Search Results (83)

Gear whine noise is governed not only by intentional microgeometry modifications but also by unavoidable pitch (indexing) deviation. This study presents a workflow that couples a tooth-resolved surface scan with a calibrated pitch-deviation table, both imported into a multibody dynamics (MBD) model built in MSC Adams View. Three operating scenarios were evaluated—ideal geometry, measured microgeometry without pitch error, and measured microgeometry with pitch error—at a nominal speed of 1000 r min⁻¹. Time domain analysis shows that integrating the pitch table increases the mean transmission error (TE) by almost an order of magnitude and introduces a distinct 16.66 Hz shaft order tone. When the measured tooth topologies are added, peak-to-peak TE nearly doubles, revealing a non-linear interaction between spacing deviation and local flank shape. Frequency domain results reproduce the expected mesh-frequency side bands, validating the mapping of the pitch table into the solver. The combined method therefore provides a more faithful digital twin for predicting tonal noise and demonstrates why indexing tolerances must be considered alongside profile relief during gear design optimization. Full article

Background/Objectives: Accurate implant impressions are critical for capturing the three-dimensional (3D) spatial positioning of implants. Digital workflows using intraoral scanners (IOSs) and scan bodies offer distinct advantages over conventional elastomeric techniques. However, the geometry of scan bodies may influence the precision and trueness of IOS-acquired data, and optimal design parameters remain undefined. This systematic review aims to evaluate the effects of scan body geometry on the trueness of digital implant impressions captured using IOSs. Methods: A systematic search was conducted across PubMed, Scopus, EMBASE, Web of Science, the Cochrane Library, and Google Scholar up to 25 February 2025. Eligible studies assessed the impact of scan body geometry on the accuracy of implant-level impressions acquired with IOSs. Study quality was assessed using the Quality Assessment Tool for In Vitro Studies of Dental Materials (QUIN). Results: Twenty-eight studies were included, of which twenty-six were in vitro. The included studies, published between 2020 and 2025, demonstrated that variations in macro- and micro-geometries influenced both linear and angular trueness. Cylindrical designs with optimal dimensions generally outperformed cuboidal or spherical forms. Structural modifications, such as rigid bar extensions and surface facets, often improved scan accuracy. Some hybrid or modified designs performed comparably to conventional scan bodies. According to QUIN, 27 studies were moderate quality and one had high quality. Conclusions: Scan body geometry affected the accuracy of intraoral implant digital impressions. Designs featuring rigid extensions or simplified geometries improve trueness and precision. Further standardized clinical studies are needed to define optimal design features and validate current in vitro findings. Full article

The present work intends to assess the impact of trochoidal toolpath rounding radius loop adjustments on surface roughness, nose radius wear, and resultant cutting force during end milling of AISI D3 steel. Twenty experimental trials have been performed utilizing a face-centered central composite design through a response surface approach. Artificial Neural Network (ANN) models were built to forecast outcomes, utilizing four distinct learning algorithms: the Batch Back Propagation Algorithm (BBP), Quick Propagation Algorithm (QP), Incremental Back Propagation Algorithm (IBP), and Levenberg–Marquardt Back Propagation Algorithm (LMBP). The efficacy of these models was evaluated using RMSE, revealing that the LMBP model yielded the lowest RMSE for surface roughness (Ra), nose radius wear, and resultant cutting force, hence demonstrating superior predictive capability within the trained dataset. Additionally, a Genetic Algorithm (GA) was employed to ascertain the optimal machining settings, revealing that the ideal parameters include a cutting speed of 85 m/min, a feed rate of 0.07 mm/tooth, and a rounding radius of 7 mm. Moreover, the detachment of the coating layer resulted in alterations to the tooltip cutting edge on the machined surface as the circular loop distance increased. The initial arc radius fluctuated by 33.82% owing to tooltip defects that alter the edge micro-geometry of machining. The measured and expected values of the surface roughness, resultant cutting force, and nose radius wear exhibited discrepancies of 6.49%, 4.26%, and 4.1%, respectively. The morphologies of the machined surfaces exhibited scratches along with laces, and side flow markings. The back surface of the chip structure appears rough and jagged due to the shearing action. Full article

This paper presents a comprehensive methodology to enable the optimization of an automotive electric axle to reduce noise emissions and improve load distribution. The proposed method consists of the application of two sequential optimization procedures. The first one focuses on the gears’ macro-geometry, based on an objective function that combines the contact ratio, power loss, and center distance. The second one optimizes the micro-geometry of the teeth to reduce the sound pressure generated by tooth impacts. Mechanical stress limits are considered as a constraint in the optimization process. Shafts, joints, and the electric motor are analyzed, taking into account their deformation that influences the dynamics of the entire system. The results of the proposed procedure are verified through experimental measurements and the comparison can be considered successful. Full article

This work introduces a novel application for predicting the macroscopic intrinsic permeability tensor in deformable porous media, using a limited set of $\mu$-CT images of real microgeometries. The primary goal is to develop an efficient, machine learning (ML)-based method that overcomes the limitations of traditional permeability estimation techniques, which often rely on time-consuming experiments or computationally expensive fluid dynamics simulations. The novelty of this work lies in leveraging convolutional neural networks (CNNs) to predict pore-fluid flow behavior under deformation and anisotropic flow conditions. The approach utilizes binarized CT images of porous microstructures to predict the permeability tensor, a crucial parameter in continuum porous media flow modeling. The methodology involves four steps: (1) constructing a dataset of CT images from Bentheim sandstone at varying volumetric strain levels; (2) conducting pore-scale flow simulations using the lattice Boltzmann method (LBM) to obtain permeability data; (3) training the CNN model with processed CT images as inputs and permeability tensors as outputs; and (4) employing techniques like data augmentation to enhance model generalization. Examples demonstrate the CNN’s ability to accurately predict the permeability tensor in connection with the deformation state through the porosity parameter. A source code has been made available as open access. Full article

Background: Immediate post-extraction dental implants are increasingly popular, but ensuring primary stability and managing peri-implant tissues remain challenging. Implant macro-design significantly impacts stability and osseointegration. This study used Cone-beam Computed Tomography (CBCT) to evaluate changes in alveolar bone following immediate placement of two implant designs, System 2P and Dura-Vit 3P, which feature semi-conical microgeometry and apical self-tapping portions for improved stability and bone regeneration. Methods: With a 1:1 allocation ratio, the current investigation was a two-arm parallel group randomized clinical trial. Patients qualified if they required immediate dental replacements with adequate buccal bone support. Two types of implants were placed: System 2P (cylindrical shape) and Dura-Vit 3P (more conical shape, with a particular architecture of threads). Following the intervention, CBCT was performed both immediately (T1) and six months later (T2). Measurements of CBCT horizontal bone level at apical, medial, and bevel height on the palatal/lingual and vestibular sides as well as the buccal vertical gap were the primary results. Complications, implant stability quotient (ISQ), and torque insertion were evaluated. The Mann–Whitney test was used to determine time-based differences within each group, while the Wilcoxon test was used to estimate differences between groups. The impact of baseline marginal gap dimension and gingival biotype was estimated using multiple regressions. Results: Thirty patients were recruited and randomized to treatments, with two lost to follow-up. One System 2P implant failed and two patients of the Dura-Vit 3P group dropped out. At T1, the Dura-Vit 3P group exhibited a lower mean insertion torque and a higher ISQ than the System 2P group. Furthermore, the Dura-Vit 3P group showed lower bone reduction compared to System 2P at horizontal and vertical measurements with significant differences for the vestibular and palatal base and medial level (p-values < 0.05). Regression models indicated a positive effect of thick biotypes on gap filling and dimensional bone reduction. No complications were observed in both groups. Conclusions: The Dura-Vit 3P implant exhibits high primary stability when inserted in post-extraction sites. Furthermore, this kind of implant stimulates higher bone stability on both the palatal and buccal side when compared to the System 2P implant. The present findings support the evidence that the macro-design of the Dura-Vit 3P implant promotes increased primary stability and reduces bone loss. Full article

This article presents the implementation of the Six Sigma methodology in the electro-discharge texturing process of cold mill work rolls. The final surface quality of sheet metal must meet the specific demands of car body part producers, which require a specific surface texture described by surface microgeometry parameters: the average roughness and the peak density. The requirements for the surface microgeometry of sheet metal are mainly related to improving the formability and adhesion of the paint in the body painting process. These microgeometry parameters can be controlled by the texture of work rolls: this texture is transferred onto the sheet metal surface. The electro-discharge texturing process allows for control of the average roughness and peak density according to individual customer specifications. In this study, a model is proposed to predict the average roughness based on the input parameters of the electro-discharge texturing process: current, voltage, and time. Compared to previous models, this model includes more input parameters. The process suitability was analyzed using control charts, capability indices, and Z scores. The modified weighted product method was used to create a purpose function describing the relationships between the input and output quality parameters. Based on the agreement of the target quality characteristics and the calculated values according to the models obtained, an algorithm to control the texturing process of the work rolls was designed. The proposed model was also validated on results published by other authors and demonstrated good agreement. This study should contribute to the philosophy of continuously improving the surface quality of cold-rolled sheet metal. Full article

The study evaluates models produced using fused deposition modeling (FDM) technology in five orientations, fabricated from polycarbonate (PC) material with a FORTUS 360mc printer. The models included simple shapes (planes and cylinders) and complex free-form surfaces. Accuracy was assessed using a GOM Scan 1 scanner and GOM Inspect 2019 software, focusing on 3D deviations and dimensional and geometric deviations (form, position, and orientation, which have not yet been analyzed in similar studies and may limit the usage of the printed elements). Surface roughness was analyzed using a MarSurf XR profilometer, measuring Ra and Rz parameters. All models were characterized by a predominance of negative 3D deviations. The analysis of variance showed no effect of model orientation on the values of linear dimensional deviations and geometric deviations. The largest deviations were negative and associated with the size of the models. The average value of the absolute deviation of linear dimensions associated with the size of the model was 0.30 mm. The average value of the absolute deviation of other linear dimensions was 0.07 mm. The average value of orientation and position deviations for each model varied in the range of 0.15–0.20 mm, and for form deviation 0.16–0.20 mm. One of the models had a higher surface roughness (Ra = 17.2 µm, Rz = 71.3 µm) than the other four models (Ra in the range of 12.7–13.8 µm, Rz in the range of 57.2–61.2 µm). During the research, three distinct surface types were identified on the models. The research indicated the validity of taking surface type into account when analyzing its microgeometry. Full article

Microbubbles, acting as cavitation nuclei, undergo cycles of expansion, contraction, and collapse. This collapse generates shockwaves, alters local shear forces, and increases local temperature. Cavitation causes severe changes in pressure and temperature, resulting in surface erosion. Shockwaves strip material from surfaces, forming pits and cracks. Prolonged cavitation reduces the mechanical strength and fatigue life of materials, potentially leading to failure. Controlling bubble size and generating monodispersed bubbles is crucial for accurately modeling cavitation phenomena. In this work, we generate monodispersed microbubbles with controllable size using a novel and low-cost microfluidic method. We created an innovative T-junction structure that controls the two-phase flow for tiny, monodispersed bubble generation. Monodisperse microbubbles with diameters below one-fifth of the channel width (W = 100 µm) are produced due to the controlled pressure gradient. This microstructure, fabricated by a CNC milling technique, produces 20 μm bubbles without requiring high-resolution equipment and cleanroom environments. Bubble size is controlled with gas and liquid pressure ratio and microgeometry. This microbubble generation method provides a controllable and reproducible way for cavitation research. Full article

Surface microgeometry created by the energy of electric discharges is related to surface wetting behavior. These relationships change depending on the scale of observation. In this work, contact angles correlated with the surface complexity of AA 6060 after electro-discharge machining were analyzed at different observation scales. This research focuses on the methodology of selecting the best scales for observing wetting phenomena on irregular surfaces, as well as indicating the topographic characterization parameters of the surface in relation to the scales. Additionally, the geometric features of the surface that determine the contact angle were identified. In this study, the surfaces of an aluminum alloy are rendered using focus variation 3D microscopy and described by standardized ISO, area-scale, and length-scale parameters. The research also confirms that it is possible to design surface wettability, including its hydrophilicity and hydrophobicity, using electrical discharge machining parameters. The static and dynamic behavior of liquids on surfaces relevant to contact mechanics was also determined. Full article

This investigation sought to characterize the combined influence of cutting-edge microgeometry and cooling/lubricating strategies on process thermo-mechanics and the resultant surface integrity in orthogonal machining of the Ti-6Al-4V alloy. Reverse waterfall cutting inserts were prepared with varying cutting-edge geometries, and machining experiments were conducted under cryogenic cooling with liquid nitrogen (LN₂), minimum quantity lubrication (MQL), and dry machining conditions, using constant machining parameters. The induced surface integrity was characterized in terms of the developed cutting forces and through-thickness microhardness, grain morphology, dislocation generation, and residual stress formation. The experimental results revealed that the governing process physics are strongly influenced by variation in the implemented machining parameters. As a greater proportion of the cutting edge is distributed on the flank face, competing mechanical ploughing and thermal-based frictional effects both become more pronounced. Utilization of advanced cooling strategies to control cutting interface thermal gradients thus provides a processing route to generate tailored microstructures and surface integrity during the machining of this alloy. Full article

The efficiency of bevel and hypoid gears is, alongside load capacity, one of their most important design criteria. To consider the efficiency of bevel and hypoid gears during the development and design process, validated calculation methods based on experimental investigations are necessary. However, the isolated experimental investigation of the load-dependent power losses of bevel and hypoid gears has not been adequately investigated, as most of the experimental investigations consider the complete gearbox. This paper presents a test rig that allows for the experimental investigation of the efficiency of bevel and hypoid gears with a measurement uncertainty of the efficiency of $∆\eta \le \pm 0.08\%$ according to the Guide to the Expression of Uncertainty in Measurement (GUM). Using the developed test rig, experimental investigations on the efficiency behavior of bevel and hypoid gears regarding the influence of the axial offset, driving direction, and microgeometry are carried out for different operating points varying in circumferential speed and load. This paper discusses the methodology and the first experimental results of a study on the efficiency of bevel and hypoid gears in detail. Full article

The selection of the right tool path trajectory and the corresponding machining parameters for end milling is a challenge in mold and die industries. Subsequently, the selection of appropriate tool path parameters can reduce overall machining time, improve the surface finish of the workpiece, extend tool life, reduce overall cost, and improve productivity. This work aims to establish the performance of end milling process parameters and the impact of trochoidal toolpath parameters on the surface finish of AISI D3 steel. It especially focuses on the effect of the tool tip nose radius deviation on the surface quality using precision measurement techniques. The experimental design was carried out in a systematic manner using a face-centered central composite design (FCCD) within the framework of response surface methodology (RSM). Twenty different experiment trials were conducted by changing the independent variables, such as cutting speed, feed rate, and trochoidal pitch distance. The main effects and the interactions of these parameters were determined using analysis of variance (ANOVA). The optimal conditions were identified using a multiple objective optimization method based on desirability function analysis (DFA). The developed empirical models showed statistical significance with the best process parameters, which include a feed rate of 0.05 m/tooth, a trochoidal pitch distance of 1.8 mm, and a cutting speed of 78 m/min. Further, as the trochoidal pitch distance increased, variations in the tool tip cutting edge were observed on the machined surface due to peeling off of the coating layer. The flaws on the tool tip, which alter the edge micro-geometry after machining, resulted in up to 33.83% variation in the initial nose radius. Deviations of 4.25% and 5.31% were noted between actual and predicted values of surface roughness and the nose radius, respectively. Full article

The paper investigates the feasibility of plasma electrolytic treatment (PET) of 90CrSi tool steel to enhance hardness and wear resistance. The influence of electrophysical parameters of PET (polarity of the active electrode, chemical-thermal treatment, and polishing modes) on the composition, structure, morphology, and tribological properties of the surface was studied. Tribological tests were carried out under dry friction conditions according to the shaft-bushing scheme with fixation of the friction coefficient and temperature in the friction contact zone, measurements of surface microgeometry parameters, morphological analysis of friction tracks, and weight wear. The formation of a surface hardened to 1110–1120 HV due to the formation of quenched martensite is shown. Features of nitrogen diffusion during anodic PET and cathodic PET were revealed, and diffusion coefficients were calculated. The wear resistance of the surface of 90CrSi steel increased by 5–9 times after anodic PET followed by polishing, by 16 times after cathodic PET, and up to 32 times after subsequent polishing. It is shown that in all cases, the violation of frictional bonds occurs through the plastic displacement of the material, and the wear mechanism is fatigue wear during dry friction and plastic contact. Full article

Additive manufacturing (AM) techniques are among the fastest-growing technologies for producing even the most geometrically complex models. Unfortunately, the lack of development of metrology guidelines for these methods, related to dimensional and geometry accuracy and surface roughness, significantly limits the commercialization of finished products manufactured using these methods. This paper aims to evaluate the macro- and micro-geometry of models manufactured using the PolyJet method from three types of photopolymer resins: Digital ABS Plus, RGD 720, and Vero Clear. For this purpose, test parts were designed and then manufactured on an Object 350 Connex3 3D printer. The Atos II Triple Scan optical system and the InfiniteFocusG4 microscope were used to evaluate macro- and micro-geometry, respectively. For both systems, measurement procedures were developed to obtain statistical results for evaluating geometric accuracy and surface roughness parameters. In the case of macro-geometry, for Digital ABS Plus and Vero Clear materials, 50% of the central deviations (between first quartile Q1 and third quartile Q3) lie within the range (−0.06, 0.03 mm) and for RGD 720 material within the range (−0.08, 0.01 mm). For micro-geometry, the arithmetic mean height (Sa) values for the Digital ABS Plus and Vero Clear samples were approximately 1.6 and 2.0 µm, respectively, while for RGD 720, it was 15.9 µm. The total roughness height expressed by reduced peak height (Spk) + core height (Sk) + reduced dale depth (Svk) for the Digital ABS Plus and Vero Clear samples was approximately 9.1 and 10.5 µm, respectively, while for the RGD 720, it was 101.9 µm. Full article