Minimum Surface Roughness Research Articles

Prediction and Optimization of Surface Roughness and Cutting Forces in Turning Process Using ANN, SHAP Analysis, and Hybrid MCDM Method

As manufacturing technologies advance, the integration of artificial neural networks in machining high-hardness materials and optimization of multi-objective parameters is becoming increasingly prevalent. By employing modeling and optimization strategies during the machining of such materials, manufacturers can improve surface roughness and tool life while minimizing cutting time, tool vibrations, and cutting forces. In this paper, the aim was to analyze the impact of input parameters (cutting speed, feed rate, depth of cut, and insert radius) on surface roughness and cutting forces during the machining of 90MnCrV7 using feed-forward neural network models and SHAP analysis. Afterward, multi-criteria optimization was applied to determine the optimal parameter levels to achieve minimum surface roughness and cutting forces using the modified PSI-TOPSIS method. According to the SHAP analysis, the insert radius has the most significant impact on the surface roughness and passive force, while in the multi-criteria analysis, according to ANOVA results, the insert radius has the most significant impact on all considered outputs. The results show that an insert radius of 0.8 mm, a cutting speed of 260 m/min, a feed rate of 0.08 mm, and a depth of cut of 0.5 mm are the optimal combination of input parameters.

Multi-Objective Optimization of the Surface Grinding Process for Heat-Treated Steel

This paper effectively integrates Taguchi, Response Surface Methodology (RSM), and Genetic Algorithm (GA) approaches for both single and multi-objective optimization, delivering low-cost, high-effectiveness solutions for grinding. It examines the effects of three factors—depth of cut in coarse grinding, depth of cut in fine grinding, and the number of spark-outs—on three objectives: surface roughness, grinding time, and the deviation between the desired and actual grinding depth for SKD61 steel. Through in-depth analysis, the paper describes the impact of these factors and their interactions with the responses. It also proposes the optimal parameter setup for each objective. The optimal grinding time is achieved at 950 seconds with a coarse grinding depth of 0.007 mm, fine grinding depth of 0.004 mm, and zero spark-out. The minimal deviation and surface roughness were obtained at 0 mm and 0.144 µm, respectively, using the optimal setup of a coarse grinding depth of 0.004 mm, fine grinding depth of 0.001 mm, and 10 spark-outs. By applying GA, the paper provides a Pareto solution set, offering multiple combinations of optimal factors for minimizing grinding time, deviation, and surface roughness. These solutions serve as useful references for users seeking the best trade-offs in multi-objective scenarios. This paper contributes to improving customer satisfaction by enhancing the quality and efficiency of the machining process while reducing production costs for grinding machines. Its methodology can also be applied to other optimization fields.

Experimental study of NiTi alloy cardiovascular stent formed via SLM

Selective laser melting (SLM) has garnered significant attention in the manufacturing of cardiovascular stents due to its potential for fabricating customized stents with intricate geometries that meet clinical requirements. This study aims to optimize the SLM parameters for NiTi stents to achieve minimal porosity and surface roughness, and investigate the biocompatibility and compression tests of SLMed stents. Firstly, the single-factor experiments of laser power, scanning speed and hatch spacing are conducted, respectively. Subsequently, a Box-Benhnken experimental was employed to establish regression prediction models for porosity and surface roughness using response surface methodology (RSM). The results show that scanning speed is the most influential factor on porosity, while laser power significantly affects surface roughness. The optimized parameter combination with minimum porosity of 0.165% and surface roughness of 6.17 μm as follows: laser power of 156W, scanning speed of 712mm/s, and hatch spacing of 0.9mm. The relative errors of them are 0.19% and 0.8%, respectively, indicating that the regression model possesses good prediction ability. Additionally, the corrosion rate and nickel ion release gradually increase with the immersion time, reaching the highest corrosion rate of 2.46g/m² and nickel ion release of 1.08μg after 42 days. Besides, the SLMed stent demonstrated good recovery ability in the compression test. The findings promote the utilization of SLM in the manufacturing of NiTi cardiovascular stents for medical implant applications.

Machining of Cf/SiC composite with indigenously developed nano green cutting fluid: Machined surface fibre morphology

The Carbon fibre reinforced Silicon Carbide (Cf/Sic) composites are widely used in different industries such as automotive, aerospace, etc. The Cf/SiC is indigenous developed and detail of the fabrication procedure is presented. The nano fluid, namely Graphene Oxide Organo Boron (GOOB) is developed indigenously for using as the cutting fluid. This nano fluid is mixed in green cutting fluid (GCF) in different proportions and the concentration is optimized. The nano fluid is characterized by advanced techniques for the confirmation. To reduce the surface roughness on the fabricated Cf/SiC, end milling operation is carried out with different machining environments such as dry, flood cooling with cutting fluid and nano fluid and minimum quantity cutting fluid with nano fluid. The machining operations are carried out by varying different input parameters, namely, cutting speed, feed rate, and depth of cut. The results indicated that the minimum surface roughness of 1.845 μm is obtained when 0.5 % GOOB with GCF is used. This work would benefit the researchers exploring the preparation and interaction mechanism of the indigenously developed nano green cutting fluid for machining Cf/SiC-based ceramic matrix composites.

Overall improvement of macro electrochemical jet milling by utilizing a novel cathode tool with an ultra narrow inter-electrode gap

Electrochemical jet milling (EJM) offers significant benefits for producing workpieces, showcasing various advantages in terms of quality and design flexibility. However, macro-scale EJM currently encounters limitations regarding machining efficiency and surface precision. A critical determinant of these aspects is the inter-electrode gap (IEG), with its optimization presenting an opportunity to enhance both precision and efficiency. Reducing the IEG is particularly desirable as it promises considerable improvements in machining efficiency and surface quality. Nonetheless, achieving a narrower IEG is challenging due to the risk of sparking from excessively high current densities at the cathode tool tips. To address this issue, this study introduces an innovative cathode tool design tailored to exploit the characteristics of electric in EJM. This design strategically removes the energy concentration area. As a result, this advancement allows for an ultra-narrow IEG of 0.05 mm, setting a new benchmark for the narrowest IEG achievable in macro EJM. Employing this novel cathode tool leads to a substantial leap in machining performance at an IEG of 0.05mm. When compared with the conventional machining gap of 0.2mm, the refined 0.05mm IEG not only boosts the material removal rate by an impressive 107% but also enhances surface quality. Specifically, the experimental results showed that the minimum surface roughness produced by the RD cathode tool was reduced by nearly 86.2% than that of the surface produced by the standard cathode tool. Moreover, the overcut area was reduced by nearly 60.1%, and stray corrosion was eliminated.

Assessment of physio-mechanical characteristics of ABS/PETG blended parts fabricated by material extrusion 3D printing

Abstract This study examines the effect of blending acrylonitrile butadiene styrene (ABS) and polyethylene terephthalate glycol (PETG) in various weight percentage ratios (ABS/PETG: 100/0, 90/10, 80/20, 70/30, 60/40, 50/50, 40/60) on the physio-mechanical properties of 3D-printed parts. The result showed that the 3D-printed PETG sample exhibited the highest density of 1.12 ± 0.05 g cm−3 along with the 40ABS60PETG blend displaying similar density value. However, the 40ABS60PETG sample also demonstrated the highest shrinkage, attributed to differences in thermal expansion and cooling rates between ABS and PETG. Moreover, the surface roughness value of the blended samples varied between 8.04 μm–and 9.78 μm, with the 40ABS60PETG sample having a minimal surface roughness of 8.04 ± 0.60 μm. Regarding mechanical performance, the 40ABS60PETG blend showed a notable improvement in flexural modulus, with increases of 6.45% and 60% compared to neat ABS and PETG, respectively. Compression testing revealed that ABS-dominant blends possess higher compression modulus and maximum compressive stress, indicating superior resistance to deformation and enhanced load-bearing capacity. This study highlights the importance of blend ratios to optimize performance, especially for applications requiring a balance between stiffness and flexibility. The results suggest that controlling the ABS/PETG ratio and carefully managing printing parameters can optimize the mechanical and dimensional stability of 3D-printed parts.

Synthesis of nickel and copper metal complexes for blending in PVC to enhance UV absorption and stability

Three new copper and nickel complexes were synthesized using N-alkylated imidazole as a ligand, characterized by NMR, FTIR, and UV analysis, and subsequently assessed as UV absorbers to enhance the stability of polyvinyl chloride (PVC). PVC is widely used due to its cost-effectiveness, resistance to alkali and acid corrosion, and ease of molding. However, its susceptibility to degradation under prolonged UV exposure poses a significant challenge to its durability. To address this, the study focuses on the effect of these synthesized complexes on the stabilization of PVC films subjected to 500 h of UV irradiation at 25 °C. Analytical techniques, including IR spectroscopy, UV-visible spectroscopy, weight loss analysis, and SEM with EDX, were employed to evaluate the degradation of the PVC films. The results demonstrated that the C1 complex provided superior protection against UV-induced damage, significantly reducing decomposition, and minimizing surface roughness, cracks, and overall deterioration compared to C2 and C3 complexes, and a blank sample. C1 exhibited the highest efficiency, with a 91% reduction in degradation. Response Surface Methodology (RSM) was utilized to optimize the experimental results, further confirming the outstanding performance of C1 in stabilizing PVC against UV exposure.

Effective Dual Cation Release in Quasi‐2D Perovskites for Ultrafast UV Light‐Powered Imaging

AbstractRuddlesden‐Popper quasi‐2D perovskites represent robust candidates for optoelectronic applications, achieving a delicate balance between outstanding photoresponse and stability. However, mitigating the internal defects in polycrystalline films remains challenging, and their optoelectronic performances still lag behind that of their 3D counterparts. This work highlights the profound impact of defect passivation at the buried interface and grain boundaries through a dual‐cation‐release strategy. Cations released from the pre‐deposited inorganic iodide buffer layer effectively repair deep‐level defects by inducing low‐dimensional phase reconstruction and interacting with undercoordinated ions. The resulting quasi‐2D perovskite polycrystalline films feature large grain size (>2 µm) and minimum surface roughness, along with alleviated out‐of‐plane residual tensile strain, which is beneficial for inhibiting the initiation and propagation of cracks. The fabricated photodetector demonstrates drastically improved self‐powered photoresponse capability, with maximum responsivity up to 0.41 A W−1 at 430 nm and an ultrafast response speed of 161 ns / 1.91 µs. Moreover, this strategy is compatible with the photolithography‐assisted hydrophobic‐hydrophilic patterning process for fabricating pixelated photodetector arrays, which enables high‐sensitivity imaging. This study presents a feasible defect passivation approach in quasi‐2D perovskites, thereby providing insights into the fabrication of high‐performance optoelectronic devices.

A universal reverse‐cool annealing strategy makes two‐dimensional Ruddlesden‐popper perovskite solar cells stable and highly efficient with Voc exceeding 1.2 V

AbstractTwo‐dimensional Ruddlesden‐Popper (2D RP) layered metal‐halide perovskites have garnered increasing attention due to their favorable optoelectronic properties and enhanced stability in comparison to their three‐dimensional counterparts. Nevertheless, precise control over the crystal orientation of 2D RP perovskite films remains challenging, primarily due to the intricacies associated with the solvent evaporation process. In this study, we introduce a novel approach known as reverse‐cool annealing (RCA) for the fabrication of 2D RP perovskite films. This method involves a sequential annealing process at high and low temperatures for wet perovskite films. The resulting RCA‐based perovskite films show the smallest root‐mean‐square value of 23.1 nm, indicating a minimal surface roughness and a notably compact and smooth surface morphology. The low defect density in these 2D RP perovskite films with exceptional crystallinity suppresses non‐radiative recombination, leading to a minimal non‐radiative open‐circuit voltage loss of 149 mV. Moreover, the average charge lifetime in these films is extended to 56.3 ns, thanks to their preferential growth along the out‐of‐plane direction. Consequently, the leading 2D RP perovskite solar cell achieves an impressive power conversion efficiency of 17.8% and an open‐circuit voltage of 1.21 V. Additionally, the stability of the 2D RP perovskite solar cell, even without encapsulation, exhibits substantial improvement, retaining 97.4% of its initial efficiency after 1000 hours under a nitrogen environment. The RCA strategy presents a promising avenue for advancing the commercial prospects of 2D RP perovskite solar cells.image

Advancing optical transparency in 3D‐printed PLA parts using chemical post‐processing

AbstractFused filament fabrication (FFF) is an increasingly popular three‐dimensional (3D) printing technology known for its ability to produce complex 3D models at a low‐cost using polymer materials. Despite its advantages, the poor surface finish and high layer resolution in FFF‐printed parts have hindered its wider adoption, particularly for applications requiring high transparency. Thus, the current study investigates the transparency evaluation of chemically post‐processed 3D‐printed transparent polylactic acid (PLA) parts, focusing on enhancing optical transparency. Fused Filament Fabrication was employed to produce transparent parts made from PLA filament, which were subsequently treated at various time settings using various solvents, including tetrahydrofuran (THF), chloroform or trichloromethane (TCM), and ethyl acetate (EA). This study examines the impact of chemical post‐processing on the surface roughness, transparency, mechanical properties, and dimensional accuracy of solvent treated parts. It has been found that the THF solvent with 40 s of immersion time resulted in a maximum transmittance of 74.66% and minimum surface roughness of 1.777 μm. Based on this finding a case study was also conducted to apply the findings of the current investigation to a practical application. The findings highlight the potential of chemical‐based post‐processing techniques to improve the optical properties of 3D printed PLA, offering a promising approach for applications in optics, medical devices, and consumer goods requiring transparent components.Highlights Effect of chemical post‐processing on 3D‐printed PLA parts was investigated. Tetrahydrofuran, chloroform, and ethyl acetate were used as solvents. Surface roughness, transparency, hardness, and dimensional accuracy were analyzed. Reported a maximum transmittance of 74.66% and minimum surface roughness of 1.777 μm.

Effects of Finishing on Surface Roughness of Four Different Glass-Ionomer Cements and One Alkasite: In Vitro Investigation over Time Using Aging Simulation.

In 2017, Europe implemented a ban on amalgam restorations for children aged <15 years and for pregnant/breastfeeding women, highlighting the need for alternative filling materials exhibiting less surface roughness and enhanced longevity. This in vitro study aimed to examine the surface roughness variations of five amalgam-replacement materials across three time points and using six finishing methods: (1) no finishing (control), (2) Arkansas burs, (3) diamond burs, (4) tungsten carbide burs, (5) SofLex discs in descending grit size, and (6) coarse SofLex discs combined with silicone polishing. We prepared 960 samples. Each material group, i.e., Cention Forte (CNF), DeltaFil (DLF), Ketac Universal (KTU), IonoStar Molar (ISM), and Equia Forte HT (EQF), comprised 60 samples (n = 10 per finishing method) created using standardized 3D-printed metal molds. Surface roughness (Sa) was measured immediately after finishing, after 30 days of storage in distilled water, and after thermocycling (5000 cycles) using a non-contact profilometer. The results indicate that conventional and hybrid glass-ionomer cements have smoother surfaces than high-viscosity GICs. The DLF and CNF groups exhibited stable outcomes. These findings underscore the importance of selecting appropriate finishing methods based on the restorative material to minimize surface roughness.

Research on a novel non-uniform and asymmetric ultrasonic vibration system

Abstract A new type of non-uniform and asymmetric ultrasonic vibration system (UVS) is proposed and applied to the turning process. The research results show that the design theory of the non-uniform and non-symmetric UVS is accurate and reliable. The theoretical design frequency and modal simulation frequency error of ultrasonic vibration turning system is only 2.5%. The designed non-uniform and non-symmetric UVS has excellent vibration performance and stability, and the established simulation model can predict surface microtexture accurately. The vibration mode output by the non-uniform and non-symmetric UVS is longitudinal-bending vibration, and the actual vibration performance is excellent. Compared with conventional cutting, the addition of longitudinal-bending ultrasonic vibration under the same conditions can give the machined surface a microscopic textured structure, reduce surface roughness and water contact angle, and improve surface wettability. The minimum surface roughness obtained in the experiment is 1.005 μm. The orthogonal experiment results show that there is a correlation between the machining parameters, surface micro-structure parameters, surface wettability, and surface roughness.

Parametric analysis of electrical discharge machining on AA6061 with a WC–Cu composite electrode

The AA6061 aluminium alloy surface characteristics presented in this study were obtained after it was machined using die sinking electro discharge machining (EDM) with a composite electrode developed through powder metallurgy. Machining was performed using negative polarity. In order to obtain optimum material removal rate (MRR) and surface roughness (SR), the research has been carried out, and EDM parameters like voltage, current and pulse on time were optimized using the response surface methodology that integrates the central composite design. The parameter interaction effects on EDM machined surface characteristics were studied with the aid of ANOVA. It was determined from model that the regression for MRR and SR were 98.6% and 98.3% respectively, means empirical model is considered sufficient. It was observed that increased MRR and SR were observed in the condition of increased current, but MRR and SR decreased at increased voltage and pulse on time. This could be due to strengthened ionization temperature that increased MRR with acceptable SR. The microstructure of the machine was assessed using microscopic evaluation. The increased current contributed to the formation of a recast layer and debris which hinders the machining process and reduces MRR. The experimental results show that the maximum MRR of 0.087 mg/min and minimum SR of 1.893 µm were achieved. Additionally, the use of WC–Cu composite electrodes led to an increase in hardness from 65 HV to 78 HV in the machined region. It is concluded that WC–Cu composite electrodes typically result in higher hardness, improved MRR and better SR for the AA6061 alloy compared to conventional Cu electrodes.

Enhancing two-dimensional growth of high-temperature AlN buffer to improve the quality of GaN on Si grown by ex situ two-step method

GaN epitaxial films were grown on Si substrates by ex situ two-step method combining the technologies of pulsed laser deposition (PLD) and metal organic chemical vapor deposition (MOCVD). The N/Al ratio of high-temperature AlN (HT-AlN) buffer layer was optimized, and its influence on the HT-AlN growth mode as well as the quality of GaN epitaxial films was investigated. When the N/Al ratio was 500, the two-dimensional growth of HT-AlN was greatly enhanced, and it obtained a coalesced and smooth surface with the minimum RMS surface roughness as 1.63 nm. The as-grown GaN epitaxial film had the best crystalline quality with the minimum full-width at half maximums of GaN(0002) and GaN(10 1¯ 2) as 0.14° and 0.22°, respectively. Owing to the high energy of PLD, the ex situ low-temperature AlN template had an abrupt Si/AlN interface and flat surface, which was of significance to improve the quality of HT-AlN buffer and GaN film.

Removal-Free and Multicellular Suspension Bath-Based 3D Bioprinting.

Suspension bath-based 3D bioprinting (SUB3BP) is effective in creating engineered vascular structures. The transfer of oxygen and nutrients via engineered vascular networks is necessary for tissue or organ survival and integration following transplantation. Existing SUB3BP techniques face challenges in fabricating hierarchical structures with multicellular organization, including issues related to suspension bath removal, restricted material choices, and low accuracy. A next-generation SUB3BP technique that is removal-free and multicellular is presented. A simple, storable, stable, and scalable starch hydrogel design leverages the diverse spectrum of hydrogels available for use in SUB3BP. Starch granules (8.1µm) create vascular structures with minimal surface roughness (2.5µm) that simulate more natural vessel walls compared to prior research. The development of cells and organoids, as well as the bioprinting of multicellular skin models with vasculature, demonstrates that starch suspension baths eliminate the removal process and have the potential for fabricating artificial tissue with a hierarchical structure and multicellular distribution.

Investigation of Titanium Nitride as an Effective Interphase for Carbon-Fiber-Reinforced Silicon Carbide Ceramic Matrix Composites.

Ceramic matrix composites (CMCs) have played a significant role in increasing the efficiency of gas turbine engines. CMCs combine the high temperature resistance of ceramics with the high mechanical strength of ceramic fibers into a single unit. Interphase layers are a crucial component in CMCs, as they prevent ceramic fibers from oxidation and introduce strengthening mechanisms into the composite. Hexagonal boron nitride and pyrolytic carbon are the most commonly used interphase layers in the aerospace industry. Other than that, very few materials have been evaluated as interphase layers. In this study, we explore the possibilities of using titanium nitride as an interphase layer in single-tow CMCs (mini composite) representative of a unidirectional composite at a smaller scale. T-300 carbon fibers were coated with TiN by atmospheric pressure chemical vapor infiltration using TiCl4, N2, and H2. The deposition temperature, precursor flow rate ratio, total precursor flow rate, and deposition time were optimized to obtain high-quality coatings. The best coating was produced at 800 °C, 4:1 H2 [TiCl4]/N2 ratio, 125 standard cubic centimeters per minute (N2 + H2 [TiCl4]) total flow precursor flow rate, and 2 h of deposition time. At these conditions, the coatings displayed good fiber coverage, good fiber adhesion, minimum fiber linkage, and minimum surface roughness. There was minimum fiber degradation after TiN coating, with a retention of 95% of the initial Young's modulus and 26% of the ultimate tensile strength of the carbon fiber. Adding the TiN interphase coating to the Cf/SiC CMC increased the ultimate tensile strength of the composite by 1122% and Young's modulus by 150%.

Amorphous In–Al–Sn–O Thin Film Transistors and Their Application in Optoelectronic Artificial Synapses

AbstractIn‐Al‐Sn‐O (IATO) is a very promising novel amorphous oxide as the active layer of thin film transistors (TFTs). Herein, IATO TFTs are first fabricated with the effects of annealing on IATO films and TFTs being studied. The IATO films possessed amorphous structure, flat surface morphology, high visible light transmittance, and wide optical bandgap ≈4.20 eV before and after annealing even at 400 °C. The minimal surface roughness and internal defects are obtained for the 300 °C annealed IATO film. Correspondingly, the 300 °C annealed TFTs demonstrated the best overall performance including high saturation mobility (8.55 ± 0.62 cm2 V−1 s−1), low subthreshold swing (0.40 ± 0.07 V dec−1), ideal on/off current ratio (1.25 ± 0.09 × 108), and negligible hysteresis (0.23 ± 0.03 V) values. The 300 °C annealed TFTs are then applied in optoelectronic artificial synapses and exhibit typical synaptic properties, including excitatory postsynaptic current, paired‐pulse facilitation, and short‐term plasticity to long‐term plasticity conversion in response to light stimulation. The international Morse code and repetitive learning‐forgetting behavior of the human brain are also successfully simulated. In particular, an emotion‐memory efficiency model is proposed and the emotion effect on human memory efficiency is successfully imitated via the regulation of gate voltage.

Experimental Study and Random Forest Machine Learning of Surface Roughness for a Typical Laser Powder Bed Fusion Al Alloy

Surface quality represents a critical challenge in additive manufacturing (AM), with surface roughness serving as a key parameter that influences this aspect. In the aerospace industry, the surface roughness of the aviation components is a very important parameter. In this study, a typical Al alloy, AlSi10Mg, was selected to study its surface roughness when using Laser Powder Bed Fusion (LPBF). Two Random Forest (RF) models were established to predict the upper surface roughness of printed samples based on laser power, laser scanning speed, and hatch distance. Through the study, it is found that a two-dimensional (2D) RF model is successful in predicting surface roughness values based on experimental data. The best and minimum surface roughness is 2.98 μm, which is the minimum known without remelting. More than two-thirds of the samples had a surface roughness of less than 7.7 μm. The maximum surface roughness is 11.28 μm. And the coefficient of determination (R2) of the model was 0.9, also suggesting that the surface roughness of 3D-printed Al alloys can be predicted using ML approaches such as the RF model. This study helps to understand the relationship between printing parameters and surface roughness and helps print components with better surface quality.

Microcrystalline and nanocrystalline structure of diamond films grown by MPCVD with nitrogen additions: Study of transitional synthesis conditions

This research explores the complex influence of nitrogen concentration and substrate temperature on the resultant properties of polycrystalline diamond (PCD) films grown by microwave plasma chemical vapor deposition (CVD). In particular, we investigated the growth parameters to find the exact conditions for changing the morphology of the resulting film from microcrystalline (MCD) to nanocrystalline (NCD). A series of 2 µm-thick polycrystalline diamond films was grown on Si substrates in methane-hydrogen–nitrogen gas mixtures with varied: (i) nitrogen concentration (0–2 %) and (ii) substrate temperature (700–1050 °C). Comprehensive characterization techniques, including scanning electron microscopy (SEM), micro-Raman spectroscopy, and X-ray diffraction, were employed to assess the morphological, structural, and spectroscopic properties of the films. The study reveals that even minor additions of nitrogen significantly modulate secondary nucleation, impacting both film morphology and phase composition. Furthermore, substrate temperature emerges as another critical parameter, influencing the growth kinetics and crystallite size. The comparison of the characteristics of grown PCD films allowed us to find conditions for the formation of NCD films with minimal surface roughness and maximal growth rate: nitrogen concentration [N2] ≈ 0.2–0.5 % and temperature T ≈ 850–900 °C. These findings can be used to optimize the CVD synthesis parameters of PCD films for applications as protective or friction-reducing layers, as well as for superhard cutting tools and optical devices.

Development of ANN model for predicting mechanical properties of 3D printed PEEK polymer using FDM and optimization of process parameters for better mechanical properties

Additive manufacturing (AM) has evolved from a proven technology to a rapid prototyping tool with great potential. This technology is widely used in many industries such as automotive, aerospace, and medical; fused deposition modeling (FDM) is a popular 3D printing technique for producing PEEK (polyether ether ketone) parts, including implant prosthetic teeth. In this study, artificial neural network (ANN) modeling, parametric optimization, and experimental examination of PEEK 3D printing were conducted to enhance 3D printing processes. In this study, four critical process factors (infill density, layer height, printing speed, and infill pattern) influence the surface roughness, mechanical strength, and elastic modulus of the printed samples. Utilizing a 4–12–3 network design, this study demonstrates that an ANN model with an average error of less than 5% is optimal for all three responses. Furthermore, the study employed a teaching and learning based optimization algorithm (TLBO) and a non-dominated sorting genetic algorithm (NSGA) to optimize the printing process to obtain improved mechanical properties. The findings highlight TLBO’s ability to minimize surface roughness to 6.01 μm and NSGA’s capability to maximize the elastic modulus to 1253.35 MPa and ultimate tensile strength to 65.55 MPa. Microstructural studies supported the results obtained through parametric analysis and optimization.