Editor’s Choice Articles

Precise electrochemical machining (PECM) is being used increasingly to produce turbine blades (high-pressure compressors) from difficult-to-machine materials such as Inconel. However, the challenges associated with PECM are particularly pronounced for filigree workpieces characterized by high aspect ratios and thin-walled geometries. The need for high-pressure flushing within the working gap to renew the electrolyte poses a dilemma because it induces unwanted deflection in these thin-walled structures. This problem is intensified by the mechanical oscillation of the tool applied to promote flushing efficiency. The superposition of mechanical tool oscillation and turbulent flushing, which exacerbate fluid–structure interaction, has been identified as the essential cause of workpiece deflection. The aim of this paper is to present an experimental setup coupled with numerical methods to better investigate the phenomenon of workpiece deflection during PECM. In the first part of this work, a novel tool system for investigating the phenomenon of workpiece deflection in PECM is presented. The tool system combines typical PECM tool–workpiece arrangements for double-sided machining and a unique electrolytic mask that provides optical access to the working gap, allowing in situ measurements. After validating the tool system by experimental tests, the workpiece deflection is investigated using high-speed imaging. In a next step, analytical studies of the flushing conditions during machining operations are carried out. These investigations are followed by a structural investigation of the workpiece to improve the understanding of the deflection behavior of the workpiece. In addition, the effect on the blade tip caused by the continuously decreasing moment of inertia of the blade due to their thinning during machining is analyzed. Full article

In the context of directed energy deposition (DED), the production of complex components necessitates precise control of all processing parameters while mitigating undesirable factors like heat accumulation. This research seeks to explore and validate with various materials the impact of a geometry-based analytical model for minimizing heat input on the characteristics and structure of the resultant DED components. Furthermore, it aims to compare this approach with other established methods employed to avoid heat accumulation during production. The geometry of the fabricated specimens was assessed using a linear laser scanner, cross-sections were analyzed through optical microscopy, and the effect on mechanical properties was determined via microhardness measurements. The specimens manufactured using the developed analytical model exhibited superior geometric precision with lower energy consumption without compromising mechanical properties. Full article

Directed energy deposition-laser beam/powder (DED-LB/Powder) is an additive manufacturing process that is gaining popularity in the manufacturing industry due to its numerous advantages, particularly in repairing operations. However, its application is often limited to case studies due to some critical issues that need to be addressed, such as the degree of internal porosity. This paper investigates the effect of the most relevant process parameters of the DED-LB/Powder process on the level and distribution of porosity. Results indicate that, among the process parameters examined, porosity is less affected by travel speed and more influenced by powder mass flow rate and laser power. Additionally, a three-dimensional finite element transient model was introduced, which was able to predict the development and location of lack-of-fusion pores along the building direction. Full article

Cooling–lubricating processes have a big impact on cutting force, tool wear, and the quality of the machined surface, especially for hard-to-machine superalloys, so the choice of the right cooling–lubricating method is of great importance. Nickel-based superalloys are among the most difficult materials to machine due to their high hot strength, work hardening, and extremely low thermal conductivity. Previous research has shown that flood cooling results in the least tool wear and cutting force among different cooling–lubricating methods. Thus, the effects of the flood oil concentration (3%; 6%; 9%; 12%; and 15%) on the above-mentioned factors were investigated during the slot milling of the GTD-111 nickel-based superalloy. The cutting force was measured during machining with a Kistler three-component dynamometer, and then after cutting the tool wear and the surface roughness on the bottom surface of the milled slots were measured with a confocal microscope and tactile roughness tester. The results show that at a 12% oil concentration, the tool load and tool wear are the lowest; even at an oil concentration of 15%, a slight increase is observed in both factors. Essentially, a higher oil concentration reduces friction between the tool and the workpiece contact surface, resulting in reduced tool wear and cutting force. Furthermore, due to less friction, the heat generation in the cutting zone is also reduced, resulting in a lower heat load on the tool, which increases tool life. It is interesting to note that the 6% oil concentration had the highest cutting force and tool wear, and strong vibration was heard during machining, which is also reflected in the force signal. The change in oil concentration did not effect the surface roughness. Full article

Strategies for obtaining deep slots in soft materials can vary significantly. Conventionally, the tool travels along the slot, removing material mainly with the side cutting edges. However, a “plunge milling” strategy is also possible, performing the cut vertically, taking advantage of the tip cutting edges that almost reach the center of the tool. Although both strategies are already commonly used, there is a clear gap in the literature in studies that compare tool wear, surface roughness, and productivity in each case. This paper describes an experimental study comparing the milling of deep slots in AA7050-T7451 aluminum alloy, coated with a novel DLCSiO500W3.5O₂ layer to minimize the aluminum adhesion to the tool, using conventional and plunge milling strategies. The main novelty of this paper is to present a broad study regarding different factors involved in machining operations and comparing two distinct strategies using a novel tool coating in the milling of aeronautical aluminum alloy. Tool wear is correlated with the vibrations of the tools in each situation, the cycle time is compared between the cases studied, and the surface roughness of the machined surfaces is analyzed. This study concludes that the cycle time of plunge milling can be about 20% less than that of conventional milling procedures, favoring economic sustainability and modifying the wear observed on the tools. Plunge milling can increase productivity, does not increase tool tip wear, and avoids damaging the side edges of the tool, which can eventually be used for final finishing operations. Therefore, it can be said that the plunge milling strategy improves economic and environmental sustainability as it uses all the cutting edges of the tools in a more balanced way, with less global wear. Full article

In this study, the welding thermal cycle, as well as the microstructural and mechanical properties of welded AA6061-T6 plates, were studied. The plates were prepared and bead-on-plate welded using gas metal arc welding (GMAW). Numerical simulations using SYSWELD^® were performed to obtain the thermal distribution in the welded plates. The numerical heat source was calibrated using the temperatures obtained from the experimental work and the geometry of the melting pool. The mechanical properties were obtained through microhardness tests and were correlated with the welding thermal cycle. Moreover, the mechanical behavior and local deformation in the heat-affected zone (HAZ) were investigated using micro-flat tensile (MFT) tests with digital image correlation (DIC). The mechanical properties of the subzones in the HAZ were then correlated with the welding thermal cycle and with the microstructure of the HAZ. It was observed that the welding thermal cycle produced microstructural variations across the HAZ, which significantly affected the mechanical behavior of the HAZ subzones. The results revealed that MFT tests with the DIC technique are an excellent tool for studying the local mechanical behavior change in AA6061-T6 welded parts due to the welding heat. Full article

Knowing the tolerance interval capabilities (TICs) of a manufacturing process is of prime interest, especially if specifications link the manufacturer to a customer. These TICs can be determined using the machine performance concept of ISO 22514. However, few works have applied this to Additive Manufacturing printers, while testing most of the printing area as recommended takes a very long time (nearly 1 month is common). This paper, by proposing a novel part design called COMPAQT (Component for Machine Performances Assessment in Quick Time), aims at giving the same level of printing area coverage, while keeping the manufacturing time below 24 h. The method was successfully tested on a material extrusion printer. It allowed the determination of potential and real machine tolerance interval capabilities. Independently of the feature size, those aligned with the X axis achieved lower TICs than those aligned with the Y axis, while the Z axis exhibited the best performance. The measurements specific to one part exhibited a systematic error centered around 0 mm ± 0.050 mm, while those involving two parts reached up to 0.314 mm of deviation. COMPAQT can be used in two applications: evaluating printer tolerance interval capabilities and tracking its long-term performance by incorporating it into batches of other parts. Full article

Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess several trajectory strategies, such as contour, zigzag, raster, and even space-filling, to search for the best strategy according to the case. However, handling complex geometries by this means poses computational efficiency concerns. This research aimed to explore the potential of machine learning techniques as a solution to increase the computational efficiency of such algorithms. First, reinforcement learning (RL) concepts are introduced and compared with supervised machining learning concepts. The Multi-Armed Bandit (MAB) problem is explained and justified as a choice within the RL techniques. As a case study, a space-filling strategy was chosen to have this machining learning optimisation artifice in its algorithm for GMA-AM printing. Computational and experimental validations were conducted, demonstrating that adding MAB in the algorithm helped to achieve shorter trajectories, using fewer iterations than the original algorithm, potentially reducing printing time. These findings position the RL techniques, particularly MAB, as a promising machining learning solution to address setbacks in the space-filling strategy applied. Full article

This critical review provides a comprehensive analysis of various condition monitoring techniques pivotal in additive manufacturing (AM) processes. The reliability and quality of AM components are contingent upon the precise control of numerous parameters and the timely detection of potential defects, such as lamination, cracks, and porosity. This paper emphasizes the significance of in situ monitoring systems—optical, thermal, and acoustic—which continuously evaluate the integrity of the manufacturing process. Optical techniques employing high-speed cameras and laser scanners provide real-time, non-contact assessments of the AM process, facilitating the early detection of layer misalignment and surface anomalies. Simultaneously, thermal imaging techniques, such as infrared sensing, play a crucial role in monitoring complex thermal gradients, contributing to defect detection and process control. Acoustic monitoring methods augmented by advancements in audio analysis and machine learning offer cost-effective solutions for discerning the acoustic signatures of AM machinery amidst variable operational conditions. Finally, machine learning is considered an efficient technique for data processing and has shown great promise in feature extraction. Full article

The aim of this paper is to establish a valid procedure for better understanding all of the phenomena associated with the high-speed machining of glass fiber-reinforced plastic (GFRP) composites. Both rectangular and circular specimens were machined at high cutting speeds (up to 50 m/min) in order to understand what occurred for all values of fiber orientation angles during machining operations. An innovative testing methodology was proposed and studied to investigate the phenomenon of burr formation and thus understand how to avoid it during machining operations. To this end, the forces arising during the machining process and the roughness of the resulting surface were carefully studied and correlated with the cutting angle. Additionally, the cutting surface and chip morphology formed during cutting tests were examined using a high-speed camera. Close correlations were found between the variations in the cutting forces’ signals and the trends of the surface roughness and the morphology of the machined surface. Full article

In the last fifteen years, several groups have investigated metal injection moulding (MIM) of NdFeB powder to produce isotropic or anisotropic rare earth magnets of greater geometric complexity than that achieved by the conventional pressing and sintering approach. However, due to the powder’s high affinity for oxygen and carbon uptake, sufficient remanence and coercivity remains difficult. This article presents a novel approach to producing NdFeB magnets from recycled material using Powder Extrusion Moulding (PEM) in a continuous process. The process route uses powder obtained from recycling rare earth magnets through Hydrogen Processing of Magnetic Scrap (HPMS). This article presents the results of tailored powder processing, the production of mouldable feedstock based on a special binder system, and moulding with PEM to produce green and sintered parts. The magnetic properties and microstructures of debinded and sintered samples are presented and discussed, focusing on the influence of filling ratio and challenging processing conditions on interstitial content as well as density and magnetic properties. Full article

Various defects are produced during the laser powder bed fusion (L-PBF) process, which can affect the quality of the fabricated part. Previous studies have revealed that the defects formed are correlated with molten pool dimensions. Powder particles are thinly spread on a substrate during the L-PBF process; hence, powder packing properties should influence the molten pool dimensions. This study evaluated the influence of particle size on powder packing properties and molten pool dimensions obtained through numerical simulations. Using particles with different average diameters ($D_{av}$) of 24, 28, 32, 36, and 40 $\mathsf{\mu }$m, a series of discrete-element method (DEM) simulations were performed. The packing fraction obtained from DEM simulations became high as $D_{av}$ became small. Several particles piled up for small $D_{av}$, whereas particles spread with almost one-particle diameter thickness for large $D_{av}$. Moreover, the packing structure was inhomogeneous and sparse for large $D_{av}$. As a result of multiphysics computational fluid dynamics (CFD) simulations incorporating particles’ positions as initial solid metal volume, the molten pool width obtained was hardly dependent on the $D_{av}$ and was roughly equivalent to the laser spot size used in the simulations. In contrast, the molten pool depth decreased as $D_{av}$ decreased. Even if the powder bed thickness is the same, small particles can form a complex packing structure by piling up, resulting in a large specific surface area. This can lead to a complex laser reflection compared to the large particles coated with almost one-particle thickness. The complex reflection absorbs the heat generated by laser irradiation inside the powder bed formed on the substrate. As a result, the depth of the molten pool formed below the substrate is reduced for small particles. Full article

Minimum quantity lubrication (MQL) technologies possess great potential for improving the sustainability of manufacturing processes, which can reduce the absolute quantity of metalworking fluid (MWF) and also enable near-dry chips that are easier to recycle. During drilling in particular, the MWF is transported to the contact zone through internal cooling channels of the drilling tool. The MWF supply and its associated flow behaviour in the transfer from the outlet of the cooling channels to the contact zone have not been sufficiently investigated yet. Great potential is seen in the proper delivery of the MQL into the contact zone. This work aims to visualize and quantify the cooling lubricant supply into the cutting zone using the MQL technique. The visualization of the MQL application is made possible by high-speed shadowgraphic imaging. Detailed image processing is used to evaluate the resulting images. The developed evaluation routine allows for the assessment of the impact of the main process parameters such as the varying pressure of the aerosol generator and the cooling channel diameter. It is found that the oil leaves the cooling channels at the tip of the drill bit in the form of ligaments. An increase in pressure and cooling channel diameter leads to an increase in the frequency of oil ligament separation. Three main flow regimes are identified with different separation frequencies. Low inlet pressures result in intermittently dispersed droplets. The most upper pressure levels lead to an almost continuous dispersion of the oil. At the same time, the air and oil mass flow rates also increase. Full article

This work emphasizes an innovative approach utilizing 3D imaging technology based on synchrotron radiation to assess the microstructure of second-phase iron particles and the porous structure within 3D-printed PLA/magnetic iron composites at different printing angles. The study examines how these observations relate to the material’s ductility when processed using fused filament fabrication. In particular, this study examines the impact of one processing parameter, specifically the printing angle, on the microstructure and mechanical behaviour of a polylactic acid (PLA)–iron (PLI) composite designed for magnetic actuation. Fused filament fabrication is employed to produce PLI tensile specimens, with varied printing angles to create different layups. X-ray microtomography is utilized to analyse the microstructure, while tensile mechanical properties are evaluated for all composites, with findings discussed in relation to printing angle conditions. Scanning Electron Microscopy is used to examine the fractography of broken specimens. Results indicate that the printing angle significantly influences the tensile properties and mechanical anisotropy of 3D-printed PLI composites, with an optimal 45°/45° layup enhancing tensile performance. These findings suggest that 3D-printed PLI composites offer a cost-efficient means of producing bio-sourced, light-adaptive materials with intricate magnetic actuation capabilities. By quantifying the modulation of mechanical properties based on printing parameters that influence microstructural arrangement, the research sheds light on a novel aspect of composite material characterization. Full article

Context—Rapidly solidified aluminium alloy (RSA 443) is increasingly used in the manufacturing of optical mold inserts because of its fine nanostructure, relatively low cost, excellent thermal properties, and high hardness. However, RSA 443 is challenging for single-point diamond machining because the high silicon content mitigates against good surface finishes. Objectives—The objectives were to investigate multiple different ways to optimize the process parameters for optimal surface roughness on diamond-turned aluminium alloy RSA 443. The response surface equation was used as input to three different artificial intelligence tools, namely genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE), which were then compared. Results—The surface roughness machinability of RSA443 in single-point diamond turning was primarily determined by cutting speed, and secondly, cutting feed rate, with cutting depth being less important. The optimal conditions for the best surface finish Ra = 14.02 nm were found to be at the maximum rotational speed of 3000 rpm, cutting feed rate of 4.84 mm/min, and depth of cut of 14.52 µm with optimizing error of 3.2%. Regarding optimization techniques, the genetic algorithm performed best, then differential evolution, and finally particle swarm optimization. Originality—The study determines optimal diamond machining parameters for RSA 443, and identifies the superiority of GA above PSO and DE as optimization methods. The principles have the potential to be applied to other materials (e.g., in the RSA family) and machining processes (e.g., turning, milling). Full article

Copper-based materials have long been used for their outstanding thermal and electrical conductivities in various applications, such as heat exchangers, induction heat coils, cooling channels, radiators, and electronic connectors. The development of advanced copper alloys has broadened their utilization to include structural applications in harsh service conditions found in industries like oil and gas, marine, power plants, and water treatment, where good corrosion resistance and a combination of high strength, wear, and fatigue tolerance are critical. These advanced multi-component structures often have complex designs and intricate geometries, requiring extensive metallurgical processing routes and the joining of the individual components into a final structure. Additive manufacturing (AM) has revolutionized the way complex structures are designed and manufactured. It has reduced the processing steps, assemblies, and tooling while also eliminating the need for joining processes. However, the high thermal conductivity of copper and its high reflectivity to near-infrared radiation present challenges in the production of copper alloys using fusion-based AM processes, especially with Yb-fiber laser-based techniques. To overcome these difficulties, various solutions have been proposed, such as the use of high-power, low-wavelength laser sources, preheating the build chamber, employing low thermal conductivity building platforms, and adding alloying elements or composite particles to the feedstock material. This article systematically reviews different aspects of AM processing of common industrial copper alloys and composites, including copper-chrome, copper-nickel, tin-bronze, nickel-aluminum bronze, copper-carbon composites, copper-ceramic composites, and copper-metal composites. It focuses on the state-of-the-art AM techniques employed for processing different copper-based materials and the associated technological and metallurgical challenges, optimized processing variables, the impact of post-printing heat treatments, the resulting microstructural features, physical properties, mechanical performance, and corrosion response of the AM-fabricated parts. Where applicable, a comprehensive comparison of the results with those of their conventionally fabricated counterparts is provided. Full article

Laser beam welding as a reliable tool for high-precision joining of batteries or microelectronics is more and more the choice for achieving reproducible results in production processes. In addition to a high automation capability, the precise control of the energy deposition into the material plays an important role, especially when highly reflective materials, such as copper or aluminum, must be welded together. Alongside the use of highly brilliant fiber lasers in the near-infrared range with a focal diameter of a few tens of micrometers, diode lasers in the wavelength range of 445 nm are increasingly being used. Here, beam diameters of a few hundred micrometers can be achieved. With a wavelength of 445 nm, the absorptivity in copper can be increased by more than a factor of 10 compared to a near-infrared laser beam sources in solid state at room temperature. This paper presents the in situ X-ray observation of laser welding processes on CuSn6 with a laser beam source with a wavelength of 445 nm using synchrotron radiation at DESY Petra III Beamline P07 EH4 in Hamburg, Germany. For the experiments, the laser radiation was focused via two separate optics to focal diameters of 362 µm and 609 µm. To characterize the dynamics of the vapor capillaries depending on the different focal diameters d_F, the parameters were varied with respect to laser power P_L and feed rate v. For the investigations, a synchrotron beam of 2 × 2 mm² in size with a photon energy of 89 keV was used, and the material samples were analyzed by means of phase-contrast videography to show the boundaries between solid, liquid, and gaseous material phases. The results of this paper show the welding depths achieved and how the geometry of the vapor capillary behaves by changing the focal diameter, laser power and feed rate. Full article

In incremental sheet forming (ISF), the geometrical accuracy is still a challenge that is only solved for specific applications. The underlying mechanisms of geometrical defects in ISF are very complex and still not fully understood. Nevertheless, the process understanding is constantly evolving. Recent work has shown, for example, how bending moments resulting from residual stresses affect geometric accuracy. It has become clear that resulting bending moments with an axis parallel to the main tool path direction are dominant. Based on that, the current paper investigates the hypothesis that linear and parallel tool paths lead to an unfavourable accumulation of residual bending moments along a common axis, and whether this accumulation effect can be reduced by wave-shaped tool paths. Thus, the described research investigates the influence of novel path strategies on the residual bending moments and the resulting geometrical deviations. The path strategies are based on wave-shaped path lines, whereas the curvature is within the sheet plane. The investigations focussed on a rectangular sheet that is clamped at its shortest edges and a part geometry-sensitive to springback. Experimental and numerical investigations show a significantly positive influence of some investigated path strategies on the geometric deviation, compared to a conventional path strategy. Full article

Optical measurements are increasingly widely used as preferential techniques to evaluate dimensional and surface quantities in micro-products. However, uncertainty estimation is more critical on micro-products than macro, and it needs careful attention for evaluating the obtained quality, the requested tolerance, and the correct setting of experimental process settings. In this study, optical measurements characterized micro-injected products by linear and surface acquisition and considered all the sources contributing to uncertainties. The results show that the measure uncertainty could be underestimated if only the standard deviation on simple measurements is considered; this could cause a significant restriction of the estimated range covering the measured values. Furthermore, the findings confirm that the correct evaluation of the potential uncertainties contributes to accurately assessing the process behavior and improving product quality. Full article

The metal spinning process has been observed in recent major investigations carried out using finite element analysis. One interesting idea has proposed simulating a rotating disc for the simulation of the metal spinning process to reduce computational time. The development of this concept is presented in this paper, including the formal mathematical transformation from the inertial frame to the rotating reference frame, specific FEM configurations with mesh sizes based on a minimized aspect ratio, a mesh convergence study, and the application of a feed rate scale. Furthermore, in the context of the rotating reference frame, the flange geometry after wrinkle initiation is investigated, including the number of peaks and their amplitudes. Using this new approach, it was found that the number of peaks gradually increases from two to eight peaks while their amplitude decreases. In the case of severe wrinkles, the number of peaks stays at four while the amplitude increases dramatically. The intermediate path proves capable of increasing the number of peaks while maintaining a low amplitude. These results will make it possible to design new paths, facilitating the production of defect-free spun parts. Full article

Wire and arc additive manufacturing (WAAM) is a metal deposition technique with a fast rate and the possibility of a high volume of deposition. Because of its fast deposition and high heat input, the manufactured products have poor surface quality. This paper presents a study on the machining of Inconel 718 wall-shaped additive manufacturing (AM) products, a necessary step for the improvement of surface quality. Considering the possibility that the characteristics of the milling processes of AM products might differ from those of traditionally manufactured parts, in this research, two types of Inconel 718 were studied and compared: one was manufactured using WAAM, and the other was an Inconel 718 rolled bar (Aerospace Material Specifications 5662). Using the testing procedure, a conventional two-flute cutting tool was used to assess their machinability. For this process, multiple passes were performed at three different heights of the samples. Considering the peculiarities of the AM products, such as their uneven surfaces, dendritic microstructures, and anisotropy, the results were analyzed. After the machining operation, the effects on the products were also studied by analyzing their surface quality. This study found a higher stability in the cutting process for the AMS 5662 samples relative to the WAAM parts with less variability in the cutting forces overall, resulting in better surface quality. Full article

Incremental sheet forming (ISF) is an advanced flexible manufacturing process to produce complex 3D products. Unlike the conventional stamping process, ISF does not require any high cost dedicated dies. However, numerical computation for large-size ISF processes is time-consuming, and its accuracy for spring back due to unclamping tools after ISF cannot satisfy industrial demand. In this paper, an advanced numerical model considering complicated forming tool paths, trimming, and spring back was developed to efficiently simulate the multi-stage deformation phenomena of incremental sheet forming processes. Numerical modeling accuracy and efficiency are investigated considering the influence of tool path, material properties of the blank, mesh size, and boundary conditions. Through a series of case studies and comparisons with experimental results, it is observed that the numerical model with kinematics material properties and a moderate element size (5 mm) may reproduce the deformation characteristics of ISF with good accuracy and can obtain practical efficiency for a large-size ISF part. Full article

Biomass–fungi biocomposite materials are derived from sustainable sources and can biodegrade at the end of their service. They can be used to manufacture products that are traditionally made from petroleum-based plastics. There are potential applications for these products in the packaging, furniture, and construction industries. In the biomass–fungi biocomposite materials, the biomass particles (made from agricultural waste such as hemp hurd) act as the substrate, and a network of fungal hyphae grow through and bind the biomass particles together. Typically, molding-based methods are used to manufacture products using these biocomposite materials. Recently, the authors reported a novel extrusion-based 3D printing method using these biocomposite materials. This paper reports a follow-up investigation into the effects of mixing parameters (mixing time and mixing mode) on fungal growth in biomass–fungi mixtures prepared for 3D printing and the effects of printing parameters (printing speed and extrusion pressure) on fungal growth in printed samples. The fungal growth was quantified using the number of fungal colonies that grew from samples. The results show that, when mixing time increased from 15 to 120 s, there was a 52% increase in fungal growth. Changing from continuous to intermittent mixing mode resulted in an 11% increase in fungal growth. Compared to mixtures that were not subjected to printing, samples printed with a high printing speed and high extrusion pressure had a 14.6% reduction in fungal growth, while those with a low printing speed and low extrusion pressure resulted in a 16.5% reduction in fungal growth. Full article

Ti6Al4V alloy (Ti64) is a popular material used in the aerospace, medical, and automotive industries due to its excellent mechanical properties. Laser Powder Bed Fusion (LPBF) is a promising manufacturing technique that can produce complex and net-shaped components with comparable mechanical properties to those produced using conventional manufacturing techniques. However, during LPBF, the rapid cooling of the material can limit its ductility, making it difficult to achieve high levels of ductility while maintaining the required tensile strength for critical applications. To address this challenge, this study presents a novel approach to controlling the microstructure of Ti64 during LPBF by using a border design surrounding the main parts. It is hypothesized that the design induces in situ martensitic decomposition at different levels during the fabrication process, which can enhance the ductility of the material without compromising its tensile strength. To achieve this aim, a series of Ti64 samples were fabricated using LPBF with varying border designs, including those without borders and with gaps from 0.5 to 4 mm. The microstructure, composition, and mechanical properties of the Reference sample were compared with those of the samples fabricated with the surrounding border design. It was found that the latter had a more homogenized microstructure, a higher density, and improvements in both ductility and tensile strength. Moreover, it was discovered that the level of property improvement and martensitic transformation can be controlled by adjusting the gap space between the border and the main part, providing flexibility in the fabrication process. Overall, this study presents a promising approach for enhancing the mechanical properties of Ti64 produced via LPBF, making it more suitable for critical applications in various industries. Full article

Unique friction-based self-piercing riveting (F-SPR) was employed to join high-strength, low-ductility aluminum alloy 7055 for lightweight vehicle applications. This study aimed to maximize the joint strength of the AA7055 F-SPR joint while avoiding cracking issues due to low ductility at room temperature. A fully coupled Eulerian–Lagrangian (CEL) model was employed to predict the process temperature during F-SPR, and the temperature field was then mapped onto a 2D axisymmetric equivalent model for accelerated numerical analysis. The geometry, dimensions, and material strength of the rivet, as well as the depth of the die cavity and plunging depth, were investigated to enhance joint formation. Also, a static finite-element analysis model was developed to predict and analyze the stress distribution in the rivet under different mechanical testing loading conditions. Overall, the numerical model showed good agreement with the experiment results, such as joint formation and mechanical joint strength. With the aid of virtual fabrication through numerical modeling, the joint design iterations and process development time of F-SPR were greatly reduced regarding the goal of lightweight, high-strength aluminum joining. Full article

The electro-discharge (ED) drilling of precision boreholes in difficult-to-machine materials, particularly with respect to the cost-effectiveness of the overall process, is still a challenge. Flushing is one key factor for the precise machining of boreholes, especially with high aspect ratios. Therefore, the influence of internal and external flushing geometries for six types of brass tool electrodes with a diameter of 3 mm with and without a helical groove was analyzed experimentally and numerically. Using this helical external flushing channel, drilling experiments in X170CrVMo18-3-1 (Elmax Superclean) with an aspect ratio of five revealed a material removal rate (MRR) that was increased by 112% compared with a rod electrode, increased by 28% for a single-channel tool electrode and decreased by 8% for a multi-channel tool electrode. Signal analyses complemented these findings and highlighted correlations between classified discharge event types and the experimental target parameters. Amongst others, it was verified that the arcing frequency ratio drove the electrode wear rate and the beneficial frequency ratio correlated with the MRR and the surface roughness Ra. Sophisticated 3D computational fluid dynamics (CFD) models of the liquid phase were introduced and evaluated in great detail to demonstrate the validity and further elucidate the effect of the external flushing channel on the evacuation capability of debris and gas bubbles. The presented methods and models were found to be suitable for obtaining in-depth knowledge about the flushing conditions in the ED drilling working gap. Full article

High-strength steels (HSS) appear as a good alternative to common steels to reduce vehicle weight, thus reducing fuel consumption. Despite the excellent mechanical behavior towards its lower weight, its application in industry is still limited, as manufacturing such materials suffers from limitations, especially regarding formability. The literature shows springback to be the most common problem. Among the parameters that can be studied to minimize this problem, the temperature appears, according to the literature, to be one of the most influential parameters in minimizing springback. However, the consequence of the temperature increase on the forming limits of materials is not completely understood. This study proposes to determine the consequences of the use of the temperature rise technique in the forming limits of high-strength steels. Two different steels were studied (HSLA 350/440 and DP 350/600). To evaluate the formability, the Nakazima method was used (practical). Finite element models were made which describe the material as well as Nakazima experimental behavior. To predict the forming limit strains via the numerical method, the thickness gradient criterion was applied. The practical and computational results were compared to validate the finite element model. Four different temperature ranges were analyzed. In general, it was found that 400 °C has a negative impact on the forming limits of both steels. This negative effect was found to be due to the alloying elements, such as silicon and manganese, present in the alloy. These alloying elements take part in the increase and decrease in resistance coefficient at the elevated temperature. For HSLA 350/440 steel, the forming limit strain decreased with an increase in temperature up to 600 °C and then increased at 800 °C; whereas for DP 350/600 steel, the forming limit strain decreased till 400 °C and then increased for 600 °C and 800 °C. Another factor which might have contributed to the behavior of the DP steel is the interaction of hard martensite with soft ferrite phase. Full article

In recent years, Additive Manufacturing (AM) has emerged as a transformative technology, with the process of Powder Bed Fusion of Metals using a Laser Beam (PBF-LB/M) gaining substantial attention for its precision and versatility in fabricating metal components. A major challenge in PBF-LB/M is the failure of the component or the support structure during the production process. In order to locate a possible residual stress-induced failure prior to the fabrication of the component, a suitable failure criterion has to be identified and implemented in process simulation software. In the work leading to this paper, failure criteria based on the Rice-Tracey (RT) and Johnson-Cook (JC) fracture models were identified as potential models to reach this goal. The models were calibrated for the nickel-based superalloy Inconel 718. For the calibration process, a conventional experimental, a combined experimental and simulative, and an AM-adapted approach were applied and compared. The latter was devised to account for the particular phenomena that occur during PBF-LB/M. It was found that the JC model was able to capture the calibration data points more precisely than the RT model due to its higher number of calibration parameters. Only the JC model calibrated by the experimental and AM-adapted approach showed an increased equivalent plastic failure strain at high triaxialities, predicting a higher cracking resistance. The presented results can be integrated into a simulation tool with which the potential fracture location as well as the cracking susceptibility during the manufacturing process of PBF-LB/M parts can be predicted. Full article

This study examined the impact of vibration-assisted drilling (VAD) on hole quality and residual stress in Ti-6Al-4V ELI (Extra Low Interstitials) material. Ti-6Al-4V ELI possesses excellent mechanical properties but presents challenges in machining, including chip evacuation, burr formation, and elevated cutting temperatures. VAD, particularly low-frequency vibration-assisted drilling (LF-VAD), has been explored as a potential solution to address these issues. The research compares LF-VAD with conventional drilling (CD) under various cutting and cooling conditions. LF-VAD exhibits higher maximum thrust forces under specific conditions, which result in accelerated tool wear. However, it also demonstrates lower RMS (root mean square) forces compared to CD, offering better control over chip formation, reduced burr formation, and improved surface roughness within the hole. Furthermore, LF-VAD generates greater compressive residual stresses on the hole’s inner surface compared to CD, suggesting enhanced fatigue performance. These findings indicate that LF-VAD holds promise for improving the hole’s surface characteristics, fatigue life, and overall component durability in Ti-6Al-4V machining applications. Full article

To save computational time and physical memory in welding thermo-mechanical analysis, an accurate adaptive mesh refinement (AMR) method was proposed based on the feature of moving heat source during the welding. The locally refined mesh was generated automatically according to the position of the heat source to solve the displacement field. A background mesh, without forming a global matrix, was designed to maintain the accuracy of stress and strain after mesh coarsening. The solutions are always carried out on the refined computational mesh using a selective integration scheme. To evaluate the performance of the developed method, a fillet welding joint was first analyzed via validation of the accuracy of conventional FEM by experiment. Secondly, a larger fillet joint and its variations with a greater number of degrees of freedom were analyzed via conventional FEM and current AMR. The simulation results confirmed that the proposed method is accurate and efficient. An improvement in computational efficiency by 7 times was obtained, and memory saving is about 63% for large-scale models. Full article

This study uses machine learning methods to model different stages of the calcination process in cement, with the goal of improving knowledge of the generation of CO₂ during cement manufacturing. Calcination is necessary to determine the clinker quality, energy needs, and CO₂ emissions in a cement-producing facility. Due to the intricacy of the calcination process, it has historically been challenging to precisely anticipate the CO₂ produced. The purpose of this study is to determine a direct association between CO₂ generation from the manufacture of raw materials and the process factors. In this paper, six machine learning techniques are investigated to explore two output variables: (1) the apparent degree of oxidation, and (2) the apparent degree of calcination. CO₂ molecular composition (dry basis) sensitivity analysis uses over 6000 historical manufacturing health data points as input variables, and the results are used to train the algorithms. The Root Mean Squared Error (RMSE) of various regression models is examined, and the models are then run to ascertain which independent variables in cement manufacturing had the largest impact on the dependent variables. To establish which independent variable has the biggest impact on CO₂ emissions, the significance of the other factors is also assessed. Full article

Analyzing the cutting process characteristics opens up significant opportunities to improve various material machining processes. Numerical modeling is a well-established, powerful technique for determining various characteristics of cutting processes. The developed spatial finite element model of short hole drilling is used to determine the kinetic characteristics of the machining process, in particular, the components of cutting force and cutting power. To determine the component model parameters for the numerical model of drilling, the constitutive equation parameters, and the parameters of the contact interaction between the drill and the machined material on the example of AISI 1045 steel machining, the orthogonal cutting process was used. These parameters are determined using the inverse method. The DOE (Design of Experiment) sensitivity analysis was applied as a procedure for determining the component models parameters, which is realized by multiple simulations using the developed spatial FEM model of orthogonal cutting and the subsequent determination of generalized values of the required parameters by finding the intersection of the individual value sets of these parameters. The target values for the DOE analysis were experimentally determined kinetic characteristics of the orthogonal cutting process. The constitutive equation and contact interaction parameters were used to simulate the short hole drilling process. The comparison of experimentally determined and simulated values of the kinetic characteristics of the drilling process for a significant range of cutting speed and drill feed changes has established their satisfactory coincidence. The simulated value deviation from the corresponding measured characteristics in the whole range of cutting speed and drill feed variation did not exceed 23%. Full article

Cracks usually generate during the formation of beads composed of a WC-12mass%Co cemented carbide by the laser metal deposition (LMD). Measuring temperatures of the formed bead and substrate during the LMD process is important for realizing crack-free beads. In this study, temperatures of the substrate around the formed bead during the LMD process were measured using a thermoviewer. Temperatures of the formed beads during the LMD process were predicted by simulation based on the thermal conduction analysis using the experimentally measured temperatures of the substrate. The experimental results obtained during forming the WC-12mass%Co cemented carbide beads on JIS SKH51 (ISO HS-6-5-2) substrates showed that the maximal temperatures of the substrates at 0.2 mm away from the center of the formed beads ranged from 229 °C to 341 °C at laser powers ranging from 80 W to 160 W. The predicted maximal temperatures of the formed beads were in the range of 2433 °C to 4491 °C in the simulation using a laser absorption coefficient of 0.35 for the substrate. Validity of these simulation results was discussed based on the melting point of the substrate and microstructures of the formed WC-12mass%Co cemented carbide beads. Full article

The development of the additive manufacturing (AM) technology proffers challenging requirements for forming accuracy and efficiency. In this paper, a hybrid additive manufacturing technology combining fusion-based selective laser melting (SLM) and solid-state cold spraying (CS) was proposed in order to enable the fast production of near-net-shape metal parts. The idea is to fabricate a bulk deposit with a rough contour first via the “fast” CS process and then add fine structures and complex features through “slow” SLM. The experimental results show that it is feasible to deposit an SLM part onto a CS part with good interfacial bonding. However, the CS parts must be subject to heat treatment to improve their cohesion strength before being sending for SLM processing. Otherwise, the high tensile residual stress generated during the SLM process will cause fractures and cracks in the CS part. After heat treatment, pure copper deposited by CS undergoes grain growth and recrystallization, resulting in improved cohesive strength and the release of the residual stress in the CS parts. The tensile test on the SLM/CS interfacial region indicates that the bonding strength increased by 38% from 45 ± 7 MPa to 62 ± 1 MPa after the CS part is subject to heat treatment, and the SLM/CS interfacial bonding strength is higher than the CS parts. This study demonstrates that the proposed hybrid AM process is feasible and promising for manufacturing free-standing SLM-CS components. Full article

Fused filament fabrication (FFF), colloquially known as 3D-printing, has gradually expanded from the laboratory to the industrial and household realms due to its suitability for producing highly customized products with complex geometries. However, it is difficult to evaluate the mechanical performance of samples produced by this method of additive manufacturing (AM) due to the high number of combinations of printing parameters, which have been shown to significantly impact the final structural integrity of the part. This implies that using experimental data attained through destructive testing is not always viable. In this study, predictive models based on the rapid prediction of the required extrusion force and mechanical properties of printed parts are proposed, selecting a subset of the most representative printing parameters during the printing process as the domain of interest. Data obtained from the in-line sensor-equipped 3D printers were used to train several different predictive models. By comparing the coefficient of determination (R²) of the response surface method (RSM) and five different machine learning models, it is found that the support vector regressor (SVR) has the best performance in this data volume case. Ultimately, the ML resources developed in this work can potentially support the application of AM technology in the assessment of part structural integrity through simulation and can also be integrated into a control loop that can pause or even correct a failing print if the expected filament force-speed pairing is trailing outside a tolerance zone stemming from ML predictions. Full article

Within the rapidly growing market for fiber-reinforced plastics (FRPs), conventional production processes involving molds are not cost-efficient for prototype and small series production. Therefore, new flexible forming techniques are increasingly being researched, many of which have been inspired by incremental sheet metal forming (ISF). Due to the different deformation mechanisms of woven reinforcement fibers and metal sheets, ISF is not directly applicable to FRP. Instead, shear and bending of the fibers need to be realized. Therefore, a new dieless forming process for the production of FRP supported by metal wire mesh as an auxiliary material is proposed. Two standard tools, such as hemispherical punches, are used to locally bend a reversible layup of metal wire mesh and woven reinforcement fiber fabric enclosed in a vacuum bag. Therefore, the mesh aids in introducing shear into the material due to its ability to transmit compressive in-plane forces, and it ensures that the otherwise flexible fabric maintains the intended deformation until the part is cured or solidified. Basic experiments are conducted using thermoset prepreg, woven commingled yarn fabric, and thermoplastic organo sheets, proving the feasibility of the approach. Full article

Single-point incremental forming (SPIF) has emerged as a time-efficient approach that offers increased material formability compared to conventional sheet-metal forming techniques. However, the physical interaction between the forming tool and the sheet poses challenges, such as tool wear and formability limits. This study introduces a novel sheet-forming technique called contactless single-point incremental forming (CSPIF), which uses hot compressed air as a deformation tool, eliminating the requirement for physical interaction between the sheet and a rigid forming tool. In this study, a polycarbonate sheet was chosen as the case-study material and subjected to the developed CSPIF. The experiments were carried out at an air temperature of 160 °C, air pressure of 1 bar, a nozzle speed of 750 mm/min, and a step-down thickness of 0.75 mm. A Schlieren setup and a thermal camera were used to visualize the motion of the compressed hot air as it traveled from the nozzle to the sheet. The results showed that the CSPIF technique allowed for the precise shaping of the polycarbonate sheet with minimal springback. However, minor deviations from the designed profile were observed, primarily at the starting point of the nozzle, which can be attributed to the bending effects of the sample. In addition, the occurrence of sheet thinning and material buildup on the deformed workpiece was also observed. The average surface roughness (Ra) of the deformed workpiece was measured to be 0.2871 microns. Full article

Electromagnetic forming is applied to form metal sheet parts from both non-ferrous and ferrous materials. In this paper, the electromagnetic forming behavior of aluminum alloy, copper and steel sheets was investigated through experiments. The disk-shaped specimens were electromagnetically free bulged with increasing deformation energies and parts with different deformation depths were obtained. The deformation was done with and without clamping the movement of the specimens’ edges. The specimens were printed with a mesh of diametrical lines and concentric circles with a predetermined pitch. The mesh served to determine the displacements in the mesh nodes after the deformation of the specimens, with which the axial, radial and circumferential strains were then calculated. The experimental data obtained was subjected to statistical correlation and regression analyses, and the mathematical models for the three main strains in each material were established. The strains of AlMn0.5Mg0.5 and Cu-OF parts are maximum in the center and have a similar variation, while the FeP04 parts have the maximum strains in an intermediate zone between the center and the edge. Full article

Straining of sheet metal leads to surface roughness changes. In this study, foils of AISI 201 and AISI 304 stainless steel were strained in uniaxial tension to impose roughening of their surfaces. Thereafter, the corrosion resistance, electrical resistivity, magnetic field density, and lubricated friction of the resulting surfaces were evaluated. The effect of strain-rate on the surface roughening, and thereby on the friction against tools, corrosion resistance, and occurrence of deformation-induced martensite was investigated. The AISI 304 material showed higher roughening than AISI 201 at low strain-rate. Lubricated friction is clearly affected by the changes to the surface of the strained foils that occur. When simulating a micro-forming process, the effect of strain-induced changes should be included where possible to maintain a high fidelity of the simulation. Strain-rate, in the range tested in this work, had only a minor effect on corrosion properties; however, the martensite fraction was reduced for material elongated at higher strain-rates. Full article

Additive Manufacturing (AM) is gaining importance as an alternative and complementary technology to conventional manufacturing processes. Among AM technologies, the Atomic Diffusion Additive Manufacturing (ADAM) technology is a novel extrusion-based process involving metallic filaments. In this work, the widely used 17-4 PH stainless steel filament was selected to study the effect of different deposition strategies of ADAM technology on mechanical properties. The printed parts had mechanical properties comparable to those obtained by other more developed AM technologies. In the case of tensile and fatigue tests, obtained values were in general greatly affected by deposition strategy, achieving better results in horizontal built orientation specimens. Interestingly, the effect was also considered of machining post-process (turning), which in the case of the tensile test had no remarkable effect, while in fatigue tests it led to an improvement in fatigue life of two to four times in the tested range of stresses. Full article

Thermal conductivity (TC) is greatly influenced by the working temperature, microstructures, thermal processing (heat treatment) history and the composition of alloys. Due to computational costs and lengthy experimental procedures, obtaining the thermal conductivity for novel alloys, particularly parts made with additive manufacturing, is difficult and it is almost impossible to optimize the compositional space for an absolute targeted value of thermal conductivity. To address these difficulties, a machine learning method is explored to predict the TC of additive manufactured alloys. To accomplish this, an extensive thermal conductivity dataset for additively manufactured alloys was generated for several AM alloy families (nickel, copper, iron, cobalt-based) over various temperatures (300–1273 K). This unique dataset was used in training and validating machine learning models. Among the five different regression machine learning models trained with the dataset, extreme gradient boosting performs the best as compared with other models with an R² score of 0.99. Furthermore, the accuracy of this model was tested using Inconel 718 and GRCop-42 fabricated with laser powder bed fusion-based additive manufacture, which have never been observed by the extreme gradient boosting model, and a good match between the experimental results and machine learning prediction was observed. The average mean error in predicting the thermal conductivity of Inconel 718 and GRCop-42 at different temperatures was 3.9% and 2.08%, respectively. This paper demonstrates that the thermal conductivity of novel AM alloys could be predicted quickly based on the dataset and the ML model. Full article

This paper presents a systematic approach to developing big data analytics for manufacturing process-relevant decision-making activities from the perspective of smart manufacturing. The proposed analytics consist of five integrated system components: (1) Data Preparation System, (2) Data Exploration System, (3) Data Visualization System, (4) Data Analysis System, and (5) Knowledge Extraction System. The functional requirements of the integrated system components are elucidated. In addition, JAVA™- and spreadsheet-based systems are developed to realize the proposed system components. Finally, the efficacy of the analytics is demonstrated using a case study where the goal is to determine the optimal material removal conditions of a dry Electrical Discharge Machining operation. The analytics identified the variables (among voltage, current, pulse-off time, gas pressure, and rotational speed) that effectively maximize the material removal rate. It also identified the variables that do not contribute to the optimization process. The analytics also quantified the underlying uncertainty. In summary, the proposed approach results in transparent, big-data-inequality-free, and less resource-dependent data analytics, which is desirable for small and medium enterprises—the actual sites where machining is carried out. Full article

While Inconel 718 is a widely used engineering material in industrial fields such as the aerospace and automotive fields, the machined surface integrity has a significant effect on the performance of its components and parts. In this work, the laser-assisted micro-milling process of Inconel 718 is investigated using a combination of experiments and finite element simulations. Firstly, an experimental platform of laser-assisted milling is built, and a three-dimensional thermal–mechanical coupled finite element model of laser-assisted milling of Inconel 718 is then established. Secondly, laser-assisted milling experiments and finite element simulations are conducted to investigate the impact of laser assistance on cutting force, chip morphology, tool wear and surface topography of Inconel 718 under a milling process. The results indicate that laser-assisted milling results in a moderate reduction in cutting forces while enhancing surface integrity and chip continuity, as compared with ordinary milling. Thirdly, orthogonal experiments of laser-assisted milling of Inconel 718 are conducted to discover the optimal processing parameters, including spindle speed, feed per tooth, milling depth and laser parameters. Finally, single-factor experiments are conducted to investigate the effect of laser power on cutting force, chip morphology, tool wear, groove burr and surface roughness in the laser-assisted milling of Inconel 718. And, a minimal surface roughness Sa of 137 nm for Inconel 718 accompanied by minimal tool wear is experimentally obtained via laser-assisted milling. These findings highlight the effectiveness of applying laser assistance in enhancing the machinability of difficult-to-machine materials for achieving desirable machined surface integrity. Full article

Shearing high-strength steels often leads to a subpar cut quality and excessive stress on the tool components. To enhance the quality of the cut surface, intricate techniques like fine blanking are commonly employed. However, for applications with lower quality requirements, precision shear cutting offers an alternative solution. This research paper introduces a novel approach to directly superimpose radial stress on a workpiece during the precision shear cutting process and showcases for the first time how the application of direct stress superimposition can impact the cut surface by concurrently modifying the shear cutting edge and punch surface. A statistical experimental design is employed to investigate the interrelationships between the parameters and their effects. The results indicate that the overall cut quality, including cylindricity, clean-cut angle, rollover height, and tool stress, defined by punch force and retraction force, is influenced by the superimposed stress. Regarding the clean-cut zone, the statistical significance of direct radially superimposed stress was not observed, except when interacting with sheet thickness and clearance. Additionally, the sheet thickness and cutting gap emerged as significant parameters affecting the overall quality of the cut surface. Full article

Laser-based powder bed fusion is an additive manufacturing process in which a high-power laser melts a thin layer of metal powder layer by layer to yield a three-dimensional object. An inert gas must remove process byproducts formed during laser processing to ensure a stable and consistent process. The process byproducts include a plasma plume and spatter particles. An NC sensor gantry is installed inside a bespoke open-architecture laser-based powder bed fusion system to experimentally characterize the gas velocity throughout the processing area. The flow maps are compared to manufactured samples, where the relative density and melt pools are analyzed, seeking a potential correlation between local gas flow conditions and the components. The results show a correlation between low gas flow velocities and increased porosity, leading to lower part quality. Local flow conditions across the build plate also directly impact components, highlighting the importance of optimizing the gas flow subsystem. The experimental flow analysis method enables optimization of the gas flow inlet geometry, and the data may be used to calibrate the computational modeling of the process. Full article

Multi-material additive manufacturing (AM) attempts to utilize the full benefits of complex part production with a comprehensive and complementary material spectrum. In this context, this research article presents new processing strategies in the field of polymer- and metal-based multi-material AM. The investigation highlights the current progress in powder-based multi-material AM based on three successfully utilized technological approaches: additive and formative manufacturing of hybrid metal parts with locally adapted and tailored properties, material-efficient AM of multi-material polymer parts through electrophotography, and the implementation of UV-curable thermosets within the laser-based powder bed fusion of plastics. Owing to the complex requirements for the mechanical testing of multi-material parts with an emphasis on the transition area, this research targets an experimental shear testing set-up as a universal method for both metal- and polymer-based processes. The method was selected based on the common need of all technologies for the sufficient characterization of the bonding behavior between the individual materials. Full article

Driven by high energy prices, AHSS are still gaining importance in the automotive industry regarding electric vehicles and their battery range. Simulation-based design of forming processes can contribute to exploiting their potential for lightweight design. Fracture models are frequently used to predict the material’s failure and are often parametrised using different tensile tests with optical measurements. Hereby, the fracture is determined by a surface crack. However, for many steels, the fracture initiation already occurs inside the specimen prior to a crack on the surface. This leads to inaccuracies and more imprecise fracture models. Using a method that detects the fracture initiation within the specimen, such as acoustic emission analysis, has a high potential to improve the modelling accuracy. In the presented paper, tests for fracture characterisation with two AHSS were performed for a wide range of stress states and measured with a conventional optical as well as a new acoustical measurement system. The tests were analysed regarding the fracture initiation using both measurement systems. Numerical models of the tests were created, and the EMC fracture model was parametrised based on the two evaluation areas: a surface crack as usual and a fracture from the inside as a novelty. The two fracture models were used in a deep drawing simulation for analysis, comparison and validation with deep drawing experiments. It was shown that the evaluation area for the fracture initiation had a significant impact on the fracture model. Hence, the failure prediction of the EMC fracture model from the acoustic evaluation method showed a higher agreement in the numerical simulations with the experiments than the model from the optical evaluation. Full article

Fatigue properties of parts are of particular concern for safety-critical structures. It is well-known that discontinuities in shape or non-uniformities in materials are frequently a potential nucleus of fatigue failure. This is especially crucial for the Ti6Al4V alloy, which presents high susceptibility to the notch effect. This study investigates how post-processing treatments affect the mechanical performance of Ti6Al4V samples manufactured by laser powder bed fusion technology. All the fatigue samples were subjected to a HIP cycle and post-processed by machining and using combinations of alternative mechanical and electrochemical surface treatments. The relationship between surface properties such as roughness, topography and residual stresses with fatigue performance was assessed. Compressive residual stresses were introduced in all surface-treated samples, and after tribofinishing, roughness was reduced to 0.31 ± 0.10 µm, which was found to be the most critical factor. Fractures occurred on the surface as HIP removed critical internal defects. The irregularities found in the form of cavities or pits were stress concentrators that initiated cracks. It was concluded that machined surfaces presented a fatigue behavior comparable to wrought material, offering a fatigue limit superior to 450 MPa. Additionally, alternative surface treatments showed a fatigue behavior equivalent to the casting material. Full article

Dynamic machine tool simulation models can be used for various applications such as process simulations, design optimization, and condition monitoring. However, all these applications require that the model replicates the real system’s behavior as accurately as possible. Next to carefully building the model, the parameterization of the model, that is, determining the parameter values the model is based upon, is the most crucial step. This paper describes the application of both sensitivity-based and black-box parameter identification to a machine tool. It further provides a comparison between these two methods and the method of sequential assembly. It is shown that both methods can increase the mode shape conformity by more than 25% and significantly reduce damping deviations. However, sensitivity-based parameter identification is the most economical method, offering the chance to update a dynamic machine tool model within minutes. Full article

The innovative Green Ceramic Hybrid Machining (GCHM) process sequentially combines milling with a cutting tool (GCM, Green Ceramic Machining) and laser beam machining (GCLBM) of a ceramic material (black Y-TZP in this study) at the green stage mainly to increase productivity, avoid taper angle limitations of laser beam machining, and obtain micro-features. The study focuses on the reliability and the repeatability of the properties of sintered parts obtained by three manufacturing processes (GCM, GCLBM, GCHM) to assess the performance of hybridisation. It turns out that GCHM is a compromise of both milling and laser beam processes; it increases the repeatability of the surface quality and it slightly reduces (less than 7%) the flexural strength by comparison to milling for a similar reliability. The study also highlights that the surface quality of GCLBM processed parts relies on of the surface generated by the previous operation. Milling that surface at the previous step is therefore recommended, corresponding to the sequence adopted by GCHM. Full article