J. Manuf. Mater. Process., Volume 9, Issue 6 (June 2025) – 35 articles

Traditional manufacturing processes yield plastic containers in large batches, even for minimal production runs, resulting in elevated production costs. Three-dimensional printing has emerged as a viable alternative for very low production volumes, offering properties comparable to traditional methods at significantly reduced costs. To assess the tensile strength, specimens printed with identical geometric parameters to the 3D-printed containers were tested according to ASTM D638 standards, enabling the determination of the stress–strain curve behavior. A compression test was conducted on containers obtained from both manufacturing processes to establish their respective resistance and deformation characteristics. The results revealed a 67% difference in resistance, indicating greater rigidity in the 3D-printed container, and a higher deformation in the blow-molded container, reaching up to 4 mm in height without fracture. Similarly, impact resistance was analyzed using finite element analysis with Ls-Dyna software, showing deformation differences of 0.91% and stress differences of 2.15%. Therefore, 3D printing presents itself as a compelling alternative for the fabrication of plastic containers in small production runs. Full article

Metal injection molding (MIM) is a current technology used to produce products with complex shapes. Despite the accumulated worldwide experience in using this technology, manufacturers sometimes fail to launch new products of proper quality. Often, this is because defects can occur at the casting stage, the prevention of which is impossible through the use of standard design and technological solutions of molds design and the experimental selection of technological modes. This study aimed to analyze the causes of such defects in the green part and optimize the mold design to ensure defect-free casting, which was impossible for the manufacturer using standard solutions. The core method used in this study was simulation modeling of the casting process. A hypotheses were selected, and an analysis of the causes of defect occurrence in casting was conducted. Simulation modeling proved that defect occurrence was due to the formation of a free melt jet and subsequent air capture by this jet. Based on modeling, different gating and feeding system designs were analyzed, which made it possible to choose a variant that provided the uniform filling of gating cavities without forming jet flows and defects. The novelty of this study lies in its optimization of the mold design to prevent free melt jetting and similar defects in other MIM products by modeling feedstock molding processes. The presented results can help enrich the knowledge base of the mold design for MIM and ensure defect-free production. Full article

Accurate preform design in forging processes is critical for improving part quality, conserving material, reducing manufacturing costs, and eliminating secondary operations. This paper presents a finite element (FE) simulation-based methodology for preform design aimed at achieving flashless and near-flashless forging. The approach leverages material point backtracking within FE models to generate physics-informed preform geometries that capture complex material flow, die geometry interactions, and thermal gradients. An iterative scheme combining backtracking, surface reconstruction, and point-cloud solid modeling was developed and applied to several three-dimensional forging case studies, including a cross-joint and a three-lobe drive hub. The methodology demonstrated significant reductions in flash formation, particularly in parts that traditionally exhibit severe flash under conventional forging. Beyond supporting the development of new flashless forging sequences, the method also offers a framework for modifying preforms during production to minimize waste and for diagnosing preform defects linked to variability in frictional conditions, die temperatures, or material properties. Future integration of the proposed method with design of experiments (DOE) and surrogate modeling techniques could further enhance its applicability by optimizing preform designs within a localized design space. The findings suggest that this approach provides a practical and powerful tool for advancing both new and existing forging production lines toward higher efficiency and sustainability. Full article

Platinum wires, known for their excellent electrical conductivity and durability, are widely used in high-precision industries, such as aerospace and automotive. These wires are typically coated with polyamide for protection; however, specific manufacturing processes require the coating to be selectively removed. Although traditional chemical stripping methods are effective, they are associated with high costs, safety concerns, and long processing times. As a result, laser ablation has emerged as a more efficient, precise, and cleaner alternative, especially at the microscale. In this study, ultraviolet nanosecond laser ablation was applied to remove polyamide coatings from ultra-thin platinum wires in a water-assisted environment. The presence of water enhances the process by promoting thermal management and minimizing debris. Key processing parameters, including the scanning speed, overlap percentage, and line distance, were evaluated. The optimal result was achieved at a scanning speed of 1200 mm/s, line distance of 1 µm, and single loop in water-ambient, where coating removal was complete, surface roughness remained low, and wire tensile strength was preserved. This performance is attributed to the effective energy distribution across the wire surface and reduced thermal damage due to the heat dissipation role of water, along with controlled overlap that ensured full coverage without overexposure. A thin, well-maintained water layer confined above the apex of the wire played a crucial role in regulating the thermal flow during ablation. This setup helped shield the delicate platinum substrate from overheating, thereby maintaining its mechanical integrity and preventing substrate damage throughout the process. This study primarily focused on analyzing the main effects and two-factor interactions of these parameters using Analysis of Variance (ANOVA). Interactions such as Speed × Overlap and Speed × Line Distance were statistically examined to identify the influence of combined factors on tensile strength and surface roughness. In the second phase of experimentation, the parameter space was further expanded by increasing the line distance and number of loops to reduce the overlap in the X-direction. This allowed for a more comprehensive process evaluation. Again, conditions around 1200 mm/s and 1500 mm/s with 2 µm line distance and two loops offered favorable outcomes, although 1200 mm/s was selected as the optimal speed due to better consistency. These findings contribute to the development of a robust, high-precision laser processing method for ultra-thin wire applications. The statistical insights gained through ANOVA offer a data-driven framework for optimizing future laser ablation processes. Full article

The topographical, microstructural, and mechanical surface properties of additively manufactured components depend on variations of several processing parameters. Most studies focus on a narrow range of parameter variations, with the surface and subsurface characteristics being determined for that limited set of conditions. This makes it difficult to optimize these properties for additively manufactured parts and the energy consumption of the additive-manufacturing (AM) process. Our study looks at the systematic variation of two key AM parameters over their full range using a commercial AM machine. The laser scanning speed (500–1700 mm/s) and the laser power (250–370 W) were the parameters used. We analyze and discuss how these two parameters affect the surface topography, roughness, porosity, microstructure and hardness, as well as their anisotropy for the top and side surfaces during powder bed fusion, using a single AM machine and printing strategy. The aluminum alloy AlSi10Mg was selected for the study. It is one of the most commonly used materials in die casting and has the potential to take advantage of AM technology, since these parts can be lightweight, have good mechanical properties and to be produced with complex shapes. Full article

This study presents the development of a deep drawing process under an indirect hot stamping method for manufacturing an automotive internal combustion engine oil pan from ultra-high-strength steel (UHSS) sheets, specifically 22MnB5. The forming process involves two stages—cold stamping followed by hot stamping—and is finalized with rapid quenching to achieve a martensitic microstructure. Finite element simulation using AutoForm R8 was conducted to determine optimal forming conditions. The simulation results guided the design of the forming tools and were validated through experimental trials. The final oil pan component exhibited no cracks or wrinkles, with maximum thinning below 18%, a hardness of 550.63 HV, and a fully martensitic phase. This research demonstrates a novel and effective solution for producing deep-drawn, high-strength components using indirect hot stamping, contributing to the advancement of automotive forming processes in Thailand. Full article

The safe removal of residual flammable contaminants from vertical mixer blades is a crucial challenge in aerospace propellant production. While robotic cleaning has become the preferred solution due to its precision and operational safety, the complex helical geometry of mixer blades presents significant challenges for robotic systems, primarily in three aspects: (1) dynamic sub-region division, requiring simultaneous consideration of functional zones and residue distribution, (2) ensuring path continuity across surfaces with varying curvature, and (3) balancing time–energy efficiency in discontinuous cleaning sequences. To address these challenges, this paper proposes a novel robotic cleaning path planning method for complex curved surfaces. Firstly, we introduce a blade surface segmentation approach based on the k-means++ clustering algorithm, along with a sub-surface patch boundary determination method using parameterized curves, to achieve precise surface partitioning. Subsequently, robot cleaning paths are planned for each sub-surface according to cleaning requirements and tool constraints. Finally, with total cleaning time as the optimization objective, a genetic algorithm is employed to optimize the path combination across sub-facets. Extensive experimental results validate the effectiveness of the proposed method in robotic cleaning path planning. Full article

In the stamping process of automotive parts, springback is a major problem when using Advanced High-Strength Steel (AHSS). This phenomenon significantly impacts the shape accuracy of products and is difficult to control. This study aims to optimize process parameters such as blank holder force (BHF), die clearance, and blank width to minimize springback in the workpiece. Using optimal process parameters will enhance the efficiency of die compensation processes. The study uses the Finite Element Method (FEM) simulation to predict forming behavior. The case study, Reinforcement-CTR PLR, is made from AHSS grade JSC980Y with a thickness of 1 mm. Four material model combinations were evaluated against actual experiment results to select the most accurate springback prediction model. A full factorial design was used for experiments with varied process parameters. The optimization process used regression and various Artificial Neural Networks (ANNs). From the result, a Deep Neural Network (DNN) with two hidden layers performed with the highest accuracy compared to the other models. The optimal process parameters were identified as 27.62 tons BHF, 1 mm die clearance, and a 290 mm blank width. These optimal results achieved 98.05% of the part area within a displacement tolerance of −1 to 1 mm, closely matching FEM-based validation. Full article

Additive manufacturing technologies are being increasingly adopted in the manufacturing industries due to their capabilities in producing complex geometries without the need for special tools. Material extrusion (MEX-TRB/P) is a popular additive manufacturing technology due to its simple operation. However, optimization of various process parameters remains a challenge, as incorrect combinations can lead to reduced dimensional accuracy and incapacitated mechanical properties of the fabricated parts. Given that the MEX-TRB/P process relies on the heating and cooling of thermoplastic materials, understanding the role of temperature is critical to optimizing the MEX-TRB/P printed parts. This article reviews existing research on the effects of process parameters, specifically those that are temperature sensitive, on the mechanical properties of the printed parts. The review first classified the process parameters into temperature sensitive and non-temperature sensitive process parameters. Then, the influence of temperature on the bonding quality and material properties is investigated, and a relationship between the thermal conditions and mechanical properties of 3D printed parts is established. This review also summarizes experimental and numerical methods for investigating temperature evolution during printing. This study aims to provide a deep understanding of the optimization of temperature-sensitive process parameters and their role in enhancing the mechanical properties of MEX-TRB/P-printed parts. Full article

In the composite materials industry, the fabrication of complex parts often necessitates the use of specialized tools, such as milled molds with intricate geometries. Among these, machined aluminum molds are widely regarded as effective tools for laminating CFRP (Carbon Fiber Reinforced Polymer) prepreg materials. However, the cost and time associated with machining aluminum molds can be significant. This paper presents a novel method for manufacturing molds using polymeric acrylic resin combined with aluminum trihydrate material (commercially known as DuPont Corian materials), offering a potential alternative with reduced complexity and cost. The study investigates the influence of various milling parameters, such as tool speed, tool type, feed rate, and depth of cut on the mechanical properties and surface finish of the molds. Also, laminating tests are conducted; results indicate that laminating tools produced through this method achieve competitive mechanical performance, including a hard, smooth surface with low roughness, making them viable candidates for industrial use. The proposed approach is particularly beneficial in terms of reducing machining time and overall costs while maintaining the necessary precision and durability for high-performance applications. This method, therefore, represents a promising solution for manufacturers seeking to optimize mold production processes in the composite materials industry. Full article

Additive manufacturing (AM) is a rapidly evolving technology that enables the fabrication of complex 3D components across a wide range of materials and applications. Among various AM techniques, direct energy deposition (DED) has gained significant attention for its ability to produce metal and alloy components with moderate geometric complexity while maintaining a high deposition rate. This makes DED particularly suitable for real-world applications, including in-situ repair and restoration of metallic parts. Due to the nature of the DED process, components undergo extreme heating and cooling cycles, leading to microstructural evolution, process-induced defects, and variations in properties. While extensive research has explored the microstructure and mechanical properties of DED-fabricated alloys, studies on their surface degradation remain incomplete. Corrosion behavior has been well documented, given its significance in AM alloys; however, their tribological performance remains largely unexplored. This paper provides a comprehensive review of the wear behavior of DED-manufactured alloys, emphasizing the potential of DED technology for producing durable components. Specifically, it examines the wear characteristics of four key material groups—Fe-based, Ni-based, Ti-based, and Cu-based alloys—by summarizing existing studies and analyzing the underlying mechanisms influencing their wear resistance. Finally, the paper identifies research gaps and outlines future directions to advance the understanding of wear performance in DED alloys, paving the way for further innovation in this field. Full article

Additive manufacturing (AM) stands out for its variable applications in terms of material, quality, and geometry. Wire Arc Additive Manufacturing (WAAM) is remarkable for producing large parts in reduced times when compared to other AM methods. The possibility of producing a part with a near-net shape not only enhances productivity but also reduces resources usage. However, parts produced by WAAM may need post-processing by machining to achieve functional surface requirements. Therefore, it is important that machining, even if minimized, does not lead to a significant environmental impact. In this sense, this work evaluates the effect of using compressed air, dry cut, and synthetic biodegradable cutting fluid at varying nozzle positions and flow rates on the surface quality of ER70S-6 steel produced by WAAM, after milling with TiAlN-coated carbide tools. To analyze the surface roughness, parameters Ra, Rq, and Rz were measured and microscopy was used to further evaluate the surfaces. The surface hardness was also evaluated. The results showed that a flow rate of 10 L/min promotes better surface quality, which can be further improved using compressed air, leading to a surface quality 50% better when compared to dry cutting. Dry cut was not suitable for machining ER70S-6 WAAM material as it resulted in rough surface texture with an Rz = 4.02 µm. Compressed air was the best overall condition evaluated, achieving a 36% Ra reduction compared to dry cutting, the second-lowest hardness deviation at 6.51%, and improved sustainability by eliminating the need for cutting fluid. Full article

Lattice structures offer the possibility to obtain lightweight components with additional functionalities, improving their shock absorption and thermal exchange properties. Recently, a body-centered cubic (BCC) lattice structure has been used to fabricate metal lattice sandwich panels (MLSPs) for aerospace applications. MLSPs are made of two external skins and a lattice core and can be produced thanks to laser powder bed fusion technology (LPBF), which is characterized by its superior printing accuracy with respect to other additive manufacturing processes for metals. Since few studies can be found in the literature on Ti-6Al-4V MLSPs, further work is needed to evaluate the mechanical response of these panels. Moreover, due to their design complexity and to avoid a costly experimental campaign, numerical simulation could be used to encourage the industrial application of these structures. In this paper, different cell configurations were printed and tested in compression to study the influence of the cell’s geometrical parameters, i.e., the cell size and beam radius, on the mechanical response of MLSPs. Numerical simulations of the LPBF of these geometries were also carried out to understand how the residual stresses can be varied by varying the cell configuration. A geometrical evaluation was carried out to quantitatively express the influence of the beam radius and cell size on the resulting volume fraction, which strongly influences the mechanical behavior and residual stress profiles of MLSPs. From the analysis, we found that the C2-R0.35 sample resulted in the configuration with the highest compressive strength, while C3-R0.25 showed the lowest and most uniform residual stress profile. Full article

The growing demand for sustainable materials has driven interest in natural fiber-reinforced composites as eco-friendly alternatives to synthetic materials. This research investigates the fabrication and mechanical performance of hemp and sisal fiber-reinforced composites, with a focus on improving fiber–matrix bonding through alkali and fungal treatments. Experimental results show that fungal treatment significantly improves tensile and flexural strength, while hardness slightly decreases. Water absorption tests revealed moderate reductions in hydrophilicity compared to untreated samples, although absolute water uptake remains higher than conventional glass/epoxy composites. Microscopy analysis further confirmed enhanced fiber adhesion and structural integrity in treated specimens. These findings suggest that hybrid composites reinforced with hemp and sisal, particularly with fungal treatment, hold promise for low-to-medium load sustainable applications in the automotive interiors, packaging, and construction industries, where moderate mechanical performance and partial biodegradability are acceptable. This research contributes to the advancement of bio-based composite materials while acknowledging current limitations in long-term durability and complete biodegradability. Full article

An environmentally friendly alternative to phosphate-based lubrication was studied through the lateral cold extrusion forging of internal gears using pulsating motion. A die set with a removable punch enabled a detailed observation of relubrication, forming load, material flow, and gear geometry. Pulsating motion with liquid lubricant significantly reduced the forming load during punch penetration, while no such effect was observed under dry conditions. Even when the number of pulses (n) was set to 1, relubrication occurred, and a comparable load reduction to that of n = 3 was achieved, shortening the forming time. When n = 3, pulsating motion contributed to increased gear height and reduced separated burr formation; however, it also caused slightly incomplete tooth filling, which may be undesirable for precision applications. Varying the pulse start position from 5.50 mm to 13.30 mm influenced forming load and material flow, further affecting gear geometry. During punch extraction, the presence of liquid lubricant reduced the load and suppressed material displacement, while dry conditions led to higher extraction loads and more deformation. Full article

The optimization of cutting parameters is critical for improving machining efficiency and extending tool life. Colding’s equation is one such tool life prediction equation that can be used to optimize the machining parameters. However, the equation is complex and is often challenging to solve to evaluate its mathematical constants. This study investigates three distinct approaches for calculating the five constants (‘K’, ‘H’, ‘M’, ‘N0’, and ‘L’) in Colding’s equation. These techniques include analytical equation calculation and different curve fitting approaches. The primary objective was to assess the accuracy and effectiveness of these methods in predicting cutting parameters. Two workpiece materials, K1045 and Mild Steel, were used with results indicating that the Python 3.13 programming approach outperformed the other methods, including MATLAB R2024b and analytical calculations, achieving error percentages of 9.08% for K1045 and 5.51% for Mild Steel compared to 12.3% and 35.3% for K1045 and 12.4% and 64.3% for Mild Steel, respectively. Furthermore, the constants ‘N0’, ‘M’, and ‘H’ displayed different values for the two materials, indicating their dependence on workpiece material properties. Moreover, it was evident that Mild Steel exhibited better machinability than K1045 at low MRR (40–80 cm³/min), with up to 55.8% longer tool life, but K1045 performed better at medium and high MRRs, suggesting different machinability behaviours under varying cutting conditions. Overall, the findings demonstrate that Colding’s model, when applied with the appropriate computational method, can accurately optimize cutting parameters for different materials, contributing to more efficient and cost-effective machining processes. Full article

This study presents a systematic optimization of GTAW welding parameters to achieve a pipe-to-pipe butt weld with a root height consistently below 2 mm when joining stainless-steel 316L material, employing the Taguchi design of experiments. To the authors’ knowledge, no similar studies have been conducted to explore the optimization of welding parameters specifically aimed at minimizing weld root height under 2 mm in stainless-steel EO pipeline welding applications. This gap in the existing literature highlights the innovative aspect of the current study, which seeks to address these challenges and improve welding precision and joint reliability. Root height, also referred to as weld root reinforcement, is defined as the excess weld metal protruding beyond the inner surface root side of a butt-welded joint. The input parameters considered are the welding current, voltage, speed, and root gap configurations of 1, 1.5, and 2 mm. Welding was performed according to the Taguchi L-09 experimental design. Nine weld samples were evaluated using liquid penetrant testing to detect surface-breaking defects, such as porosity, laps, and cracks; X-ray radiography to identify internal defects; and profile radiography to assess erosion, corrosion, and root height. Among the nine welded plate samples, the optimal root height (less than 2 mm) was selected and further validated through the welding of a one-pipe sample. An additional macro examination was conducted to confirm the root height and assess the overall root weld integrity and quality. Full article

Electric discharge machining (EDM) is widely employed for machining hard, conductive materials. Tool rotation has emerged as an effective strategy to enhance debris flushing and improve stability during deep-hole EDM drilling. This study proposes a machine learning-based approach to evaluate the influence of tool rotation and predict the unstable machining conditions in EDM of ultrafine grained tungsten carbide. A structured analytical workflow, combining Taguchi–Grey optimization, regression analysis, and classification models, was designed to capture discharge dynamics across macro- and micro-timescales. Classification models trained on raw and processed electrical signal features achieved over 88% accuracy and 90% recall. SHAP analysis revealed that the relationship between key discharge events such as sparks and short circuits varied significantly across stable and unstable machining phases, underscoring the importance of phase-specific modeling. While correlation analysis showed weak global associations, phase-dependent SHAP values revealed opposing feature effects, allowing the context-informed interpretation of model behavior. Phase segmentation revealed that, compared to 1000 RPM, short circuits were reduced by about 40% during stable machining at 8000–9000 RPM. Conversely, during unstable phases, spark effectiveness dropped by nearly 45%, and secondary discharges increased throughout this range. These insights support the design of adaptive control strategies that adjust the rotation rate in response to detected phase changes, aiming to sustain machining stability. The findings support the development of dynamic control frameworks to improve EDM performance, particularly for mold fabrication using tungsten carbide. Full article

Tungsten heavy alloys (WHAs) are two-phase composites known for their exceptional density, strength, hardness, and ductility, making them ideal for radiation shielding, kinetic energy penetrators, and aerospace components. Due to their high melting point, WHAs are primarily processed via powder metallurgy, with liquid-phase sintering (LPS). Spark plasma sintering (SPS) and microwave sintering are emerging as advanced consolidation techniques. Recent research has focused on improving WHA performance through microstructural manipulation, alloying with elements like Fe, Co, Mo, and Re; rare earth oxides like Y₂O₃, La₂O₃, and Ce₂O₃; and employing high-entropy alloys (HEAs) as matrix phase. Additionally, additive manufacturing (AM) techniques are increasingly being used to fabricate complex WHA components. Despite their advantages, WHAs still exhibit limitations in penetration performance, primarily due to their tendency to form mushroom-like heads upon impact rather than self-sharpening. Ongoing research seeks to enhance shear localization, refine grain structure, and optimize processing methods to improve the mechanical properties and impact resistance of WHAs. Furthermore, modeling and simulation approaches are being explored to understand the mechanical behavior of WHAs. This review comprehensively overviews the above aspects and presents recent advances in WHA processing. Full article

Metal additive manufacturing is a disruptive technology that is changing how various alloys are processed. Although this technology has several advantages over conventional manufacturing, it is still necessary to standardize its properties, which are dependent on the relative density (RD). In addition, since experimental designs are costly, one solution is using machine learning algorithms that allow the effects of variations in the processing parameters on the resulting density of the additively manufactured components to be anticipated. This work assembled a database based on data from 673 observations and 10 predictors to forecast the relative density of 316L stainless steel and AlSi10Mg components produced by laser powder bed fusion (L-PBF). LazyPredict was employed to select the algorithm that best models the variability of the inherent data. Ensemble boosting regressors offer higher accuracy, providing hyperparameter fitting and optimization advantages. The predictions’ precision for aluminum and stainless steel obtained an R² value greater than 0.86 and 0.83, respectively. The results of the SHAP values indicated that laser power and energy density are the parameters that have the greatest impact on the predictability of the relative density of Al-Si10-Mg and SS 316L materials processed by L-PBF. This study presents a compendium of data for the additive fabrication of stainless steel and aluminum alloys, offering researchers a guide to understanding how processing parameters influence RD. Full article

Over the past decade, friction stir spot welding (FSSW) has gained increasing attention, making it a competitor to conventional welding methods such as resistance welding, rivets, and screws. This type of welding is environmentally friendly because it does not require welding tools and is solid-state welding. This study attempts to demonstrate the importance of pin geometry on temperature distribution and joint quality by using threaded and non-threaded pins for similar and dissimilar alloys. To this end, thermal analysis of the welded joints was conducted using real-time monitoring from a thermal camera and an infrared thermometer, in addition to finite element method (FEM) simulations. The thermal analysis showed that the generated temperatures were higher in dissimilar alloys (Al-Cu) than in similar ones (Al-Al), reaching about 350 °C. In addition, dissimilar alloys show more pronounced FSSW stages through extended periods for each plunging, dwelling, and drawing-out time. The FEM simulation results are consistent with those obtained from thermal imaging cameras and infrared thermometers. The dwelling time was influential, as the higher it was, the more heat was generated, which could be close to the melting point, especially in aluminum alloys. This study provides an in-depth experimental and numerical investigation of temperature distribution throughout the welding cycle, utilizing different pin geometries for both similar and dissimilar non-ferrous alloy joints, offering valuable insights for advanced industrial welding applications. Full article

The miniaturization of smart materials has become a new trend in the modern manufacturing industry due to its enormous application in the aerospace, biomedical, and automobile sectors. Nickel–titanium (NiTi)-based binary shape memory alloys (SMAs) are one of the smart materials with certain supreme features like shape memory effect, pseudo-elasticity, high ductility, strong corrosion-resistance, and elevated wear resistance. For this, several micro-machining processes have been developed to machine NiTi SMAs. This paper summarizes all of the conventional and non-conventional micro-machining processes employed to machine NiTi SMAs. In this review process, the surface integrity, dimensional accuracy of the machined surface, cutting force and tool wear analysis during conventional and non-conventional micro-machining of NiTi SMA are evaluated mostly with the aid of input process variables like cutting speed, depth of cut, width of cut, types of coolants, tool coating, discharge voltage, capacitance, laser fluence, pulse duration, scan speed, electrolysis concentration and gap voltage. The optimization of process parameters using different methods during conventional and non-conventional micro-machining of NiTi SMAs is also analyzed. The problems faced during conventional micro-machining of NiTi SMAs are overcome by non-conventional micro-machining processes as discussed. The present study aims to recognize potential developments in the improvement of the micro-machinability of NiTi SMAs. Full article

This study focuses on the energy absorption and wearer comfort attributes of regular lattice structures fabricated by laser powder bed fusion from two elastomeric materials, namely TPU1301 and TPE300, for use in personal protective equipment (PPE). This study compares Body-Centered Cubic (BCC), Face-Centered Cubic (FCC) and Kelvin (KE) lattice structures with density varying from 0.15 to 0.25 g/cm³, cell size varying from 10 to 14 mm and feature size varying from 1 to 3 mm. Quasi-static and dynamic compression testing confirmed that among the studied geometries, KE structures printed with TPE300 powders provide the best combination of reduced peak acceleration and increased compliance, thereby improving both safety and comfort. Using the protection–comfort maps built on the basis of this study enables the design of lightweight and compact protective structures. For example, if a safety layer protecting a 100 mm² surface area can be manufactured from either TPE300 or TPU1100 powders using either KE or FCC structures, the KE TPE300 layer will be 1.5 times thinner and 2.5 times lighter than its FCC TPU1301 equivalent. The results of this study thus provide a basis for the optimization of lattice structures in 3D-printed PPE to meet both service and manufacturing requirements. Full article

In the present study, an approach for determining the different states of ball burnishing (BB) operations aimed at forming regular reliefs’ patterns on planar surfaces is introduced. The methodology involves acquiring multi-axis accelerometer data from CNC-driven milling machine to capture the dynamics of the BB tool and workpiece, mounted on the machine table. Following data acquisition from an AISI 304 stainless steel workpiece, which is subjected to BB treatments at different toolpaths and feed rates, the recorded signals are preprocessed through noise reduction techniques, DC component removal, and outlier correction. The refined data are then transformed using a root mean square (RMS) operation to simplify further analysis. A Gaussian Mixture Model (GMM) is subsequently employed to decompose the compressed RMS signal into distinct components corresponding to various operational states during BB. The experimental trials at feed rates of 500 and 1000 mm/min reveal that increased feed rates enhance the distinguishability of these states, thus leading to an augmented number of statistically significant components. The results obtained from the proposed GMM based algorithm applied on compressed RMS accelerations signals is compared with two other methods, i.e., Short-Time Fourier Transforms and Continuous Wavelet Transform. The results from the comparison show that the proposed GMM method has the advantage of segmenting three to five different states of the BB-process from nonstationary accelerations signals measured, while the other tested methods are capable only to distinguish the state of work of the deforming tool and state of its rapid (re-)positioning between the areas of working, when there is no contact between the BB-tool and workpiece. Full article

Long-term stability and laser-induced damage resistance of optical components in the UV region are critical for enhancing their performance in UV high-power laser applications. This study evaluates the laser-induced damage threshold (LIDT) of commercially available UV optical windows with anti-reflective (AR) coating, produced through various coating techniques and designed for high-power lasers. A third-harmonic (343 nm) wavelength with good beam quality was generated in the picosecond regime to investigate the LIDT of optical components. The LIDT for each sample was measured under controlled conditions and compared based on their coating techniques. The sample coated with Al₂O₃/SiO₂ through ion beam sputtering has the best LIDT value, of 0.6 J/cm², among the tested samples, based on the hundred-thousand-pulses methodology. The damage threshold curve and the corresponding damage morphology are discussed in detail, and these findings provide insights into the durability and susceptibility of UV optics for advanced laser systems available in the market. Full article

Additive manufacturing (AM) is one of the most frequently used technologies to produce complex configuration products. Moreover, AM is very well known as a technology which is characterized by a low amount of generated waste and the potential to be called zero-waste technology. As is known, there are seven main groups of technologies described in the ISO/ASTM 52900 standard that allow the use of very different materials from polymers to metals, ceramics, and composites. However, the increased utilization of additively manufactured composites for different applications requires a deeper analysis of production processes and materials’ characteristics. Various AM technologies can be used to produce complex composite structures reinforced with short fibers; however, only material extrusion (MEX)-based technology is used for the production of composites reinforced with continuous fibers (CFs). At this time, five different methods exist to produce CF-reinforced composite structures. This study focuses on co-extrusion with the towpreg method. Because of the complexity and layer-by-layer nature of the process, defects can occur during production, such as poor interlayer adhesion, increased porosity, insufficient impregnation, and others. To eliminate or minimize defects’ influence on mechanical properties and structural integrity of additively manufactured structures, a hypothesis was proposed involving heat treatment. Carbon fiber’s conductive properties can be used to heal the composite structures, by heating them up through the application of electric current. In this research article, an experimental evaluation of conditions for additively manufactured composites with continuous carbon fiber reinforcement for self-healing processes is presented. Mechanical testing was conducted to check the influence of heat treatment on the flexural properties of the composite samples. Full article

This study presents an analytical description of the computed tomography-based volumetric additive manufacturing (VAM) process, with an emphasis on the impact of resin properties on product dimensions. The main issue addressed in this study is the assessment of the dimensional limitation of the objects produced using the VAM process, which is usually reported to be of the order of one centimeter. An analytical model is introduced to predict the product size based on the resin property (penetration depth—D_p), vial size (radius), and the duration of part formation, and the results indicate significant correlations among these parameters. A method of D_p measurement and analysis that is appropriate for the VAM process is also introduced. Mathematical justification is provided along with experimental verification for the effects of the main governing factor, D_p, on the maximum possible product size. Multiple criteria are also introduced for selecting the appropriate size of the resin container (vial) based on the desired object size and the value of D_p. It was found that the D_p is a crucial factor in analysis and experimentation in the VAM process, and its value is fundamentally different from the one obtained in the conventional polymerization AM methods. The product dimension based on the resin property, vial size, and time for the formation of the part is introduced by the analytical model. This model provides valuable insights into the complex interplay of factors influencing VAM outcomes and can facilitate informed decision-making in material selection and process design. Full article

Inconel 600 alloy has gained consideration as a favourable material for heat and power applications, particularly in turbine blades, due to its superior mechanical behaviour encompassing strength, toughness, oxidation resistance, and ductility. Tungsten Inert Gas (TIG) welding is one of the preferred techniques for joining these alloys. Therefore, the investigation of the mechanical behaviour after the welding process is crucial for selecting the appropriate technique for joining Inconel 600 sheets. This research focuses on investigating the microstructure and mechanical behaviour of TIG-welded Inconel 600 through a series of tests, such as tensile, fatigue, creep, and hardness evaluations. In addition, microstructural analysis is combined with these mechanical evaluations to simulate the operating conditions experienced by turbine blades. Key parameters such as yield strength, tensile strength, and elongation have been evaluated through these analyses. The Ramberg–Osgood relationship has been investigated using the engineering and true stress–strain curves obtained from the welded specimens. The results of the fatigue test illustrate the relationship between strain amplitude and the number of cycles to failure for single and double-edge notched specimens. The test was performed at two different loads including 400 MPa and 250 MPa at a constant temperature of 650 °C, and the corresponding strain-time curves were recorded. The results showed rapid creep failure at 650 °C, suggesting that TIG welding may need to be optimized for high temperature applications. Full article

Investigating failure mechanisms in cutting tools used in advanced industries like biomedical and aerospace, which operate under extreme mechanical and chemical conditions, is essential to prevent failures, optimize performance, and minimize financial losses. The diamond-turning process, operating at micrometer-length scales, forms a tightly bonded built-up edge (BUE). The tribochemical interactions between a single-crystal diamond and its deformed chip induce inter-diffusion and contact, rapidly degrading the cutting edge upon BUE fracture. These effects intensify at higher deformation speeds, contributing to the observed rapid wear of diamond tools during d-shell-rich metal machining in industrial settings. In this study, these interactions were studied with niobium (Nb) as the transition metal. Tribochemical effects were observed at low deformation speeds (quasistatic; <1 mm/s), where thermal effects were negligible under in situ conditions inside the FEI /SEM vacuum chamber room. The configuration of the interface region of diamond and transition metals was characterized and analyzed using focused ion beam (FIB) milling and subsequently characterized through transmission electron microscopy (TEM). The corresponding inter-diffusion was examined by elucidating the phase evolution, element concentration profiles, and microstructure evolution via high-resolution TEM/Images equipped with an TEM/EDS system for elemental characterization. Full article

Due to the significantly increasing demand for plastic components, it has become necessary to investigate polymer recycling solutions to eliminate their adverse environmental impact. The focus of this study is to examine the feasibility of recycling polypropylene and a thermoplastic elastomer up to five times using additive manufacturing. This study also focuses on the production and evaluation of the quality of hybrid components based on polypropylene and thermoplastic elastomers. A thermomechanical recycling approach is used, which involves subjecting polymers to thermal and mechanical processes to obtain a usable material form after each recycling cycle. Additive manufacturing was used to produce specimens using the material in both filament and granular form. The thermal, mechanical, and rheological properties of the specimens were characterized by means of various analytical techniques, including tensile test, impact test, optical microscopy, Fourier-transform infrared spectroscopy, thermogravimetric analysis, dynamic scanning calorimetry, and rheological tests in order to study the degradation characteristics of the recycled polymers. The results generally indicate that the chosen recycling procedure causes only slight alterations in the material properties by means of thermal and rheological tests, while impacting mechanical properties and printability. Full article