Laser Powder Bed Fusion Machine Research Articles

Defect detection in additively manufactured AlSi10Mg and Ti6Al4V samples using laser ultrasonics and phase shift migration

Laser ultrasonics (LU) is a non-contact and non-destructive method with a high data acquisition rate, making it a promising candidate for in-situ monitoring of defects in different additive manufacturing (AM) processes, including laser powder bed fusion (LPBF) and directed energy deposition, as well as final part inspection. In order to see the effect of various artificial defect types on an LU sub-surface reconstruction, AlSi10Mg samples with side through-holes, as well as Ti6Al4V samples with bottom blind holes and trapped powder were printed using LPBF, and then ultrasound B-scans of the samples were obtained using an LU system. The resulting scan data was processed using a custom frequency domain phase shift migration (PSM) algorithm, to reconstruct the defects and their locations. Novel ways of pre-processing the B-scan, used as an input to PSM, and taking advantage of its frequency representation, are demonstrated. Newton’s method was used to find a stationary phase approximation, used to account in the frequency domain for the fixed offset emitter-receiver arrangement within the PSM calculation. The Newton’s method calculation time was reduced by 33%, by using an approximation of the phase function to find an initial guess. The smallest defects that were detected using this method were in the size range between 200 to 300μm for the bottom hole defects, using an 8 ns laser pulse duration. The effect of the laser on the surface of a part being built, and the challenges and further work needed to integrate LU in a LPBF machine for in-situ inspection are discussed.

Impacts of Superalloys on the Surface Quality of Additively Manufactured Channels

Abstract Gas turbines feature many components that require superalloys capable of handling extreme thermal environments. Increasing the selection of materials available for these components is important to their use in these extremely high-temperature environments. This study investigated two recently developed materials intended to be used for additive manufacturing (AM), with one superalloy based on cobalt and the other on nickel. Sets of four test coupons were built using the materials, in addition to the commonly used Inconel-718, on multiple laser powder bed fusion machines. Several build conditions were varied between coupon sets, including coupon orientation, contour settings, and upskin and downskin treatment. Each set of test coupons featured four unique cooling designs to explore how different cooling technologies would be impacted by the variations in build conditions. After being built, coupons were computed tomography (CT) scanned to determine accuracy to design intent and quantify the surface roughness. The CT scans indicated that horizontally built test coupons had a significantly higher deviation from design intent and higher surface roughness than those built vertically. Results also indicated that the cobalt-based alloy consistently had a smoother surface quality with lower surface roughness compared to the nickel-based alloy. After geometric characterization, the cooling performance of the test coupons was measured experimentally. Pressure losses were found to correlate with increases in surface roughness; however, in some cases, the convective heat transfer did not increase proportionally to the pressure loss as a result of surface features significantly blocking the flow without proportionally increasing convective heat transfer.

Computational analysis and experiments of spatter transport in a laser powder bed fusion machine

This work focuses on how spatter particles are transported within a laser powder bed fusion (L-PBF) machine. The machine’s gas flow rate and salient flow features are studied with a computational fluid dynamics (CFD) model and are validated with experimental measurements of the flow near the build plate. The CFD model is also paired with a discrete phase model (DPM) to show how a spatter particle’s diameter, speed, ejection angle, material, and ejection location each affect its trajectory. The spatter model results are also validated by experiments wherein hot spatter particles are identified with an infrared camera. Overall, this work brings focus to several spatter-mitigation strategies including increasing gas flow rate, controlling spatter production through laser settings, and changing part placement. Throughout the infrared experiment’s single build cycle, over 14 million spatter particles were detected, contaminating both the parts and the powder bed. Both the spatter model and experiment suggest that spatter particles travel primarily in the downstream direction. This suggests that placing parts next to one another instead of downstream from one another could be a strategy to prevent spatter particles from traveling between parts. A low-speed zone is also discovered beneath the lower nozzle and is predicted to negatively alter the removal of spatter from that region of the build area.

Measurement of focal plane error in laser powder bed fusion machines

Amongst the many sub-systems that make up laser powder bed fusion (PBF-LB) machines, the optomechanical sub-system stands out due to its potential for off-nominal performance but incommensurate level of study on performance evaluation. Nominally, the optomechanical system focuses the laser onto a planar field which is at a controlled position and orientation relative to the powder bed. Deviations from this assumed condition, sometimes referred to as defocus or focus offset, have the potential to significantly impact the manufacturing process by influencing the energy intensity at the process zone. Herein, a novel, high-throughput, low-cost, artifact-based methodology to measure focus offset is detailed. In a single continuous build process, tracks at varying offsets from the build plane were created by ablating the coating on discrete coupons located throughout the build area. By examining these track widths, the focus offset was determined at a relatively fine spatial resolution over the build space, down to 25 mm intervals along the x and y directions, thus ascertaining the discrepancy between the laser focal plane and the build plane, i.e., focal plane error. Results were found to agree with reference measurements to within 0.27 mm over the entire build space and defocus levels ranging from approximately -1.6 to 1.7 mm were discovered. Field sag and optomechanical misalignment were the major casual factors. It is concluded that similar or more severe levels of defocus may be present in the typical PBF-LB machine, which may impart considerable impacts to the overall PBF-LB process.

Detectability by X-ray micro computed tomography of fatigue initiating void defects in laser powder-bed additively manufactured Ti-6Al-4V coupons

Non-destructive inspection is important for the quality assurance of additively manufactured components. In this study, X-ray micro Computed Tomography (µCT) was assessed for its capabilities and limitations to detect fatigue-initiation porosities in Ti-6Al-4V additively manufactured coupons. Cylindrical coupons were built using laser powder-bed fusion (L-PBF) from three different vendors and four different L-PBF machines that utilized their default process parameters. Using OEM prescribed default process parameters, there was significant variability in the defect distribution between machine to machine and also coupon to coupon that was on the same build plate, primarily due the difference in the internal quality assurance procedures and scan strategies adopted by each vendor. The probability of detection for conventional µCT (cubic voxel size 17.77 µm) was investigated by comparing with what was detected using a Synchrotron Radiation Micro Computed Tomography (SRµCT) at cubic voxel size 5.91 µm. It was found that µCT’s detectability relative to SRµCT was approximately 90% for defect diameters of the circumscribed sphere of 230 µm and above and 100% for diameters of 340 µm and above (12–14 times the voxel size of the µCT scan). The type of defect was a key factor to the detectability of large sized defects (>200 µm in diameter) due to the flatness and elongated shape factors. Fatigue results showed the critical defect √Area at the surface was approximately 100 µm at 500 MPa stress level, where significant scatter in fatigue life was observed. Post-fatigue test fractography identified different types of fatigue initiating defects, of which a ‘flat’ lack-of-fusion type defect was undetectable by either µCT or SRµCT. This type of defect was extremely flat and occupied very little spatial resolution through the build direction which limited the detection by automated threshold-based defect detection algorithms.

Build parameter influence on strut thickness and mechanical performance in additively manufactured titanium lattice structures

Additively manufactured lattices have been adopted in applications ranging from medical implants to aerospace components. For solid AM components, the effect of build parameters has been well studied but comparably little attention has been paid to the influence of build parameters on lattice performance. For this project, the main aim was to evaluate static compressive mechanical performance of regular and stochastic lattices as a function of build parameters. The second aim was to compare strut dimensions of the metal lattice structures as build parameters were changed. Both regular and stochastic lattices were fabricated with a designed strut diameter of either 200 μm or 300 μm on a laser powder bed fusion machine. A range of laser power (140–180 W), scan speed (1700–2100 mm/s), and laser offset (0–45 μm) were used in fabricating each lattice. Compression tests were performed following the ISO 13314 (2011) standard to measure modulus, yield strength, and ultimate compressive strength values. Laser power adjustments produced the most significant effect on lattice performance. A change of 50 W resulted in roughly a 2X increase in maximum load and modulus for both regular and stochastic lattice structures. Regular lattice structures had a higher mechanical response during the mechanical evaluation. Internal strut diameters varied between build parameters as well, with laser offset adjustments producing the most noticeable change in strut geometry between lattice samples. These findings suggest that build parameter optimization, in lieu of using OEM parameters developed for solid structures, is necessary to ensure the optimum mechanical performance of AM lattice structures.

Support Structures Optimisation for High-Quality Metal Additive Manufacturing with Laser Powder Bed Fusion: A Numerical Simulation Study.

This study focuses on Metal Additive Manufacturing (AM), an emerging method known for its ability to create lightweight components and intricate designs. However, Laser Powder Bed Fusion (LPBF), a prominent AM technique, faces a major challenge due to the development of high residual stress, resulting in flawed parts and printing failures. The study's goal was to assess the thermal behaviour of different support structures and optimised designs to reduce the support volume and residual stress while ensuring high-quality prints. To explore this, L-shaped specimens were printed using block-type support structures through an LPBF machine. This process was subsequently validated through numerical simulations, which were in alignment with experimental observations. In addition to block-type support structures, line, contour, and cone supports were examined numerically to identify the optimal solutions that minimise the support volume and residual stress while maintaining high-quality prints. The optimisation approach was based on the Design of Experiments (DOE) methodology and multi-objective optimisation. The findings revealed that block supports exhibited excellent thermal behaviour. High-density supports outperformed low-density alternatives in temperature distribution, while cone-type supports were more susceptible to warping. These insights provide valuable guidance for improving the metal AM and LPBF processes, enabling their broader use in industries like aerospace, medical, defence, and automotive.

Functionality and Mechanical Performance of Miniaturized Non-Assembly Pin-Joints Fabricated in Ti6Al4V by Laser Powder Bed Fusion.

In this work, additively manufactured pin-joint specimens are analyzed for their mechanical performance and functionality. The functionality of a pin-joint is its ability to freely rotate. The specimens were produced using laser powder bed fusion technology with the titanium alloy Ti6Al4V. The pin-joints were manufactured using previously optimized process parameters to successfully print miniaturized joints with an angle to the build plate. The focus of this work lies in the influence of joint clearance, and therefore all specimens were manufactured with a variety of clearance values, from 0 µm up to 150 µm, in 10 µm steps. The functionality and performance were analyzed using torsion testing and tensile testing. Furthermore, a metallographic section was conducted to visually inspect the clearances of the additively manufactured pin-joints with different joint clearance values. The results of the torsion and tensile tests complement each other and emphasize a correlation between the joint clearance and the maximal particle size of the powder utilized for manufacturing and the mechanical behavior and functionality of the pin-joints. Non-assembly multibody pin-joints with good functionality were obtained reliably using a joint clearance of 90 µm or higher. Our findings show how and with which properties miniaturized pin-joints that can be integrated into lattice structures can be successfully manufactured on standard laser powder bed fusion machines. The results also indicate the potential and limitations of further miniaturization.

Fracture Toughness of Ti6Al4V/Cp-Ti Multi-Material Produced via Selective Laser Melting

Multi-materials can locally enhance the properties of products to improve their performance. In some cases, it might be necessary to improve the fracture toughness properties locally. This work is devoted to investigating the fracture toughness of multi-material Ti6Al4V/Cp-Ti specimens produced via laser powder bed fusion (L-PBF). The powder feeding and distributing system of the L-PBF machine was modified for programmable dual-powder feed capability. The multi-material Ti6Al4V/Cp-Ti samples analyzed in this work are layered materials, where the Ti6Al4V alloy serves as the base material and Cp-Ti is present as separate layers. Samples of this type rely on the principle of crack inhibition, where fracture energy is dissipated in the more ductile Cp-Ti layers. Two variants of alternating ductile layers were studied. The microstructure of the materials and interfacial zone were analyzed using an optical microscope. Chemical composition was examined with a scanning electron microscope. The size of the interfacial zone in the multi-material averaged between 250 and 300 μm. A comparison of the tensile tests results with the literature data (of relatively pure Ti6Al4V alloy) reveals that there is a minor reduction in ultimate tensile strength and elongation. The obtained results confirm the possibility of locally increasing fracture toughness through the creation of a multi-material structure using L-PBF.

Intelligent Additive Manufacturing Architecture for Enhancing Uniformity of Surface Roughness and Mechanical Properties of Laser Powder Bed Fusion Components

In the Laser Powder Bed Fusion (L-PBF) process, 3D components with complex geometries are fabricated in a layer-by-layer fashion by using a controlled laser beam to selectively melt particular regions of the metal powder bed. However, due to the stochastic nature of the L-PBF process, the top surface roughness of each solidified layer tends to be different even when the optimal processing conditions for the different positions on the build plate are employed. As a result, the mechanical properties of the built components frequently vary from one component to the next. Accordingly, this study proposes an Intelligent Additive Manufacturing Architecture (IAMA) for controlling the surface roughness of each build layer through an appropriate adjustment of the laser re-melting parameters. The IAMA architecture comprises five modules, namely In-Situ Metrology (ISM), Ex-Situ Metrology (ESM), Automatic Virtual Metrology (AVM), Additive Manufacturing Simulation (AMS) and Intelligent Compensator (IC). The feasibility of the proposed architecture is demonstrated by comparing the top surface roughness of cubic and mechanical strengths of tensile test samples built using the proposed method with those built using a traditional L-PBF approach without surface roughness control. It is found that the samples fabricated using the IAMA approach have an average top surface roughness of 1.6 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu$</tex-math> </inline-formula> m and a standard deviation is 0.7 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu$</tex-math> </inline-formula> m. By contrast, the samples produced using the traditional L-PBF approach have an average surface roughness of 13.45 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu$</tex-math> </inline-formula> m and a standard deviation of 2.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu$</tex-math> </inline-formula> m. In addition, the specimens produced with the assistance of IAMA architecture have an average tensile strength of 1013 MPa with a standard deviation of 69.5 MPa, while those printed without surface roughness control have an average tensile strength of 903 MPa with a standard deviation of 101.4 MPa <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —As L-PBF produce part in a layer-by-layer manner, therefore, the roughness on the top surface of previous layer have a strong influence on the printing quality of current layer. The variations of surface roughness will lead to the fluctuation of mechanical properties of the fabricated components. Additionally, to the best of author’s knowledge, current commercial L-PBF machines can not actively control the surface roughness of samples during the process. The proposed IAMA in this work can predict and control the roughness on the top surface of each layer during L-PBF process. Therefore, the constructed architecture has strong potential for integrating into the commercial L-PBF machine for controlling the surface roughness on the top of the parts during the manufacturing process. As a result, the quality of the fabricated components is expected to be in consistent. Accordingly, L-PBF machine equipped with IAMA will have a strong potential in applying for mass production of the components in aerospace and automobile industries.

A Systematic Study on Layer-Level Multi-Material Fabrication of Parts via Laser-Powder Bed Fusion Process

In this work, a systematic study was conducted on the fabrication of multi-material components obtained employing Laser-Powder Bed Fusion (L-PBF) technology. The idea of making multi-material components is a winning capability of additive technologies because it allows for the fabrication of Functionally Graded Materials (FGMs) with the customization of parts according to different required properties. This study aims to determine the ability of an inexpensive system, adaptable to the L-PBF machines already on the market, with a powder-spreading technique based on coaters or rollers, to produce parts with continuously variable properties in each layer. Also, the correlation between certain selectable factors in the production design and the result obtained in terms of metallurgical and mechanical properties and chemical composition was investigated. The factors studied were the relative position of the different materials within the powder chamber and the geometry of the equipment designed to produce the cFGMs components. The performed tests involved the use of two materials, a nickel-based superalloy, and a stainless steel, having different chemical, physical, and mechanical properties to obtain gradual property variations in the manufactured samples. Based on the results of post-process characterization obtained via metallographic, chemical, and mechanical analysis, the relative positions of the materials and the geometry of the developed equipment have a limited effect on the sample’s manufactured properties. The characteristics of the FGM zone depend on the nature of the employed powders, and its extent coincides with that defined during the design of the divider.

Processability of A6061 Aluminum Alloy Using Laser Powder Bed Fusion by In Situ Synthesis of Grain Refiners

Despite the increasing interest in laser powder bed fusion (LPBF), only a few cast aluminum alloys are available for this process. This study focuses on improving the LPBF processability of the A6061 alloy, which is challenging due to its wide solidification range, the dendritic columnar grain growth, and consequent solidification cracking. To address these issues, in situ-synthesized grain refiners can be used to induce equiaxial grain growth and prevent crack formation. A6061 RAM2 powder—a mixture of A6061, Ti, and B4C—was characterized and processed using a low-power LPBF machine to create an in situ particle-reinforced metal matrix composite. Parameter optimization was performed to evaluate the effect of their variation on the printability of the alloy. Microstructural characterization of the samples revealed that the complete reaction and the synthesis of the ceramic reinforcement did not occur. However, TiAl3 was synthesized during the process and promoted a partial grain refinement, leading to the formation of equiaxial grains and preventing the formation of solidification cracks. The tensile tests carried out on the optimized samples exhibit superior mechanical properties compared to those of A6061 processed through LPBF.

Effect of Defect Variability in Aluminum Alloys on Ultrasonic Fatigue Performance across Additive Manufacturing Platforms

Abstract Optimization of process parameters is a critical step toward realization of component builds across multiple additive manufacturing (AM) platforms and broadening the deployment of AM processes. The main focus of the present work is the quantification of defect variability and fatigue performance of builds across multiple laser powder bed fusion (L-PBF) equipment. This study of variability is predicated upon the hypothesis that, given process variables yielding a similar percentage/type of porosity based on process maps for multiple AM platforms, the defect size distribution across them should be similar. Aluminum alloy (AlSi10Mg) specimens of cylindrical geometry built on three different L-PBF machines are characterized using computed tomography. The distributions of defect size are compared using Kolmogorov-Smirnov tests. Ultrasonic fatigue testing is used to quantify fatigue properties of the builds from the different L-PBF machines under fully reversed loading conditions. Finally, fatigue performance is correlated to the defect distribution in builds across the three platforms.

Porosity Prediction in Selective Laser Melting Combining Photodiode-based In-Process Monitoring and X-CT

Laser powder bed fusion (LPBF) currently faces challenges in consistency, complexity, and cost associated with quality ensurance. In-situ process monitoring is a potential approach to this problem. This work investigates the feasibility of using photodiodes for quality monitoring and correlates photodiode signals with X-ray computed tomography (X-CT) based on deep learning. A cube of Ti-6Al-4V grade 23 was produced with optimum energy density parameters. Porosity was analyzed using X-CT to help understand the size, shape, location, and the number of pores formed. The photodiode signals were recorded using the coaxial melt-pool monitoring system on an in-house developed LPBF machine. The photodiode signals collected during processing were segmented per layer accordingly using different window sizes. The classifiers were trained to predict the presence and location of porosities considering the inter-hatch effect. Moreover, different models were trained and compared, which will act as a baseline for further research. The results showed that using photodiode signals can yield a prediction sensitivity of 68% and an accuracy of 84% for pores with a cross-section larger than 100 μm2, with an area under the receiver operating characteristic curve (AUC) of 0.86. These findings suggest that photodiodes can be a promising approach to quality monitoring in LPBF with sub-layer spatial resolution.

Impacts of microsecond control in laser powder bed fusion processing

Lasers used in standard metal Laser Powder Bed Fusion (LPBF) machines are focused at the build plane with typical beam diameters less than 100 µm. This results in millions of individual laser beam scanning vectors when fabricating complex metal parts, and in most build scenarios, the laser turns on and off at the beginning and end of each vector, respectively. The standard configuration for LPBF machines includes a laser beam steering system with two mirrors attached to galvanometers, called the scanner. Most commercial lasers have response times for beam power control below 10 µs yet acceleration/deceleration times of commercial scanners are an order of magnitude slower (due to the dynamics of the mechanical system). A common strategy for allowing the scanner to “catch up” with the commanded location and speed is to employ “skywriting” with additional built-in time delays to allow for the scanner to maintain constant velocity while the laser is on. These delays along with skywriting are intended to increase resolution and reduce defects, although the actions and times are typically not accessible by the user. In fact, the millions of laser on/off events result in additional sources for defect generation to include lack of fusion voids, keyhole voids, surface roughness, and spatter. Ultimately, this results in differences in part performance within builds (build location) and between LPBF platforms. Recent work has identified methods to eliminate some forms of laser on/off defects by controlling the laser power ramp rate. To the authors knowledge, laser power ramping is not currently implemented on any commercial LPBF machine, and the use of laser power ramping has yet to be evaluated on realistic, complex parts. As a result, the current work implemented laser power ramping on a commercial LPBF machine using a complicated geometry with 1,309,338 laser on/off events (vectors) to analyze the holistic impact of fabricating real parts on defects, mechanical properties, and spatter. Ramping the laser power over 300µs eliminated the formation of back spatter, and a demonstration build of a complex qualification test artifact using IN718 reduced total spatter by nearly 5%. However, this laser power ramp change over 300µs (i.e., linearly varying laser power from 0 W to the desired power set point over 300µs) increased lack of fusion defects near part edges that reduced the tensile ductility from 17% to 12% without affecting tensile strength. The research highlighted the financial challenges imposed when scrutinizing microsecond level interactions, and as a result, a low-cost method to identify minimum ramp rates to prevent back spatter using a smart phone and an optical microscope was demonstrated. Microsecond control over the laser must be accompanied by microsecond control of the scanner and the impacts must be quantified holistically over a variety of response variables to broadly apply the developments to industry applications.1

Influence of gaseous environment on the properties of Inconel 625 L-PBF parts

The effect of gaseous atmosphere during Laser Powder Bed Fusion (L-PBF) was analysed on an Inconel 625 alloy. The bead dimensions, the surface finish, the porosity rate and the resulting microstructure were analysed for three different gases (Argon, Nitrogen and Helium) in an industrial L-PBF machine, using rather high energy density promoting keyhole welding regime. No clear effect of gas nature on energy coupling was shown when considering fusion beads on L-PBF parts. However, this work shows that gas, and especially helium mostly modifies surface finish, due to a modification of heat dissipation at the interface between the built part and the powder bed. This effect is clearly beneficial for vertical builds but is balanced by a possible and detrimental reduction of surface tensions for inclined and overhanging surfaces. The data presented here indicates a moderate benefit of He and N2 gases on porosity rates at high laser energy, but the as-built microstructures do not exhibit detectable differences, at the scale considered for the analyses (SEM + EBSD). Some physical aspects of the liquid/gas interface are discussed at the end of the paper to explain the observed results.

Predictive simulation of bulk metallic glass crystallization during laser powder bed fusion

Laser powder bed fusion (L-PBF) has been employed to fabricate bulk metallic glass (BMG) parts. However, traditional experimental trial-and-error methods to determine process parameters for specific materials and L-PBF machines are time-consuming and expensive. In this paper, a phenomenological crystallization model, namely the Nakamura model, is coupled with L-PBF process simulation. A convenient approach for the crystallization parameter determination and a two-step Euler method for the numerical implementation has been developed. Numerical simulations are performed using the material parameters of a Zr-based BMG Zr59.3Cu28.8Al10.4Nb1.5 (at.%, trade name: AMZ4). The numerical results are validated by comparing with experimental results from different perspectives. Based on the numerical findings, a comprehensive understanding of BMG crystallization behavior during L-PBF is gained. In the end, the crystallization model is implemented in our in-house developed software SAMPLE2D. SAMPLE2D simulation results are presented, whereby the L-PBF process window for fully amorphous AMZ4 parts is explored. Thereby, it is believed that the developed numerical software can be applied to aid process development for BMGs by taking the crystallization phenomenon into account.

Value Chain Comparison of Additively and Conventionally Manufactured Multi-Cavity Tool Steel Inserts: An Injection Molding Industrial Case Study for High-Volume Production

The development of injection molding tools is an expensive, time-consuming, and resource-intensive process offering little to no flexibility to adapt to variations in product design. Metal additive manufacturing can be used to produce these tools in a cost-effective way. Nevertheless, in an industrial context, effective methods are missing for the selection of the most suitable technology for the given tooling project. This paper presents a method to compare process chains based on additive and conventional subtractive technologies for the manufacturing of metal tooling for injection molding. The comparison is based on a technology focused-performance analysis (TFPA) through computer simulation performed using Tecnomatix Plant Simulation developed by Siemens Digital Industries Software combined with a customized cost–benefit economic analysis tool. The analysis of the technology comparison highlights potential bottlenecks for production, such as the printing phase and the heat treatment. It also gives a deeper understanding of the technology maturity level of conventional milling machines against laser powder bed fusion machines. The result is that the total costs for an insert made by AM and CM are indeed rather similar (the cost difference between the two tooling process chains is lower than 5%). The cost analysis reveals major costs drivers in the production of high-performance molding tools, such as the cutting tools employed for the milling steps and their changeover frequency. The industrial case of a 32-cavity mold insert for plastic injection molding is used to perform the study, develop the analysis, and validate the results.

Energy Density Effect on the Interface Zone in Parts Manufactured by Laser Powder Bed Fusion on Machined Bases

The hybrid manufacturing procedure of combining an initial machining process and a posterior laser powder bed fusion (LPBF) process opens a new range of possibilities for manufacturing complex parts, promising to reduce both costs and printing time. Hence, the first portion of the part might be manufactured by machining, which is used as the substrate for the LPBF. Different manufacturing processes produce a melting interface zone (MIZ) that can affect the mechanical properties of hybrid parts. This work investigates the properties of the MIZ in hybrid parts. The influence of the energy density of the LPBF process on the interface zone and the mechanical properties of the final hybrid part were assessed. The different tests showed high-quality interphase even with low energy density, with a melting depth of up to 0.3 mm. Tomography analysis showed no pores in the MIZ and the increase in pore number with the scanning speed, reducing the UTS of the hybrid samples from 8 to 42% in relation to machined Corrax®. Additionally, a test piece for injection molding was produced by this new hybrid manufacturing process. The results showed that the costs and manufacturing time were reduced by about 50%, showing a potential application of hybrid manufacturing in such applications. Besides, this work identifies a limitation of the hybrid manufacturing approach using LPBF machines which are not equipped with a system to identify the substrate coordinate system. The present study develops an operational method to identify the coordinate system in order to ease the referencing of the pre-machined substrate within the machine platform.

Geometry-Based Radiation Prediction of Laser Exposure Area for Laser Powder Bed Fusion Using Deep Learning

Laser powder bed fusion (LPBF) is a promising technique used to manufacture complex geometries in a layer-wised manner. Radiation during the LPBF process is influenced by the part geometry, e.g., the overhang angle and the wall thickness. Locally varying radiation can cause deformation of the product after manufacturing. Thus, the prediction of the geometry-caused radiation before the manufacturing can support the evaluation of the design printability to achieve first-time-right printing. In this paper, we present a framework to predict the geometry-based radiation information using a deep learning (DL) algorithm based on the part geometry from computer-aided design (CAD). The algorithm was trained using data from an LPBF-print job consisting of parts with varying overhang angles. Image data, which include the information of radiation, were captured with an optical tomography (OT) camera system that was installed on a LPBF machine used in a laboratory environment. For the DL algorithm, a U-Net based network with mean absolute error (MAE) loss was applied. The training input was binarized OT data representing the contour of the designed geometry. Complementary, the OT data were used as ground truth for the model training. For the application, the design contours of multiple layers were extracted from the CAD file. The result shows the applicability to predict the OT-like radiation by its contour, which has the possibility to show the anomaly due to the part geometry.