser melting of Ti-6Al-4V is typically martensite in elongated prior  grains, which leads to anisotropic mechanical properties. A heat treatment can reduce this anisotropy by making these grains more equiaxed. In this work, simulations are performed wherein the evolution of the microstructure during a heat treatment is modelled using a cellular automata method. The results obtained from this simulation are compared to experimentally obtained micrographs. The simulated microstructure shows a similar evolution of the prior  grains from columnar to equiaxed, although the average diameter of the grains is slightly smaller in the simulations.
In this paper, a multi-physics numerical model for multi-track-multi-layer laser powder bed fusion (L-PBF) process is developed and used for analysing the formation and evolution of porosities caused by lack of fusion and improper melting. The simulations are divided into two categories: first and foremost, a multi-physics thermo-fluid model in meso-scale, and second, a mechanical model based on the concept of a unit cell. The thermo-fluid model is used to track and observe the formation of the porosities, and considers phenomena such as multi-phase flow, melting/solidification, radiation heat transfer, capillary and thermo-capillary (Marangoni effect) forces, recoil pressure, geometry dependant absorptivity, and finally evaporation and evaporative cooling. The results for the investigated process parameters indicate that the porosities are mainly formed due to improper fusion of the particles. The probability of presence of pores is also observed to be higher in the first layers. Moreover, the lack of fusion zones are seen to become smaller in the subsequent layers, largely due to better fluid flow and higher temperatures in those layers. Based on the porosity levels determined from the thermo-fluid model, a unit cell mechanical model with an equivalent amount of porosity has been made and subsequently subjected to loading for analysing the part's mechanical behaviour. The unit cell results show that an increase in the porosity can highly affect and deteriorate the part's elastic modulus and its yield strength, as well. The combination of the thermo-fluid and the mechanical unit cell model establishes a direct link between process parameters and mechanical properties for L-PBF. INTRODUCION Laser powder bed fusion (L-PBF) method, is categorized as a metal additive manufacturing process [1], where the metallic parts are produced in a layer-wise manner. A simple view of a typical L-PBF machine is shown in Fig. 1. In this process, first a layer of fine spherical metallic particles, whose diameters typically span from approximately 10 µm to 60 µm [2], is distributed on a base plate (which in turn is attached to a build platform) by means of a controllable coating mechanism. Then, the laser starts scanning predefined locations based on the data provided in the CAD files [3]. While the laser scans these zones, the fine metallic particles will get coalesced together, either by being sintered or fully-molten, depending on
In this paper, a transient 3-dimensional thermal model for the selective laser melting process, based on the finite volume method, has been developed, which takes into account the phase change and powder to bulk material transition. A parametric study has been performed for the temperature field as well as the melt pool dimensions, and the results show the impact on melt pool size. Also, in this paper, a straightforward metallurgical model has been coupled to a thermal model, which uses the temperature gradient and the cooling rate on the melt pool borders at the onset of solidification to determine whether the grains have columnar or equiaxed morphology. Furthermore, the effect of process parameters on the size of grains and subsequently the yield stress has been studied via empirical equations. The results show that lower values of speed along with higher values of laser power (higher laser energy density) will cause lower cooling rates that prompt the formation of bigger grain. This would consequently give rise to lower tensile strength, as compared to lower laser energy density where smaller grains are formed due to higher cooling rates. SLM-Thermal model-Finite volume method-grain morphlogy-parametric study
Sankhya Mohanty
added 8 research items
Selective laser melting is yet to become a standardized industrial manufacturing technique. The process continues to suffer from defects such as distortions, residual stresses, localized deformations and warpage caused primarily due to the localized heating, rapid cooling and high temperature gradients that occur during the process. While process monitoring and control of selective laser melting is an active area of research, establishing the reliability and robustness of the process still remains a challenge. In this paper, a methodology for generating reliable, optimized scanning paths and process parameters for selective laser melting of a standard sample is introduced. The processing of the sample is simulated by sequentially coupling a calibrated 3D pseudo-analytical thermal model with a 3D finite element mechanical model. The optimized processing parameters are subjected to a Monte Carlo method based uncertainty and reliability analysis. The reliability of the scanning paths are established using cumulative probability distribution functions for process output criteria such as sample density, thermal homogeneity, etc. A customized genetic algorithm is used along with the simulation model to generate optimized cellular scanning strategies and processing parameters, with an objective of reducing thermal asymmetries and mechanical deformations. The optimized scanning strategies are used for selective laser melting of the standard samples, and experimental and numerical results are compared.
Residual stresses and deformations continue to remain one of the primary challenges towards expanding the scope of selective laser melting as an industrial scale manufacturing process. While process monitoring and feedback-based process control of the process has shown significant potential, there is still dearth of techniques to tackle the issue. Numerical modelling of selective laser melting process has thus been an active area of research in the last few years. However, large computational resource requirements have slowed the usage of these models for optimizing the process. In this paper, a calibrated, fast, multiscale thermal model coupled with a 3D finite element mechanical model is used to simulate residual stress formation and deformations during selective laser melting. The resulting reduction in thermal model computation time allows evolutionary algorithm-based optimization of the process. A multilevel optimization strategy is adopted using a customized genetic algorithm developed for optimizing cellular scanning strategy for selective laser melting, with an objective of reducing residual stresses and deformations. The resulting thermo-mechanically optimized cellular scanning strategies are compared with standard scanning strategies and have been used to manufacture standard samples.
Over the last decade, several studies have attempted to develop thermal models for analyzing the selective laser melting process with a vision to predict thermal stresses, microstructures and resulting mechanical properties of manufactured products. While a holistic model addressing all involved phenomena is yet to emerge, the existing partial models have already become computationally heavy. This is observed to go hand-in-hand with a trend across literature for the usage of finite element (FE) formulations for developing implicit 3D models. However, the 3D implicit FE models, though able to accurately simulate the process, are constrained by either the size or scale of the model domain. A second challenging aspect involves the inclusion of non-linear material behavior into the 3D implicit FE models. An alternating direction implicit (ADI) method based on a finite volume (FV) formulation is proposed for modeling single-layer and few-layers selective laser melting processes. The ADI technique is implemented and applied for two cases involving constant material properties and non-linear material behavior. The ADI FV method consume less time while having comparable accuracy with respect to 3D implicit FE models. Drawing on the comparative results, appropriate models are recommended for different scenarios and modeling domains.