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The push-type rotary steerable core bearing has high load capacity and high precision, and has been widely used in oil and gas drilling field. Its service life is difficult to predict due to various complex working conditions. Based on the finite element method, this paper establishes a three-dimensional rotating guide mandrel model to calculate and analyze the mechanical simulation of the guide mandrel under different working conditions, and establishes the corresponding life prediction model to predict its life. The results show that reducing the torque and speed in the range of drilling requirements is conducive to improving the overall life of the spindle, and the life matrix and life distribution are consistent with the characteristics of S-N curve, which is consistent with the characteristics of high cyclic stress of the spindle. The research results can be used to reliably predict the life of the push-type rotary steering mandrel and simulate its working state with high precision. This data is critical for reliability analysis and design optimization.

In a vertical impact crusher, material particles undergo multiple impact collisions and eventually break due to accumulated damage. In order to further study the crushing mechanism of the crusher, a cumulative damage model of material particles under re-peated impact was established. Firstly, a crushing model is established based on the specific fracture energy, reflecting material particles' cumulative damage and crushing process. Then, the simulation model of the crushing system of the vertical shaft impact crusher is established. And by simulating the crushing process of limestone particles in a crusher, it reveals that the crushing of particles is essentially due to the crushing that occurs as a result of multiple cumulative impacts. Next, the simulation model is used to simulate and analyze the rotor's power and particle size distribution of crushed products of limestone, iron ore, and copper ore during crushing. The reliability of the simulation model is experimentally validated. Finally, the simulation analyzed the in-fluence of the diameter and speed of the crusher rotor, as well as the mixed feeding of various materials, on the rotor power and material crushing effect. The results show that the particle size distribution curves of three types of crushed products, including limestone, have a high degree of agreement between simulation and experiment. Fur-thermore, the simulation values of rotor power and specific power consumption fit well with the experimental values, verifying the reliability of the simulation model. As the rotor diameter and rotor speed increase, the rotor power and sand production rate gradually increase. And the increase in rotor power is much greater than the increase in sand production rate. When the feed is a mixture of multiple materials, the rotor power increases approximately linearly with the increase of the proportion of high hardness materials in the feed, while the yield of fine particles in the crushed product decreases with the increase of the proportion of high hardness materials in the feed.

The influence of the casting method on the microstructures of Al-Cu-Li-Mg-Zr-Sc was examined. The techniques include mold casting, twin-roll casting, and melt spinning. Estimated solidification rates up to 107 K·s−1 produce dendritic solidification with eutectic cells ranging from 500 nm to 50 μm, decorated by primary phase particles with thicknesses from 200 nm to 3 μm. Exceeding this solidification rate results in near-diffusionless solidification, which traps more solutes in the matrix. This type of solidification yields a more supersaturated material with nearly 90% of the total Cu content in the matrix and a fine dispersion of nanoscale spherical precipitates below 100 nm in diameter. The small addition of Sc during casting primarily affects the material at low cooling rates, where primary Sc-containing particles modify the grain boundary shape.

The article presents the possibilities of using wavelet transform and fast Fourier analysis (FFT) to evaluate the signal collected during roughness measurement. During the tests, high-density polyeth-ylene was turned using variable cutting parameters. During cutting, the tool feed was changed to ob-tain roughness structures of different types and with varying degrees of anisotropy. The measured roughness profiles were filtered with Daubechies 6 (db6), Morlet and "Mexican Hat" wavelets and examined using Fourier analysis. The research carried out shows how the machining conditions affect the surface condition and the stability of the cutting process under variable machining conditions for high molecular weight polymers. The effectiveness of the continuous wavelet transform (CWT), sup-plemented with data obtained from Fourier analysis, in identifying places and detecting the nature of disturbances in the generated roughness signal is also shown.

This paper presents the design and analysis of a 3-PRS mechanism for positioning cutting heads in CNC machines, addressing limitations of traditional rotary mechanisms such as hose twisting, wear, and limited modularity. Kinematic and dynamic analyses guided actuator selection and confirmed bearing durability. The mechanism achieves a favourable load-to-weight ratio and integrated Z-axis movement, making it suitable for simpler gantry CNC machines. Though programming is complex due to multiaxis synchronization, the modular design supports easy adaptation to different tools. Future research will focus on reducing the eccentric torch offset and refining dimensions to enhance versatility. The mechanism has strong potential in sectors like automotive, aerospace, and construction.

Gears and toothed parts are significant components in power transmission systems. These parts usu-ally manufactured by traditional methods such as machining by milling or forming by rotary forging. In this study, the forming of solid gears or toothed parts using a forging process that combines rotary forging and ballizing technique. The specimens were placed inside the die with excessive volume to fill the toothed part in the die. The forming tool applies pressure to the specimen while rotating it together with the die by the lathe machine chuck, while the tool advances continuously in the direc-tion of the die. This reduces height of the specimen and increases its diameter, causing metal flow to fill die cavity teeth and form the gear or toothed part required for production. Two sets of experi-ments were performed. In the first set, optimization for the appropriate volume of four different sizes of dies and four forming tools was conducted. While in the second set, the effects of forming process variables on the forming load and tooth filling percentage was studied. The results showed that the best tooth filling ratio happened with specimens size of 1.2 to 1.4 times the volume size of the desired tooth for filling. The results also revealed that the forming speed, die size, and forming tool diameter affect the filling ratio and forming load.

This paper presents the results of nanoscratch tests conducted on adhesive bond thickness, analyzed in terms of material property heterogeneity within adhesive bonds. Nanoscratch tests were performed on adhesive layers made from rigid and elastic adhesives with thicknesses of 0.05 mm and 0.1 mm, under constant load conditions. Penetration depth and residual depth results were analyzed for potential varia-tions in hardness along the adhesive layer thickness. The findings clearly indicate some differences in the material properties of adhesive layers within bonded joints. These results can also be correlated with the phenomenon of apparent Young's modulus, which involves changes in modulus values across the adhesive bond thickness. These findings are crucial for understanding phenomena affecting the consti-tution of adhesive joints, enabling enhancements in their reliability and durability.

The optimization of process parameters plays a critical role in controlling temperature and velocity fields during centrifugal casting, which is essential for mitigating shrinkage porosity defects caused by uneven cooling in thick walled bearing alloy layers. In this study, two sequential numerical models were devel-oped using ProCAST software to simulate gravity filling and centrifugal solidification stages. The effects of key parameters, including inlet cross-sectional area and centrifugal rotational speed, on flow field characteristics were systematically analyzed. By using an orthogonal experimental design, we deter-mined the optimal parameters: a melt temperature of 440 °C for the Babbitt alloy, an initial temperature of 280 °C for the bearing blank, a filling inlet diameter of 16 mm, and a rotational speed of 340 r/min. Bearing alloy layers manufactured according to these optimized parameters exhibit no evident shrinkage or cracks on their surfaces. The high quality finished products meet the design requirements, thereby validating the accuracy of the numerical simulation.

This study focuses on addressing the challenges faced by individuals with physical disabilities, particu-larly lower body impairments, by developing a stump socket using Reverse Engineering (RE), 3D Printing, and QFD. The integration of these three methods is something new in product design devel-opment, especially prosthetic products. The research adopted a three-step methodology: 3D scanning the stump, obtaining precise measurements, and fabricating a stump socket using fused deposition modeling (FDM) technology. QFD will produce technical requirements (TR) derived from consumer needs and brainstorming with prosthetists. TR will be the basis for developing the socket design in the 3D Scanning phase. The scanning process utilized Polycam, and the 3D models were refined with Meshmixer. The socket was fabricated using PLA+ material to ensure cost efficiency and customiza-bility. Experimental results demonstrated the accuracy and feasibility of the designed prosthetic sock-et, with a layer thickness of 0.2 mm and printing temperatures up to 215°C. The study highlights the potential of RE and 3D Printing to address the unique anthropometric variations of Indonesian users, overcome the limitations of conventional crutches, and reduce production costs compared to imported prostheses. This approach demonstrates a scalable and innovative solution to improve accessibility and quality of life for individuals with physical disabilities while contributing to economic inclusivity.

The study examines the effect of various post-processing heat treatments on the microstructural evolution and hardness of the AlSi10Mg alloy produced by selective laser melting (SLM). The alloy was examined in the as-built (AB) condition and after three heat treatment regimes: direct aging (DA, 160°C/5 h), stress relieving (SR, 300°C/2 h), and solution annealing followed by artificial aging (SA, 520°C/2 h + 170°C/4 h) to better understand the solidification and consolidation processes. A multiscale characterization using OM, SEM, EBSD, TEM, and EDS was performed to reveal the changes in specific microstructures due to additive manufacturing and different levels of heat treatment. The AB state exhibited a fine cellular network of Si within an α-Al matrix, and high hardness (approx. 138 HV1). The DA treatment preserved cellular morphology with mild coarsening, whereas SR led to partial fragmentation of the Si network and a significant drop in hardness (approx. 83 HV1). The SA condition caused recrystallization, Si spheroidization, and formation of Mg- and Fe-rich precipitates, accompanied by moderate hardness recovery (approx. 104 HV1). The persistent crystallographic texture was confirmed across all states.

Monitoring and diagnostics of cutting tools are crucial for ensuring production efficiency and product quality in the machining industry. This study uses acoustic emission (AE) to non-invasively detect damage and monitor tool condition in real time. Experiments assessed cutting inserts in a milling head, both used and new. Results showed AE effectively diagnoses tool wear, with significant differences in signals from worn and new inserts. Fast Fourier Transform (FFT) analysis determined the frequency range of signals during machining, confirming AE's usefulness. Microscope verification supported the AE findings on tool wear. This research highlights AE's potential in non-destructive diagnostics, enhancing production efficiency and product quality

To design an engine intake system that complies with FSC racing regulations while achieving enhanced operational stability, this study conducts a comprehensive review of domestic and international research advancements in racing engine intake systems. Through computational fluid dynamics simulations performed in Workbench Fluent, critical structural parameters of the restrictor valve were optimized, resulting in a 12.06% improvement in outlet mass flow rate compared to the baseline design. A three-dimensional parametric model of the racing intake system was developed using Siemens NX platform. Taking the intake plenum chamber as a representative component, this research systematically analyzes the CNC machining process for the mold of the pressure stabilization chamber. The investigation encompasses toolpath generation, cutting simulation verification, and ultimately implements the optimized NC program on machining centers for physical manufacturing. The fabricated mold exhibits high dimensional accuracy and superior surface finish, providing both theoretical guidance and practical manufacturing references for intake system development. This integrated approach combining numerical optimization with advanced manufacturing techniques demonstrates significant potential for performance enhancement in motorsport engineering applications.

This article presents particular results from a long term research focused on machining of INCONEL alloys. As a representative of this group of material INCONEL 738LC is selected and the article presents results of different experiments conducted. The behavior of material under different conditions was evaluated with focus to define cutting condition that can be recommended as suitable cutting conditions for profile milling of material. Basic problems of profile milling are exposed with focus to the respective material. Several machining experiments are explained and archived results are discussed. Effect of tool geometry and geometrical constraints and relations during profile milling is defined. Tool wear and cutting forces were measured and evaluated. The final conclusion is a recommendation for successful machining of given material.

The paper focuses on the application of machine learning techniques and optimization algorithms in predictions and controls of grinding temperature variations. The major thrust of investigation has been on how the different input conditions such as feed, depth of cut, and cooling conditions influence grinding temperatures and the effectiveness of these conditions on the control of their thermal effects. Three machine learning models: Random Forest (RF), Gradient Boosting (GB), and Artificial Neural Networks (ANN) were then used to develop prediction models for the grinding temperature on both face and shoulder of the workpiece. Out of all the models, RF achieved a much higher R² score of 0.96 as compared to both GB and ANN, indicating its greater predictive performance. Furthermore, Bayesian optimization and genetic algorithms were employed in model optimization and grind parameters and cooling condition optimization to avoid damages caused due to temperature. MQL has been found to be highly superior to the inefficient dry cooling methods in terms of achieving lower grinding temperatures and, therefore, seems to be most suited as an eco-friendly yet practical cooling solution as based on this comparison. Altogether, these research findings indicate that AI-based techniques and traditional optimization methods can lead to much better grinding in terms of efficiency and energy consumption, as well as surface quality, and assist towards greener manufacturing altogether.

Manufacturing inaccuracies in vehicle suspension systems inevitably lead to uncertainties in the parameters of their structural components. Simultaneously, the road excitation impacting nonlinear vehicle systems exhibits pronounced randomness and time-variant characteristics. Consequently, it is crucial to conduct a stochastic dynamics analysis on nonlinear suspension systems, taking into account these uncertain factors. In this paper, a seven-degree-of-freedom (7-DOF) nonlinear suspension system dynamics model has been established. The stochastic process of road irregularities is simulated using the harmonic superposition method. Moreover, based on the direct probability density integral method, the stochastic dynamic equations of the nonlinear suspension system and their corresponding solution strategies have been developed and explored. Through MATLAB, the time-varying probability density function of the vibration response for a nonlinear vehicle suspension system was calculated under the combined effects of stochastic road irregularity excitation and random coupling of system structural parameters. Additionally, analyses were conducted on how different coefficients of variation and the intensity of nonlinearity in the suspension system influence the probability density of the output body displacement of the nonlinear vehicle suspension system. The research outcomes demonstrate that the direct probability density integral method offers superior efficiency and accuracy when computing nonlinear vehicle suspension systems. Furthermore, altering the coefficients of variation for various system parameters reveals that as these coefficients increase, the disparity in the probability density of body displacement becomes more pronounced, leading to more intense vehicle vibrations. Under soft nonlinear conditions with lower suspension spring stiffness, the probability density function of body displacement shifts slightly to the right with minimal change. However, under strong nonlinear conditions, body displacement significantly increases, resulting in diminished vibration isolation capabilities of the suspension system. This leads to severe jolts and a noticeable decline in ride comfort during vehicle operation.

In this study, the process parameters of a vertical shaft impact (VSI) crusher are optimized. Different feed size distributions, material physical properties, and product size distribution requirements are considered to determine the optimal material particle bond cleavage ratio. First, a numerical model is developed to simulate the crushing effect by adopting a CFD-DEM method. Then, the relationship between the crushing effect and the rotor speed, feed size distribution, and feed rate is revealed by analyzing the bond cleavage ratio of smaller-size distribution feed crushing to the specified particle size. The optimized working parameters of the crusher are determined under different feed size distributions. The results show that the feed size distribution of 8 mm, 20 mm, and 40 mm account for 20%, 30%, and 50% of the feed, respectively. Based on the results, it is implied that a feed rate of 120 t/h and a rotor rotational speed of 1800 r/min can be selected for crushing production. When the feed size distribution varies, this method can also be used to select a suitable feed rate and the rotor speed for crushing production. Overall, this study guides for optimizing the working parameters and improving the crushing efficiency.

This study centers on 7B50 aluminium alloy. The intention is to reduce the pre-treatment and post-treatment times of the shot peening model. By comparing and analyzing different process parameters, the best combination of peening solutions can be obtained. The pre-processing is implemented through a GUI interactive interface. Post-processing is carried out by using Python for secondary development in ABAQUS. Orthogonal test method is employed for post-processing analysis of shot peening simulations under various process conditions. The results are evaluated by using a weighted composite scoring method to determine the depth of the residual compressive stress layer on the workpiece surface, the surface residual compressive stress, and the extreme deviation of the maximum residual compressive stress value after shot peening. The combined influence degree of shot peening process parameters such as impact speed, projectile diameter and impact angle is determined. The optimal combination of shot peening process parameters is analyzed and verified through simulation.

The article deals with the measurement of the vibrations in passenger elevators. The introduction of an article briefly discusses machine vibrations and their impact on machine design and the surrounding environment. The basic equations from which the equations of motion are derived are listed here. The importance of analyzing machine vibrations in their design, or rather proposing solutions to reduce vi-brations during machine reconstruction, is emphasized. Specifically, attention is paid to vibrations gen-erated during an elevator operation in the elevator shaft. This is an elevator for transporting people in a newly constructed 5-story building. Vibration values generated by an elevator operation were measured in order to assess the suitability of simple anti-vibration modifications. Vibration measurements were taken on an existing elevator without modifications, and after the initial measurements, modifications were made to attach the guides to the bracket and attach the bracket to the elevator shaft wall. After the adjustment, the vibration measurement was performed again and both measurements were compared with each other.

Determining the productivity and quality of precision AWJ machining requires routine and careful inspection of nozzle condition. The degradation of the inner bore of the nozzle adversely impacts the mixing efficiency and uniformity of the water jet, thereby affecting its cutting performance. In this study, new nozzle was designed and manufactured using additive manufacturing and were made of 316 L stainless steel. The new nozzle consists of two combined parts with the peculiarity of being easy to install using a screw thread. The wear behavior of the new nozzle was examined using an accelerat-ed wear test. An accelerated wear test was conducted on the hard abrasive silicon carbide (SiC) and compared to garnet, the abrasive commonly used in the AWJ industry. The aim of the test was to de-termine the wear pattern of the nozzle. The cumulative mass loss and nozzle diameter increase for different abrasives were measured. The geometric change in the nozzle is made visible through de-structive examination. The findings indicated that the type of abrasives significantly affects nozzle wear. As the hardness of the abrasive increases, the diameter of the nozzle enlarges, resulting in accel-erated nozzle wear. The mass loss factor of SiC abrasives is three times higher than that of garnet abrasives. This research allows practitioners to monitor the nozzle wear behaviour during the AWJ process. The results obtained were used to estimate the nozzle life based on the observed wear history.

The magnitude of a locomotive's traction and braking forces is directly related to its adhesive mass, which largely determines its tractive and braking characteristics. Therefore, an important task is to maximize the utilization of the locomotive's adhesive mass. The degree of adhesive mass utilization is determined by more factors and is quantitatively characterized by the Adhesive Mass Utilization Coeffi-cient (AMUC). One of the ways to increase the AMUC is to improve the locomotive's lever-type brake transmission. In braking mode, it interacts with the wheelsets and the bogie frame and may block the operation of the first stage of the suspension system. This research presents the results of a mathematical model-based study of the influence of certain parameters of the lever brake transmission on the utilisation of locomotive adhesive mass in braking mode. The calculations were carried out for various values of the vertical stiffness of the brake transmission. The results indicate that the distribution of vertical loads across the locomotive's wheelsets in braking mode significantly depends on the vertical stiffness of the brake transmission.

The effects of aging treatment temperature of 250°C on microstructure, mechanical properties characteristics of 6111 aluminum alloy sheet were investigated by mechanical testing, scanning electron microscopy, electron backscatter diffraction and other analytical methods. The results show that the aging treatment temperature has a significant effect on the yield strength of cold rolled 6111 aluminum alloy, and appropriate heat treatment can significantly improve the work-hardening properties of rolled 6111 aluminum alloy. The rolled sheet without heat treatment aging shows the highest strength values, with the yield strength reaching 140.2 MPa and the tensile strength 211.2 MPa, while the ten-sile strength decreases to 119.2 MPa and the yield strength to 35.1 MPa when the heat treatment aging temperature of the cold-rolled sheet is set at 250°C. In terms of the plastic behavior of the sheet, the elongation reaches a maximum value of 31.3% when aging at 250°C. The elongation of the cold-rolled aluminum alloy reaches a maximum value of 31.3% when aging at 250 °C. The elongation reached the maximum value of 31.3% at the aging temperature of 250°C.

The given paper deals with the defects propagation in car tires for passenger vehicles under dynamic loading. The occurrence of defects has the significant influence on the lifetime and quality of the tire, especially during its operation as a part of the vehicle. The given defects are closely connected with a safety in road traffic. The aim of the study was to carry out a non-destructive analysis of the car tire for the purpose to analyze the defects propagation as well as to introduce the defects classification and their location along with the whole course of rupture as a result of increasing speed, loading and the number of hours or kilometers driven. During the analysis, we used a non-destructive method for detecting defects using a non-destructive analyzer that works on the principle of shearography. The experimental measurement was carried out for 12 car tires. The measurement results are displayed from the non-destructive analyzer in the form of protocols from measurement and video display. The evaluation of the results of the measurement for the propagation of defects is displayed graphically. In relation to the tire casing, the analysis of the defects propagation can help design engineers to solve critical issues by choosing the right material, modifying dimensions of individual components or even by redesigning the overall construction of the tire casing and thus to increase the safety from the as-pect of vehicle operation.

The Mg-Y-Zn alloy system is well known for its outstanding combination of high strength and ductility, even at relatively low concentrations of alloying elements. This exceptional performance is primarily at-tributed to its characteristic microstructure, which features Long-Period Stacking Ordered (LPSO) phas-es and the distinctive Mille-Feuille Structure (MFS). Kink-induced strengthening, developed during thermomechanical processing, has emerged as a promising strategy to simultaneously enhance strength and ductility. In this study, the beneficial effect of pre-deformation aimed at introducing additional kinks into the microstructure prior to extrusion is demonstrated. The subsequent extrusion process promotes dynamic recrystallization (DRX), generating fine DRX grains while preserving kink structures in the non-DRX regions. As a result, the yield strength is enhanced by approximately 80 MPa, accom-panied by a slight improvement in ductility.

In order to improve the crushing effect of the rotor of vertical shaft impact crusher on the particle, the design method of secondary accelerated rotor based on kinematics theory is proposed. And the operation effect of the secondary acceleration type rotor was verified using a combination of computational fluid dynamics and discrete element method (CFD-EDM). First, the kinematics of the particles thrown by the rotor throwing head was analyzed. On this basis, the structure of the secondary acceleration type rotor was designed by comprehensively considering factors such as the motion, friction, and collision recovery coefficient of particles; Then, based on the gas-solid coupling analysis method, a simulation model of the rotor's effect on particle acceleration was established and the reliability of the model was verified; Finally, the CFD-EDM method was used to calculate and analyze the motion process of particles in the crushing chamber, the collision position of particles in the crushing chamber, and the average throwing speed of the rotor. Research results show that roughly 77.6% of the particles in the crushing chamber will collide with the impact plate to achieve secondary acceleration; The average throwing speed of the traditional rotor is 57.14m/s, and the average throwing speed of the designed secondary accelerated rotor is 60.89m/s, which is about 6% higher than the average throwing speed compared with the traditional rotor, and achieves the expected design purpose.

This paper details a systematic machine learning workflow designed for the prediction of surface roughness in grinding operations using key machining parameters. Those parameters are: Depth of Cut, Feed Rate, Work Speed, and Wheel Speed. The model was trained and validated on a data set which comprised experimental measurements of those parameters and their corresponding values of surface roughness. Three machine learning models, Random Forest, Gradient Boosting, and LightGBM, were developed and tested based on accuracy of prediction of the surface roughness. The validation of all three models was performed using performance metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R²). Among the models, LightGBM exhibited the highest value of performance with the lowest error ob-served MSE 0.0047, MAE 0.064, and RMSE 0.09 respectively while an R-squared value closest to zero. (-0.02). The moderate performance was shown by the Random Forest which presented an MSE of 0.0063, MAE of 0.085, and RMSE of 0.10 while the Gradient Boosting recorded the highest error rates which may indicate that it is the least effective model. It's an effective application of machine learning in predicting surface roughness and gives an insight into machining process optimization through predictive modelling.

The paper presents work aimed at building practical applications of virtual reality (VR) in manufacturing environments. It contains studies of the optical properties of cameras and lenses aimed at the selection of an optimal set (camera, adapter, lens) for the realization of recordings and video transmissions in stereoscopic format for VR. In response to the increasing trend in the number of applications of VR systems in the industry, works have been initiated with the purpose of building a system levelling image noise identified thus far as an obstacle to the effective utilization of VR in production systems. It was considered that picture error correction can significantly increase an already big data stream from the recordings. Based on it, a set of parameter values was defined which determined the selection of study equipment. Three research areas were set: the verification of the optical correctness, the study of image defects and their correction and the determination of the maximum optical resolution and the achievable image parameters in various lighting and environmental conditions. An example was presented for the application of a projected system for the monitoring of undesirable events/movement at work stands and key areas of production halls as well as training in the high-risk production zones.

Drill bits used for machining of composite materials can have different geometries and it is difficult to choose suitable geometry for a specific type of composite. Unsuitable geometry of a drill bit leads to bad surface quality. The objective of this paper is to find the most suitable drill bit geometry for machining of the thermoplastic composite C/PPS in terms of surface quality and magnitude of thrust force under different cutting conditions. Three drill bits were chosen for experimental investigation. A significant influence of the point angle was identified. A gradually decreased point angle together with an increased rake angle of the cutting edge lead to better surface quality. In addition, investigation of the influence of cutting conditions on surface quality and cutting forces was performed. A considerable influence of feed was observed in comparison to cutting velocity. Information included in this paper can help to design more suitable technology for drilling of thermoplastic composites.

In the present study, local defects in deep groove ball bearings are studied as forward and inverse problems. To this end, the separation-integration method is applied for modeling the forward problem. It is assumed that the inner race of the rolling element is multi-DOF, while the outer race is deformable along the radial direction. Then the problem is modeled with concepts of the finite element method. The contact force for the rolling elements is described by the nonlinear Hertz contact deformation. Various surface defects originating from local deformations are introduced into the developed model. Since the outer ring can be coupled with the FE model of the housing, the developed bearing model is capable of considering the transmission path of the bearing housing. Then model parameters are modified to reach better performance in predicting local defects. Through translating the inverse problem into the comparison of the geometric distance, measured indicators are used in the defect detection process and the relative location and size of defects are predicted. Finally, the defect range is established to evaluate the fault severity. Obtained results demonstrate that the proposed method is effective and accurate in the studied cases.

Laser cladding technology is used to clad the surface layer of H13 mold steel with Ni60A metal powder coating to solve the failure problem. The study used JMatPro software to extract and fit the thermophysical property parameters of the substrate and the clad material, and then used ANSYS APDL software to qualitatively analyze the distribution of melt pool morphology, nodal temperature versus time course curve and residual stress magnitude during the laser cladding process. Based on the results of the minimum residual stress in the cladding, reasonable scan paths were derived for the preparation of metal coatings on the surface layer of the die steel. The results show that the maximum peak temperature of the cladding process is 2515°C using short path scanning. The cladding layer can form a good metallurgical bond with the substrate at this temperature, with a stress of 406.68 MPa in the scanning direction and 284.45 MPa perpendicular to the scanning direction, which is significantly smaller than the residual stresses of other scanning methods. The residual stress values for the different strategies are from largest to smallest: spiral scan > block scan > long path scan > short path scan.

This article explores the significance of microtexturing on cutting tools for improved tribological performance and reduced friction in machining operations. Drawing inspiration from biomimetic structures, the study focuses on laser surface microtexturing and evaluates its impact on cutting forces and tool wear. Experiments involve microtextures of dots with a specific emphasis on a fiber laser-processed pattern. While long-term tests reveal the formation of negative protrusions on the textured tools, reduced variability in cutting forces suggests potential benefits for stable machining processes and increased tool longevity. The findings underscore the intricate relationship between microtexturing patterns and tool performance, offering insights into the broader implications for energy-efficient machining.