J. Manuf. Mater. Process., Volume 7, Issue 5 (October 2023) – 35 articles

The present research investigated the turning of AZ31B magnesium alloy in a dry environment using carbide tool inserts coated with tungsten carbonitride (TiCn) and thin alumina (Al₂O₃). A Box–Behnken design based on fifteen experiments showed a proportional increasing trend of flank wear with all three machining parameters, i.e., cutting speed, feed rate, and depth of cut. The most influential parameter is the cutting speed. A maximum flank wear of 299.34 µm due to excessive adhesion of work material on the tool face was observed at a high cutting speed. Machining at low speed resulted in a significant reduction in tool wear due to less chipping. The tool wear and chip morphology study confirmed the results. 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

The cross-roll piercing and elongation (CPE) is a forming process performed at high temperatures and high strain rates. The final product quality is strongly dependent on its microstructure. In this study, a finite element method (FEM) model was developed to better understand plastic deformation effects on microstructure during CPE and to analyze alternative thermo-mechanical processing routes. Specific models were used to simulate dynamic and meta-dynamic recrystallization (DRX and MDRX) for the processing of superaustenitic stainless steel (SASS). In addition, the CPE of SASS was investigated experimentally. The microstructure, mechanical properties, and chemical changes of the final product were assessed using optical microscopy, hardness testing, X-ray diffraction, and SEM-EDS. The results revealed higher temperatures and strain rates in the exterior area of the shell after piercing, and MDRX occurred in the whole thickness. However, an average grain size reduction of 13.9% occurred only in the shell middle and inner diameters. During elongation, the highest values of the strain rate and DRX were observed in the inner region, exhibiting a grain size reduction of 38%. Spread in terms of grain size and grain shape anisotropy was found to be less accentuated for tube samples as compared to the pierced shells. Full article

LDS-MIDs (laser direct structured mechatronic integrated devices) are 3D (three-dimensional) circuit carriers that are used in many applications with a focus on antennas. However, thanks to the rising frequencies of HF (high-frequency) systems in 5G and radar applications up to the mmWave (millimeter wave) region, the requirements regarding the geometrical accuracy and minimal wall thicknesses for proper signal propagation in mmWave circuits became more strict. Additionally, interest in combining those with 3D microstructures like trenches or bumps for optimizing transmission lines and subsequent mounting processes is rising. The change from IM (injection molding) to ICM (injection compression molding) could offer a solution for improving the 3D geometries of LDS-MIDs. To enhance the scientific insight into this process variant, this paper reports on the manufacturing of LDS-MIDs for mmWave applications. Measurements of the warpage, homogeneity of local wall thicknesses, and replication accuracy of different trenches and bumps for mounting purposes are presented. Additionally, the effect of a change in the manufacturing process from IM to ICM regarding the dielectric properties of the used thermoplastics is reported as well as the influence of ICM on the properties of LDS metallization—in particular the metallization roughness and adhesion strength. This paper is then concluded by reporting on the HF performance of CPWs (coplanar waveguides) on LDS-MIDs in comparison to an HF-PCB. Full article

Creating digital twins of industrial equipment requires the development of adequate virtual models, and the calculation of their parameters is a complex scientific and practical problem. To configure and digitally commission automated drives, two-mass electromechanical system models are used. A promising area in which to implement such models is the development of digital shadows, namely drive position observers. Connecting virtual models for online data exchange predetermines the tightening of requirements for their parameter calculation accuracy. Therefore, developing accessible techniques for calculating electromechanical system coordinates is an urgent problem. These parameters are most accurately defined by experiments. The contribution of this paper is the proposition of a method for defining the two-mass system model parameters using the oscillograms obtained in the operating and emergency modes. The method is developed for the horizontal stand drives of a plate mill 5000 and is supported by numerical examples. The technique is universal and comprises calculating the rotating mass inertia torques, elastic stiffness and oscillation damping coefficients, and the time constants of the motor air gap torque control loop. The obtained results have been applied to the development of the elastic torque observer of the rolling stand’s electromechanical system. A satisfactory coordinate recovery accuracy has been approved for both open and closed angular gaps in mechanical joints. Recommendations are given for the use of the method in developing process parameter control algorithms based on automated drive position observers. This contributes to the development of the theory and practice of building digital control systems and the implementation of the Industry 4.0 concept in industrial companies. 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

This review reports on the influencing parameters on the joining parts quality of tools and techniques applied for conducting process analysis and optimizing the friction stir welding process (FSW). The important FSW parameters affecting the joint quality are the rotational speed, tilt angle, traverse speed, axial force, and tool profile geometry. Data were collected corresponding to different processing materials and their process outcomes were analyzed using different experimental techniques. The optimization techniques were analyzed, highlighting their potential advantages and limitations. Process measurement techniques enable feedback collection during the process using sensors (force, torque, power, and temperature data) integrated with FSW machines. The use of signal processing coupled with artificial intelligence and machine learning algorithms produced better weld quality was discussed. 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

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

This paper shows how temperature influences impact energy for continuous fiber additively manufactured (AM) polymer matrix composites. AM composites were fabricated with a nylon-based matrix and four continuous reinforcements: fiberglass, high-temperature fiberglass (HSHT), Kevlar, and carbon. The tested temperatures ranged from −40 to 90 °C. The chosen printed configuration for the lattice structure and fiber volume was the configuration that was found to perform the best in the literature, with a volumetric fiber content of 24.2%. Impact tests showed that the best response was fiberglass, HSHT, Kevlar, and carbon, in that order. The impact resistance was lowered at temperatures below ambient temperatures and above 50 °C. Additionally, each material’s impact energy was adjusted to third-degree polynomials to model results, with correlation factors above 92%. Finally, the failure analysis showed the damage mechanisms of matrix cracking, delamination in the printing direction, fiber tearing, and fiber pulling as failure mechanisms. Full article

This study presents a comprehensive investigation and modeling of the ignition delay time ($t_d$) in wire-EDM (WEDM). The research focuses on the influence of gap distance, discharge energy, and piece height on the stochastic distributions of $t_d$, providing important insights into the complex properties of these distributions. Observations indicate that these parameters exert significant yet intricate influences on $t_d$, with a particular emphasis on the gap distance. A critical value was identified, around $8\mathsf{\mu }\mathrm{m}$ to $10\mathsf{\mu }\mathrm{m}$, that divides the stochastic behavior. To capture the binomial nature of $t_d$, a mixture probability model consisting of two Weibull distribution curves was developed and validated through extensive experimentation and a data analysis. The model demonstrated strong agreement with observed cumulative probability curves, indicating its accuracy and reliability in predicting $t_d$. Further, a sensitivity analysis revealed regions of fast change, emphasizing the challenges and importance of careful parameter selection in control of WEDM processes. The findings of this study contribute to a deeper understanding of WEDM processes and provide a modeling approach for predicting $t_d$. Future research directions include refining the model by incorporating additional input parameters, investigating the influence of other process variables on $t_d$. Full article

We recently introduced the possibility of performing operando small-angle X-ray scattering measurements using a novel industrially relevant injection moulding system for plastics. We show that useful time-resolving measurements can be performed with a time-cycle of 1 s and highlight the possible steps to reduce this to 0.5 s. We show how we can use the transmission measurements to provide a time marker when plastic first enters the mould cavity in the region probed by the incident X-ray beam. We show the opportunities provided by this experimental stage mounted on the NCD-SWEET beamline at ALBA to probe the reproducibility of the injection moulding system on different scales. The design of the equipment allowed for the development of the structure and the morphology to be evaluated in different parts of mould cavity, and we evaluated any differences in a rectangular mould cavity. We identified future prospects for this equipment in terms of novel mould heating and cooling systems and the opportunities for quantitatively evaluating radical approaches to injection moulding technology. Full article

Warm forming is widely used to enhance the formability of aluminum alloy sheets. In warm deep drawing, the process variables significantly affect frictional characteristics at the tool–blank interface. It has been a conventional approach to use a constant value of friction coefficients in the finite element (FE) simulations. However, this can occasionally result in suboptimal accuracy of the predictions. In the present work, strip drawing tests were carried out on AA5182 aluminum alloy sheets to investigate the effect of important process variables, namely, temperature, contact pressure, and drawing speed, on the friction coefficient in the warm forming temperature range (100–250 °C) under lubricated condition. The results obtained from the strip drawing tests were used for defining the friction conditions in the simulation of warm deep drawing of cylindrical cups incorporating the variation of the friction coefficient with contact pressure and speed at different temperatures. The Barlat89 yield criterion was used to define the effect of anisotropy in the material. The Voce hardening law and Cowper–Symonds model were used to incorporate the effect of strain hardening and strain rate, respectively, in the simulation. Drawability and peak force were compared with the predictions when a constant friction coefficient was assumed. Warm deep drawing experiments were conducted to validate the predicted drawability and load–displacement curves. It is clearly observed that the accuracy of prediction of the limiting drawing ratio and peak load through simulations is improved by incorporating the effect of pressure and speed on friction coefficient as it captures the local variations of friction during warm deep drawing precisely, rather than assuming a constant average friction coefficient at all the tool–blank contact areas. 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

Given the use of high-strength steels to achieve lightweight construction goals, conventional shear-cutting processes are reaching their limits. Therefore, so-called high-speed impact cutting (HSIC) is used to achieve the required cut surface qualities. A new machine concept consisting of linear motors and an impact mass is presented to investigate HSIC. It allows all relevant parameters to be flexibly adjusted and measured. The design and construction of the test bench, as well as the mechanism for coupling the impact mass, are described. To validate the theoretically determined process speeds, the cutting process was recorded with high-speed cameras, and HSIC with a mild deep-drawing steel sheet was performed. It was discovered that very good cutting edges could be produced, which showed a significantly lower hardening depth than slowly cut reference samples. In addition, HSIC was numerically modelled in LS-DYNA, and the calculated cutting edges were compared with the real ones. With the help of adaptive meshing, a very good agreement for the cutting edges could be achieved. The results show the great potential of using a linear motor in HSIC. 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

Due to the high specific surface area of titanium aluminide powders, significant and unavoidable surface oxidation takes place during processing. The resulting oxides disrupt the conventional powder metallurgical process route (pressing and sintering) by reducing the green strength and sintered properties. Oxide-free particle surfaces offer the potential to significantly increase particle bond strength and enable the processing of difficult-to-press material powders. In this work, the effect of milling titanium aluminide powder in a silane-doped atmosphere on the component properties after pressing and the subsequent sintering was investigated. Ball milling was used to break up the oxide layers and create bare metal surfaces on the particles. With the help of silane-doped inert gas, the oxygen partial pressure was greatly reduced during processing. It was investigated whether oxide-free surfaces could be produced and maintained by milling in silane-doped atmospheres. Furthermore, the resulting material properties after pressing and sintering were analysed using density measurements, hardness tests, EDX measurements, and micrographs. It was concluded that ball milling in a silane-doped atmosphere produces and maintains oxide-free particle surfaces. These oxide-free surfaces and smaller particle sizes improve the component properties after pressing and sintering. Full article

A nickel-based copper alloy known as Monel-400 is extensively applied in many industries including aerospace, marine engineering, and nuclear power generation, owing to its exceptional characteristics such as extreme tensile strength and toughness, excellent corrosion resistance, and the ability to retain shape even at extremely high temperatures. Traditional methods of drilling Monel-400 alloy are difficult due to quick tool wear and poor surface polishing, resulting in expensive machining costs. In this study, a technique called heat annealing was implemented to externally heat-treat the Monel-400 alloy material before the drilling process. Cutting force, surface roughness, and tool wear were used as the responses to investigate the effect of heat annealing and the drilling parameters on the machinability of Monel-400. The results revealed that the cutting force (Fz) and surface roughness (Ra and Rt) could be reduced by 33%, 31%, and 25%, respectively, after annealing at 700 °C compared to the results of the drilled Monel-400 at room temperature. It can be observed that the maximum improvement can reach 42% of Fz, 35% of Ra, and 59% of Rt while annealing Monel-400 at 1000 °C. A significant reduction was observed in the tool wear for machining the annealed material, which minimized the tooling and overall machining cost. Regarding the effects of the drilling process on the considered responses, the results revealed that the spindle speed has a greater effect on the cutting force, whereas the feed rate has the most significant effect on Ra. The significance of the drilling input parameters on the outputs is determined by analysis of the main effect plots and surface plots. Subsequently, the multi-objective genetic algorithm (MOGA) is used to identify the optimal parametric conditions for minimizing the cutting force and surface roughness of the drilled holes. The optimized values achieved via multi-objective optimization are the cutting force, Fz = 388–466 N, and the surface roughness, R_a = 0.17–0.19 μm and Rt = 3–3.5 μm, respectively. Full article

Consistent lightweight construction in the area of vehicle manufacturing requires the increased use of multi-material combinations. This, in turn, requires an adaptation of standard joining techniques. In multi-material combinations, the importance of integral cast components, in particular, is increasing and poses additional technical challenges for the industry. One approach to solve these challenges is adaptable joining elements manufactured by a thermomechanical forming process. By applying an incremental and thermomechanical joining process, it is possible to react immediately and adapt the joining process inline to reduce the number of different joining elements. In the investigation described in this publication, cast plates made of the cast aluminium alloy EN AC-AlSi9 serve as joining partners, which are processed by sand casting. The joining process of hypoeutectic AlSi alloys is challenging as their brittle character leads to cracks in the joint during conventional mechanical joining. To solve this, the frictional heat of the novel joining process applied can provide a finer microstructure in the hypoeutectic AlSi9 cast alloy. In detail, its Si is finer-grained, resulting in higher ductility of the joint. This study reveals the thermomechanical joining suitability of a hypoeutectic cast aluminium alloy in combination with adaptively manufactured auxiliary joining elements. Full article

The advent of additive manufacturing (AM) in Australian small and medium-sized enterprises offers the direct benefits of time-saving and labour cost-effectiveness for Australian manufacturing to be highly competitive in global markets. Australian local businesses can tailor their products to a diverse range of customers with a quicker lead time on the sophisticated design and development of products under good quality control in the whole advanced manufacturing process. This review outlines typical AM techniques used in Australian manufacturing, which consist of vat polymerisation (VP), environmentally friendly AM, and multi-material AM. In particular, a practical case study was also highlighted in the Australian jewellery industry to demonstrate how manufacturing style is integrated into their manufacturing processes for the purpose of reducing lead time and cost. Finally, major obstacles encountered in AM and future prospects were also addressed to be well positioned as a key player in the revolutionised Industry 4.0. Full article

The objective of this work is to improve the surface and subsurface properties of steel parts by means of a new grinding tool concept featuring nearly spherical grains in an elastic bonding system and to uncover the underlying mechanisms leading to the intended improvement of surface integrity. The resulting workpiece topography and subsurface properties, such as residual stresses, are evaluated to characterise and assess the potential of this novel tool concept. Micrographs and EBSD images are also analysed. The results show increased mechanical process loads and resulting favourable subsurface properties in terms of mechanically induced plastic deformation and compressive residual stresses, revealing the high potential of spherical grains in an elastic bonding system. Full article

A piezoelectric vibration sensing system (PVSS) was devised in this study and employed for the purpose of vibration sensing in machining. The system comprises three primary components, wherein the sensor is utilized for the collection and conversion of energy, subsequently transmitting it to the data acquisition card (DAC) via a low-noise cable. The crux of the entire system lies in the upper computer-based control application, which facilitates the transmission of instructions to the DAC for data acquisition and transmission. The integration of Wi-Fi data transfer capability between the DAC and the computer serves to eliminate the principal issue associated with employing the sensor as a voltage source. The sensitivity of the designed device was calibrated utilizing commercial accelerometers, while an aluminum workpiece was fabricated to conduct vibration and machining tests in order to verify the performance of the PVSS. The shaker excitation experiment yielded a peak voltage of 0.05 mV, thereby substantiating that the PVSS can more accurately discern the natural frequency of the workpiece below 5000 Hz compared to commercial accelerometers. The experiments verify that the devised PVSS can precisely measure vibrations during the milling process, and can be implemented for the purpose of detecting machining stability. Full article

Micro-EDM is an unconventional technology used to machine every type of electrically conductive material regardless of its mechanical properties. Material removal occurs through electrical discharges between the workpiece and the electrode immersed in a dielectric fluid. In drilling operations, the technology is able to realise microholes with excellent quality in terms of precision, quality surface, roundness, and taper to the detriment of the machining time, which is less than other technologies. Several efforts are being made to improve different features related to the process performance that are severely affected by both the operative conditions, such as the electrode material or the type of dielectric, and process parameters. The typical indexes used to characterise the performance are the machining time, the material removal rate, and the geometric indexes. These indexes are very effective and are easily measurable, but they do not give information about the evolution of the drilling process, which could be irregular due to the different phenomena occurring during machining. The aim of this paper is the development of a method able to elaborate the motion law of the electrode during the micro-EDM drilling operation. In order to do this, a single hole was manufactured in several steps, recording both the machining time and electrode wear for each step. In this way, the actual position of the electrode during the drilling can be measured without the use of a predictive model for electrode wear. It was tested to confirm that the multistep procedure did not introduce new phenomena, in contrast to the traditional drilling operation. This method was used to study the effects of the electrode diameter, the type of electrode, the length of the electrode out of the spindle, and the entity of the run-out on the process performance. The tests were executed on titanium alloy sheets using a tungsten carbide electrode and hydrocarbon oil as the dielectric. It was found that the descent of the electrode into the workpiece was not regular, but it depended on the level of debris concentration in the machining zone. The debris concentration was influenced by the type and diameter of the electrode, its length out of the spindle, and, to a lesser extent, the run-out. This method was found to be a useful method for an in-depth analysis of the micro-EDM drilling process, contributing to a better understanding of the physical aspects of the process. Full article

In recent years, the advancement of Industry 4.0 and smart manufacturing has made a large amount of industrial process data attainable with the use of sensors installed on machines. This paper proposes an experimental predictive maintenance framework for an industrial drying hopper so that it can detect any unusual event in the hopper, which reduces the risk of erroneous fault diagnosis in the manufacturing shop floor. The experimental framework uses Deep Learning (DL) algorithms to classify Multivariate Time-Series (MTS) data into two categories—failure or unusual events and regular events—thus formulating the problem as a binary classification. The raw data extracted from the sensors contained missing values, suffered from imbalancedness, and were not labeled. Therefore, necessary preprocessing is performed to make them usable for DL algorithms and the dataset is self-labeled after defining the two categories precisely. To tackle the imbalanced data issue, data balancing techniques like ensemble learning with undersampling and Synthetic Minority Oversampling Technique (SMOTE) are used. Moreover, along with DL algorithms like Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM), Machine Learning (ML) algorithms like Support Vector Machine (SVM) and K-nearest neighbor (KNN) have also been used to perform a comparative analysis on the results obtained from these algorithms. The result shows that CNN is arguably the best algorithm for classifying this dataset into two categories and outperforms other traditional approaches as well as deep learning algorithms. Full article

Conventional mechanical machining of composite is a challenging task, and thus, electric discharge machining (EDM) was used for the processing of the developed material. The processing of developed composite using different electrodes on EDM generates different surface characteristics. In the current work, the effect of tool material on the surface characteristics, along with other input parameters, is investigated as per the experimental design. The experimental design followed is an RSM-based Box–Behnken design, and the input parameters in the current research are tool material, current, voltage, pulse-off time, and pulse-on time. Three levels of each parameter are selected, and 46 experiments are conducted. The surface roughness (Ra) is investigated for each experimental setting. The machine learning approach is used for the prediction of surface integrity by different techniques, namely Xgboost, random forest, and decision tree. Out of all the techniques, the Xgboost technique shows maximum accuracy as compared to other techniques. The analysis of variance of the predicted solutions is investigated. The empirical model is developed using RSM and is further solved with the help of a teaching learning-based algorithm (TLBO). The SR value predicted after RSM and integrated approach of RSM-ML-TLBO are 2.51 and 2.47 µm corresponding to Ton: 45 µs; Toff: 73 µs; SV:8V; I: 10A; tool: brass and Ton: 47 µs; Toff: 76 µs; SV:8V; I: 10A; tool: brass, respectively. The surface integrity at the optimized setting reveals the presence of microcracks, globules, deposited lumps, and sub-surface formation due to different amounts of discharge energy. Full article

17-4PH Stainless Steel is a mechanically high-performing alloy that is widely used across chemical and mechanical processing industries. The alloy is conventionally fabricated by cast methods, but emerging additive manufacturing techniques are presently offering an economic, efficient, and environmentally friendly alternative. Bound Powder Extrusion (BPE) is a relatively new additive manufacturing technique that is used to fabricate three-dimensional, free-form components. Investigation into the mechanical properties and behavior of 17-4PH stainless steel fabricated by BPE is vital to understanding whether this technique proposes a competitive substitute to the cast alloy within industry. Published literature has investigated the as-fabricated mechanical properties, microstructure, porosity, and post-processing heat treatment of the BPE alloy, with limited comparison evident among the papers. This paper, therefore, aims to review published findings on the mechanical properties of 17-4PH stainless steel produced by additive manufacturing techniques, with a key focus on BPE. It is important to highlight that this review study focuses on the MetalX^TM 3D printer, manufactured by Markforged. This printer is among the widely utilized BPE 3D printers available in the market. The key results, together with the impact of post-heat treatments, were discussed and compared to provide a more comprehensive picture of the patterns that this alloy presents in terms of its microstructure and mechanical properties. This enables the manufacture of components relative to desired material performance, improving overall functionality. A comparison of yield strength, ultimate tensile strength (UTS), Young’s modulus, ductility, and hardness was made relative to microstructure, porosity, and density of published literature for the as-fabricated and post-heat-treated states, identifying areas for further research. Full article

The present study investigated the dissimilar metal combination of SUS303 stainless steel (SS) and pure copper C19210 by utilizing a fiber pulse laser to perform lap welding. The weld quality was evaluated through metallurgical and mechanical examinations, including scanning electron microscopy (SEM), optical microscopy (OM), energy dispersive spectroscopy (EDS), as well as tensile and shear tests. The cross-section of the weld joints was observed to examine the penetration inside the molten zone of the pulse laser welding. The incomplete weld penetration depth was confirmed by analyzing the molten pool geometry, which indicated that the penetration depth was proportional to the pulse heat energy input. EDS analysis demonstrated that interdiffusion and dissolution of Cu and SS occurred inside the weld pool, although only a limited amount of Cu was melted. Microhardness (MH) exploration revealed the hardness of the molten zone was lower than that of the heat-affected zone (HAZ) on the SS side, while the hardness on the Cu side, closer to the molten zone, was higher. The results of the tensile test indicated that the fracture occurred in the HAZ on the Cu side, displaying a dimpled fracture mode characteristic of ductile fracture. 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

Efficient roll bonding for the manufacturing of clad strips not only requires surface activation but also is improved by a surface patterning to reduce the initial contact area. This increases contact stresses and facilitates a joining without an increasing rolling force. Experiments to pattern surfaces with deformable inlays during cold rolling for a subsequent bonding in low-oxygen atmosphere were carried out using two types of rolling mills, two types of inlays and two types of assemblies. Digital twins of selected experiments were created by means of the FE simulation software QForm UK 10.2.4. The main set of rolling parameters, which play a significant role during formation of the pattern shape considering deformation of the patterning tool, were investigated. The pilot roll bonding of patterned components under vacuum conditions, provided using vacuum sealer bags, allowed for an experimental realization of this approach. The concept technological chain of roll bonding in a low-oxygen or oxygen-free environment comprises the following stages: roll patterning; surface activation and sealing of the strips in a vacuum bag; subsequent roll bonding of the prepared strips inside the protective bag. The difference between the shape of the pattern created and the initial shape of the mesh insert can be quantitatively described by the change of its angle. This difference reaches maximum values when smaller rolls are used with increased rolling reductions. This maximum value is limited by the springback of the deformed insert; the limit is reached more easily if the inlay is not positioned on the rolling plane. Full article