Key Process Parameters Research Articles

Effect of Warpage Pattern of Printed Circuit Board on Solder Paste Volume in Stencil Printing Process

Abstract This study examines the influence of printed circuit board (PCB) warpage patterns on solder paste distribution during the stencil printing process (SPP). A multi-stage numerical model was developed and validated with experimental data, showing a deviation of less than 4%, to simulate the SPP with various warped PCB configurations. Various warpage patterns, including horizontal, vertical, spherical, and diagonal warpage, were analyzed along with key process parameters such as stopper load, squeegee load, and the positioning of clamping plates to identify the conditions that most significantly affect solder paste distribution. Results indicate that increasing the stopper load to 170 N can reduce PCB warpage by approximately 60%, leading to a more even solder paste volume distribution. The squeegee load had minimal impact on gap reduction due to the constraints imposed by the side-clamping plates. Among the warpage patterns, diagonal warpage yielded the most uniform solder paste distribution, with up to 43% better consistency compared to horizontal warpage, which exhibited the greatest variation.

Enhancing overall performances of large constructed wetlands using an integrated approach of numerical simulation and response surface method--Taking Bagong hybrid CWs as an example.

Constructed wetlands (CWs) with low carbon properties represented an effective approach for treating low-polluted water and improving water quality. Here, a research scheme was proposed to achieve maximum operation benefits of the large-scale CWs through parameter identification, operation simulation, evaluation, and analysis of the water quality process. Based on the two-dimensional water hydrodynamic model coupling with the Eco-Lab water quality module (with nutrients), simulation for Bagong hybrid CWs was successfully conducted. Variables were estimated using response surface design (RSD), and the values of model parameters were calibrated in accordance with central combination design (CCD) experiments. Ten key parameters in the water quality process affecting the overall pollutant removal of CWs were identified, and the water quality model of the CWs could be replicated well with the actual situation within the 95% confidence interval. The water purification effect of the CWs under five different influent flow conditions was simulated, and the maximum hydraulic loading (0.036m3·(m-2·h-1)) of the CWs was determined with the effluent water quality to meet the design requirements. The integrated method could effectively enhance the efficiency of parameter calibration and significantly reduce the simulation workload. The results of pollutants migration and transformation under different influent conditions could provide a universally applicable and valid method in engineering applications, and process a promising application prospect.

Data-based modeling of an industrial flotation column using classic and intelligent machine learning algorithms

ABSTRACT In the mineral production industry, the separation of valuable from waste minerals is generally conducted through the froth flotation process. Flotation is a multivariate and complex process that cannot be modeled using traditional mathematical procedures. Therefore, machine learning algorithms must be applied to experimental databases for the identification of the flotation system. The grade and recovery of concentrate serve as key metallurgical parameters in the flotation process, reflecting the quality and quantity of the final product. These parameters are directly linked to the manipulated variables of the process, such as gas velocity, frother type/dosage, and slurry solids concentration. In this study, the metallurgical parameters (i.e. copper recovery and concentrate grade) of an industrial flotation column were modeled using various machine learning algorithms. The final results indicate that optimised Gaussian Process Regression (GPR) outperforms the other learning algorithms in the data-based modeling of the flotation system.

Material Characterisation Experiments and Data Preparation for a Finite Element Analysis of the Deep Drawing Process Using AA 1050-O

The use of computer simulation to imitate physical processes has proven to be a time-efficient and cost-effective way of performing scenario testing for process optimisation in different applications. The finite element analysis (FEA) is the dominant numerical simulation method for analysing sheet metal forming processes. It uses mathematical tools and computer-aided engineering software programmes to predict forming processes. To improve the quality of output from the simulation, accurate material characterisation data that correctly model the behaviour of the material when it undergoes deformation must be provided. This paper outlines the stages of conducting material characterisation experiments, such as tensile, hardness, and formability tests, using the aluminium alloy AA1050-O. Sample preparation, the machine setup, and testing procedures for the material characterisation tests are given. Subsequent data preparation methods for input into an FEA software programme are also outlined. Implications of the testing results to a deep drawing process are examined while considering the formation of a rectangular monolithic component measuring 2300 mm by 1400 mm with a drawing depth of approximately 150 mm. The results from the characterisation tests indicate that the forming process for the product can be achieved using cold forming at room temperatures as a 25% strain was recorded before necking against an anticipated uniaxial strain of 5.93%. The aluminium alloy AA1050-O demonstrated a negligible strain rate sensitivity in the forming region, thus eliminating tool velocity from the key process parameters that should be considered during FEA simulations. A 50% increase in hardness was recorded after strain hardening.

Effects of expansion rate and sintering time on the morphology and mechanical properties of double‐expanded polytetrafluoroethylene tubes

AbstractA novel manufacturing technique for expanded polytetrafluoroethylene (ePTFE) has been previously developed. Through modifications to the processing conditions by adding one additional expansion step at lower temperatures, one can produce highly compliant double‐expanded PTFE (dePTFE) with enhanced mechanical properties. The superior mechanical properties of dePTFE stem from the unique presence of wavy fibrils, which can be tuned to meet the specific requirements of various applications. This study investigated two main processing parameters: the expansion rate during the first expansion step (50, 75, and 112.5 mm/min) and the sintering time between the two expansion steps (67.5, 90, and 135 min). The mechanical properties in both the longitudinal and circumferential directions were measured, and the microstructure of dePTFE was analyzed through scanning electron microscopy (SEM) and image processing. The dePTFE exhibited smaller pore structure and higher leakage (water entry) pressures when produced with a higher expansion rate. By increasing the sintering time, the circumferential strength of dePTFE could be improved by 50% per time interval increase. Higher sintering temperatures also increased material stiffness in the circumferential direction. The compliant properties of dePTFE were not compromised with changes in the microstructure, still attaining 30%–50% increased elastic strain, while maintaining its characteristic “toe region” in the modulus.Highlights Relation between processing, morphology, and properties of dePTFE was studied. Wavy fibrils increased flexibility without reducing the strength of dePTFE. Expansion rate and sintering time are the two key processing parameters. Higher expansion yielded better mechanical strength and smaller pore sizes. Higher sintering temp increased material stiffness in the circ. direction.

Optimization of 3D Printing Nozzle Parameters and the Optimal Combination of 3D Printer Process Parameters for Engineering Plastics with High Melting Points and Large Thermal Expansion Coefficients

Three-dimensional printing is a transformative technology in the manufacturing industry which provides customization and cost-effectiveness for all walks of life due to its fast molding speed, high material utilization, and direct molding of arbitrary complex structural parts. This study aims to improve the molding accuracy of 3D printed polyether ether ketone (PEEK) samples by systematically studying key process parameters, including printing speed, layer thickness, nozzle temperature, and filling rate. The 3D printing nozzle has an important impact on the extrusion rate of the melt, and the fluid simulation of the nozzle was carried out to explore the variation characteristics of the melt flow rate in the nozzle and optimize the nozzle structure parameters. In order to effectively optimize the process, considering its inherent efficiency, robustness, and cost-effectiveness, the L9 orthogonal array experimental design scheme was used to analyze the effects of printing speed, layer thickness, nozzle temperature, and filling rate on the molding accuracy of the test sample, and the optimal combination of process parameters was optimized through the comprehensive weighted scoring method so as to improve the molding accuracy of the 3D printed PEEK sample; finally, the molding accuracy of the components printed using the Sermoon-M1 3D printer with the optimized nozzle structure was printed. The results show that the nozzle structure is optimal when the convergence angle is 120° and the aspect ratio is 2, and the outlet cross-section velocity is increased by 2.5% and 2.7%, respectively. The order of influence strength on the dimensional accuracy of the test sample is layer thickness > filling rate > nozzle temperature > printing speed. The optimal combination of parameters is: a printing speed of 15 mm/s, a layer thickness of 0.1 mm, a nozzle temperature of 420 °C, and a filling rate of 50%. The insights derived from this study pave the way for predicting and implementing the selection of optimal process parameters in the production of 3D printed products, with important implications for the optimal molding accuracy of printed components.

Influence of Process Parameter and Build Rate Variations on Defect Formation in Laser Powder Bed Fusion SS316L.

Laser powder bed fusion (LPBF) is an additive manufacturing process that has gained interest for its material fabrication due to multiple advantages, such as the ability to print parts with small feature sizes, good mechanical properties, reduced material waste, etc. However, variations in the key process parameters in LPBF may result in the instantiation of porosity defects and variation in build rate. Particularly, volumetric energy density (VED) is a variable that encapsulates a number of those parameters and represents the amount of energy input from the laser source to the feedstock. VED has been traditionally used to inform the quality of the printed part but different values of VED are presented as optimal values for certain material systems. An optimal VED value can be maintained by changing the key process parameters so that various combinations yield a constant value. In this study, an optimal constant VED value is maintained while printing SS316L with variable key processing parameters. Porosity analysis is performed using optical microscopy, as well as X-ray computed tomography, to reveal the volume density and distribution of those pores. Two primary defect categories are identified, namely lack of fusion and porosity induced by balling defects. The findings indicate that, even at optimal VED, variations in process parameters can significantly influence defect type, underscoring the sensitivity of defect formation to the variation of these parameters. Furthermore, a minor change in the build rate, driven by adjustments in process parameters, was found to influence defect categories. These findings emphasize that fine tuning the process parameters and build rate is essential to minimize defects. Finally, fiducial marks have been identified as a source of unintentional porosity defects. These results enable the refinement of process parameters, ultimately optimizing LPBF to achieve enhanced material density and expedite the printing.

Prilling as an Effective Tool for Manufacturing Submicrometric and Nanometric PLGA Particles for Controlled Drug Delivery to Wounds: Stability and Curcumin Release.

This study investigates for the first time the use of the prilling technique in combination with solvent evaporation to produce nano- and submicrometric PLGA particles to deliver properly an active pharmaceutical ingredient. Curcumin (CCM), a hydrophobic compound classified under BCS (Biopharmaceutics Classification System) class IV, was selected as the model drug. Key process parameters, including polymer concentration, solvent type, nozzle size, and surfactant levels, were optimized to obtain stable particles with a narrow size distribution determined by DLS analysis. Particles mean diameter (d50) 316 and 452 nm, depending on drug-loaded cargo as Curcumin-loaded PLGA nanoparticles demonstrated high encapsulation efficiency, assessed via HPLC analysis, stability, and controlled release profiles. In vitro studies revealed a faster release for lower drug loadings (90% release in 6 h) compared to sustained release over 7 days for higher-loaded nanoparticles, attributed to polymer degradation and drug-polymer interactions on the surface of the particles, as confirmed by FTIR analyses. These findings underline the potential of this scalable technique for biomedical applications, offering a versatile platform for designing drug delivery systems with tailored release characteristics.

A Radiation-Based Analytical Model for the Computation of Temperature in the Arc Column of Submerged Arc Additive Manufacturing (SAAM) Process

Abstract Submerged Arc Additive Manufacturing (SAAM) is an advanced Wire Arc-based Additive Manufacturing (WAAM) technique known for its uniform deposition structure, high deposition rate, and superior surface finish. However, it is difficult and expensive to experimentally investigate the arc column in SAAM due to its submerged nature under flux. This paper presents an effective alternative: developing a radiation-based analytical model to predict the complex temperature distribution within the SAAM arc column. It focuses on the radiation heat transfer phenomenon since the temperatures attained inside the arc column are beyond the melting temperature of the material involved, and the presence of granular flux and slag intensifies the effect of the same. The model incorporates key input process parameters like wire diameter, stick-out length, current, voltage, and travel speed alongside design parameters like bead width, penetration depth, and material reinforcement. The double ellipsoidal heat source model is the foundation for generating the temperature profile. The predicted temperature profile resembles the double ellipsoid in other arc welding-based additive manufacturing techniques. The model's predictions showed a deviation of approximately 14% from experimental results, validating its effectiveness. Extensive parametric studies were carried out using the developed model. It was observed that longer stick-out lengths dampened temperature variations, while higher currents confined the affected zone further. Increased travel speed reduces the heating and cooling rate, while voltage behaves the opposite way. This analytical approach offers a cost-effective alternative for optimizing process parameters to achieve desired dimensions and deposition quality.

Numerical Study to Analyze the Influence of Process Parameters on Temperature and Stress Field in Powder Bed Fusion of Ti-6Al-4V.

This paper presents a comprehensive numerical investigation to simulate heat transfer and residual stress formation of Ti-6Al-4V alloy during the Laser Powder Bed Fusion process, using a finite element model (FEM). The FEM was developed with a focus on the effects of key process parameters, including laser scanning velocity, laser power, hatch space, and scanning pattern in single-layer scanning. The model was validated against experimental data, demonstrating good agreement in terms of temperature profiles and melt pool dimensions. The study elucidates the significant impact of process parameters on thermal gradients, melt pool characteristics, and residual stress distribution. An increase in laser velocity, from 600 mm/s to 1500 mm/s, resulted in a smaller melt pool area and faster cooling rate. Similarly, the magnitude of residual stress initially decreased and subsequently increased with increasing laser velocity. Higher laser power led to an increase in melt pool size, maximum temperature, and thermal residual stress. Hatch spacing also exhibited an inverse relationship with thermal gradient and residual stress, as maximum residual stress decreased by about 30% by increasing the hatch space from 25 µm to 75 µm. The laser scanning pattern also influenced the thermal gradient and residual stress distribution after the cooling stage.

Optimizing seawater purification: Ion exchange selective demineralization through single and multi-objective techniques

This study focused on optimizing a selective demineralization process for seawater purification using ion-exchange technology. Experiments were conducted in three semi-batch reactors containing cation, anion, and mixed resins. Key process parameters included temperature (25 °C–50 °C), resin depth (23–82 cm), and pH (2–12). Statistical modeling and optimization were performed using Response Surface Methodology (RSM) with a central composite design, addressing both single and multi-objective criteria. A desirability function was used to assess process performance based on multiple response variables, such as the removal of trace metals (Ca2+, Mg2+, Mn2+, Zn2+, Fe2+, Cu2+, Ba2+, Cd2+), conductivity reduction, and total dissolved solids (TDS) elimination. Ten quadratic regression models were developed to describe the relationships between input parameters and responses, achieving high R2 values (≥0.7) for most responses except Cu2+, Mn2+, and Ba2+. Multi-objective optimization highlighted TDS, conductivity, and the removal of Ca2+, Mn2+, and Mg2+ as critical targets due to their significant impact on water hardness. The optimal conditions (temperature of 43.9 °C, resin depth of 75.45 cm, and pH of 5.9) yielded a composite desirability score of 0.77. Under these conditions, the process achieved over 99% removal efficiency for key cations (Ca2+, Mg2+), significant conductivity reduction, and near-complete TDS elimination. However, Mn2+ removal efficiency reached approximately 85%, likely due to its lower diffusion coefficient and higher hydration enthalpy. The results, particularly from the multicriteria optimization combined with desirability function approaches, highlight the effectiveness of ion-exchange resins in seawater demineralization and offer a robust framework for enhancing process performance.

Regolith-Rich PEEK Composite Bricks: Steps Towards Space-Ready Lunar Construction Materials

This study introduces a novel composite construction material composed of lunar regolith combined with PEEK in dry powder form. The work demonstrates significant advantages over alternative methods, primarily by reducing production power consumption and simplifying the manufacturing process. Building on previous research that explored binder optimization through process simplification and targeting predefined shapes, this work delves deeper into a comparative analysis of high-performance thermoplastics. Among the various options, PEEK demonstrates the most favorable properties. The study investigates key processing parameters and evaluates the effects of vacuum processing and temperature testing on mechanical properties. The research also evaluates the effects of vacuum processing and temperature testing to assess the material’s performance under lunar conditions. Comparative analysis is performed with standard performance of various reinforced and unreinforced concretes and with standard requirements for construction bricks as per ASTM standards. This shows that the composite, with an organic binder content as low as 5 wt%, has great potential. Notably, the improvements achieved through vacuum curing ensure compliance with lunar environmental conditions and alignment with most Earth-based engineering standards. Samples compacted at 7.50 MPa with 10 wt% binder, and tested at room temperature, achieve a compression strength of 16.3 MPa, exceeding that of industrial floor bricks and matching that of building bricks used on Earth. Bending strength (7.4 MPa) aligns with steel fiber-reinforced and high-strength concretes. Vacuum curing further enhances these properties, with an observed increase of +66% in bending strength and +33% in compression strength.

Insights on proton‐conducting ceramic electrochemical cell fabrication

AbstractThis study investigates the key factors influencing sintering behavior and grain growth in (BCZYYb4411)–NiO negatrodes and BCZYYb electrolytes for protonic ceramic electrochemical cells (PCECs). Elastic net machine learning models are applied to a dataset of nearly 200 individual PCEC button cells fabricated over the course of more than 3 years to identify the key processing parameters that significantly affect negatrode shrinkage and electrolyte grain growth. The shrinkage rate of the BCZYYb4411–NiO negatrode is primarily governed by the solid‐state sintering behavior. Higher sintering temperatures, longer dwell times, and smaller NiO particle size are the primary determinants that lead to greater shrinkage. New or lightly‐used setters and more compact negatrodes are also found to increase shrinkage. Electrolyte grain growth is chiefly controlled by the liquid‐phase sintering of the BCZYYb phase. Increased cerium content on the B‐site leads to the largest enhancement in grain size, followed by increasing maximum sintering temperature. We find that the parameters used to tune the spray deposition of the electrolyte layer are also critical, with wetter and more uniform sprays promoting grain enlargement. Finally, we find that the sintering environment (e.g. presence/absence of sintering neighbors or sacrificial powders and the ambient humidity level) also substantially impacts both shrinkage and grain growth. This work comprehensively analyzes data from nearly 200 PCECs without “success bias,” meaning that poor performers and fabrication failures were included in the analysis. By doing so, the study provides valuable insight into the critical factors controlling shrinkage and grain growth in BCZYYb‐based PCECs. The findings offer foundational guidance for processing optimization that could lead to better repeatability, increased yields, and higher performance.

Design and process optimization of a new reaction chamber for microwave synthesis of MOFs materials.

Based on the application demand of metal-organic framework (MOFs) materials in environmental science, energy conversion, biomedicine and other fields, its efficient synthesis method has attracted much attention. Microwave method has become one of the most competitive and potential methods because of its low cost, high efficiency and green environmental protection. However, the traditional microwave assisted synthesis of MOFs materials mostly uses microwave oven as the reaction chamber, or small-scale microwave reactor. There are many problems such as uneven heating, low microwave utilization rate and low one-time synthesis yield. In view of the above problems, the design and process optimization of a new type reaction chamber for microwave synthesis of MOFs materials were studied in this paper. A material synthesis reactor using waveguide as microwave source was designed. The structure model of the reactor was optimized by multi-physics numerical simulation, and better heating uniformity and microwave utilization were obtained. At the same time, the optimization test of key process parameters was designed by orthogonal method, and the optimal process parameter combination of this model for the synthesis of MOFs materials was obtained: microwave power is 200W, irradiation time is 100min, and reagent concentration is 50mM/L. This study will promote the microwave method to achieve more efficient and uniform MOFs material synthesis, which is of great significance for further improving material yield and properties and industrial practical applications.

Assessment on surface integrity in electrochemical grinding of AISI 304.

Electrochemical grinding (ECG) offers advantages such as burr-free and stress-free material removal. Despite its proven potential, limited research has addressed the comprehensive effects of key process parameters on the surface integrity of AISI 304 stainless steel, particularly for applications requiring high-quality finishes, such as medical components. This study bridges this gap by systematically investigating the influence of ECG key parameters including voltage, rotational speed, and electrolyte concentration on main surface integrity parameters including current density, surface roughness, microhardness, and surface texture. Total of 20 experiments were carried out following a Response Surface Methodology (RSM) design, incorporating five levels of variation for the parameters of electrolyte concentration, voltage, and grinding wheel speed. Results revealed that voltage and electrolyte concentration were the dominant factors affecting current density, increasing it by 368% and 241%, respectively, while higher rotational speeds decreased it by 44.5% due to reduced contact time and electrolyte removal. Surface roughness decreased by up to 65% in the perpendicular direction as concentration and voltage increased, but higher voltages led to over-etching, increased the surface roughness. Electrolyte concentration and voltage also reduced surface microhardness by 10-14% through intensified corrosion, while higher wheel speeds increased microhardness due to enhanced mechanical removal. The maximum variation for in-depth microhardness extended up to a depth of 40μm below the surface. Surface texture analysis also revealed more uniform pitting across the surface at higher concentrations, indicating more consistent material dissolution. However, at higher voltages, deep pitting emerged, raising surface roughness.

Investigation of multi-field coupling performance in a binary-mixture fluidized bed reactor for FCC-PDH coupling process: Effects of key process parameters

Investigation of multi-field coupling performance in a binary-mixture fluidized bed reactor for FCC-PDH coupling process: Effects of key process parameters

Pitfalls in Early Bioprocess Development Using Shake Flask Cultivations.

For about 100years, the shake flask has been established for biotechnological cultivations as one of the most important cultivation systems in early process development. Its appeal lies in its simple handling and highly versatile application for a wide range of cell types-from bacteria to mammalian cells. In recent decades, extensive research has been conducted on the shake flask, to not perform processes blindly but to gain a deeper understanding of the various process parameters, phenomena, and their impact on the process. Although the characterization of the shake flask is now well-established in literature, many publications show that this knowledge is often inadequately applied. Therefore, this review provides an overview of the current state of knowledge on various topics related to the shake flask. We first present the key process parameters and their influence on different physical phenomena, such as power input, the largely unknown in-phase/out-of-phase phenomenon, as well as temperature and mass transfer. Then, the most common online monitoring systems that have been established for shake flasks are discussed. Finally, various pitfalls that often arise from inadequate knowledge of handling shake flask cultivations are discussed and guidance on how to avoid them is provided.

From biogas to biomethane: Evaluating the role of microalgae in sustainable energy production – A review

Methane, predominantly derived from fossil resources, is a highly utilised energy source due to its high energy density. However, the rapid consumption of fossil fuels has precipitated anthropogenic climate change and resource depletion, compelling the necessity for a transition towards sustainable and climate-compatible energy sources. This review examines biogas upgrading technologies, encompassing physical, chemical, and biological methods, with a particular focus on photosynthetic CO2 fixation to enhance methane purity and meet biomethane purity standards. Biological processes, in particular those utilising microalgae, demonstrate considerable potential for CO2 sequestration and have the capacity to reduce emissions while simultaneously generating valuable byproducts. The review investigates key process parameters, including pH, liquid-to-gas (L/G) ratio, temperature, and gas retention time (GRT), along with the removal efficiency of CO2. The mass transfer of CO2 and the role of microorganisms are also examined. Furthermore, biological, and chemical/physical upgrading technologies are economically and ecologically compared.

Overview of anodization and silver coating for titanium alloys: Process parameters and biomedical insights

Anodization is a critical electrochemical process for producing titanium oxide layers with varying characteristics, significantly influencing the physicochemical properties, biocompatibility, and performance of bone implants. This study systematically reviews the current state of research on the effects of anodization parameters and silver coatings on the morphology, functional groups, and phase identification of Ti-6Al-4V bone implants. By synthesizing findings from 18 relevant studies selected from 1044 screened articles (2000–2023), this review provides a comprehensive framework for understanding the role of anodization and silver coating in improving implant performance. The review highlights how variations in anodization parameters—such as electrolyte composition, voltage, and duration—significantly impact critical implant properties, including corrosion resistance, antimicrobial efficacy, and biocompatibility. Additionally, silver coatings are underscored for their antimicrobial benefits and ability to address challenges such as bacterial adhesion and biofilm formation. Beyond functional improvements, this review identifies gaps in the literature, such as the limited exploration of process optimization and the environmental implications of implant fabrication, offering actionable insights for future research. The novelty of this article lies in its holistic synthesis of fragmented findings, bridging material science, biomedical functionality, and sustainability. It provides a structured evaluation of key process parameters and their influence on implant performance, emphasizing the need for balanced approaches that integrate clinical effectiveness with environmentally responsible practices. By offering a unified perspective, this review serves as a valuable reference for advancing both research and practical applications in the development of high-performance bone implants.

Process Research of Surface Laser Phase Transformation Hardening for 42CrMo Material

42CrMo is an ultra-high-strength, low-alloy structural steel. To enhance its surface wear resistance and prolong the service life of components, surface strengthening techniques are commonly applied. In this study, a numerical model for the laser phase transformation hardening of 42CrMo was established. The temperature field and metallurgical transformations during the laser phase transformation hardening process were investigated through numerical simulation, and the morphology of the hardened layer after laser surface treatment was predicted. The effects of key process parameters on the temperature field and the characteristics of the hardened layer were identified. The optimal parameters for single-pass laser phase transformation hardening were found to be a laser power of 1200 W, a scanning speed of 20 mm/s, and a spot diameter of 6 mm. The accuracy of the simulation results was validated through laser phase transformation hardening experiments. The results indicate that under these optimal conditions—laser power of 1200 W and a scanning speed of 20 mm/s—the hardening effect is maximized. The surface hardness reaches a maximum of 782 HV0.2, with a cross-sectional hardness peaking at 875 HV0.2, which is three to four times higher than the base material’s hardness, with an average surface hardness of 745 HV0.2.