Workpiece Surface Research Articles

Feasibility analysis and parameter optimization of ultrasonic assisted electrolytic plasma polishing of small modulus gears

Precision polishing of small modulus gears is a difficult task due to the complexity of their geometry. Electrolytic plasma polishing technology as a green and efficient processing method, it can effectively decrease the friction between parts and improve the service life. However, considering the uneven distribution of gas layers on the surface of workpieces in electrolytic plasma polishing, which affects the precision of workpiece shapes after polishing, this study proposed the use of ultrasonic vibrations to generate pressure waves to improve the fluid characteristics. Comparative experiments on small modulus gear electrolytic plasma polishing with and without ultrasonic vibration were conducted. A high-speed camera was utilized to monitor the distribution of gas layers around the workpiece during the polishing process in real-time. The optical measurement methods were used to evaluate the gear precision. The results indicate that ultrasonic assistance is beneficial in improving the uniformity of the gas layers surrounding the workpiece, achieving higher gear precision, and obtaining a lower surface roughness after polishing. Through orthogonal experiments, this study analyzed the effects of various process parameters on the surface roughness of gear profiles and the uniformity of material removal after polishing. These parameters included power voltage, polishing time, workpiece immersion depth, ultrasonic frequency, and workpiece posture angle. An optimal combination of process parameters was identified. The results show that the best surface roughness and gear precision were achieved with a power voltage of 300 V, a polishing time of 4 min, a workpiece immersion depth of about 10 mm, an ultrasonic frequency of 40 kHz, and a workpiece tilt angle of 45°.

Analysis of tangential stress response of ice-workpiece interface in ice-based machining of thin-walled parts: Modeling and experiment

The contact stress between the fixture and the workpiece surface is a crucial factor in evaluating the constraint performance of the fixture. According to the concept of an ice-based fixturing(IBF) proposed by the author, this paper conducts a modeling and experimental study of the tangential stress response at the ice-workpiece interface during ice-based machining. Initially, the principle of IBF is explained. Subsequently, the Dundurs parameters are used to characterize the mechanical properties of the ice-workpiece interface. According to the interface continuous conditions of stress and displacement, a predictive model for the tangential stress at the ice-workpiece interface is established using the Goursat formula. Afterwards, interface temperature experiments are carried out to analyze the temperature state of the ice-workpiece interface. Finally, milling experiments are conducted to analyze the variation of cutting force and interface tangential stress with the thickness of TWP, and to verify the accuracy of the analytical model. This study can provide valuable references for the evaluation of the constraint state of the fixture.

Experimental Investigation of Cr12 Steel Under Electrostatic Minimum Quantity Lubrication During Grinding

In this work, electrostatic minimum quantity lubrication (EMQL) has been applied in grinding. When the droplets were charged, it could promote penetrability in the processing area. The electric field formed between the charged droplets and the surface of Cr12 die steel could affect the hardness of the workpiece surface. The grinding mechanism of EMQL has been revealed under different charging voltage by analyzing the wetting angle of droplets and the hardness of Cr12 surface. The reduction of grinding force (11.5% to 49%), surface roughness (10% to 22.1%), and the increase in grinding ratio (1.9% to 27.3%) and surface quality of EMQL under various charging voltages were studied. The results showed that the wetting angle decreased when the droplets were charged. Compared to MQL, the charged lubricant droplets with better penetrability are easier to penetrate and spread on the contact surface between the grinding wheel and the workpiece, thereby improving the lubrication of the friction interface and obtaining better grinding performance. Moreover, we also found that the positively charged EMQL not only effectively improves the penetrability of droplets but reduces the hardness of the Cr12 surface. Thus, the grinding performances under positively charged EMQL are always better than these under negatively charged when grinding Cr12.

An Experimental Investigation into the Enhancement of Surface Quality of Inconel 718 Through Axial Ultrasonic Vibration-Assisted Grinding in Dry and MQL Environments

Ultrasonic vibration-assisted grinding (UVAG) has proven to be beneficial for grinding difficult-to-machine materials. This work attempts to enhance the grinding performance of Inconel 718 through a comprehensive study of UVAG characteristics. Grinding experiments were performed in both dry and Minimum Quantity Lubrication (MQL) environments, and assessment of the grinding forces, specific energy, residual stress, and surface topography was done. A substantial reduction of both surface roughness and grinding force components was observed in UVAG compared to conventional grinding (CG). Utilizing UVAG with MQL at the maximum vibration amplitude led to a 64% reduction in tangential grinding force and a 51% decrease in roughness parameter, Ra, when compared to CG conducted in a dry environment. The high-frequency indentations of the abrasives in UVAG generated compressive residual stresses on the ground surface. Surface parameters pointed to uniform texture and SEM images showed widening of abrasive grain tracks on the workpiece surface during UVAG. The utilization of UVAG under MQL produced a synergistic impact and resulted in the lowest grinding forces, specific energy, and optimal surface quality among all the grinding conditions investigated. Overall analysis of the results indicated that the axial configuration of the vibration set-up is favorable for UVAG, and the high-frequency periodic separation-cutting characteristic of the process improves lubricating efficiency and grinding performance.

The influences of alloying elements and processing conditions on the machinability of wrought aluminium alloys: A literature review

Today, wrought aluminium alloys are ranked among the most important materials with low specific density, strength features, corrosion resistance, machinability and recyclability properties in numerous application fields. Machining process of these alloys involves a number of considerations to ensure the highest quality and productivity. Key machinability issues include the rate of tool wear, workpiece surface finish and integrity and machining process sustainability. Understanding and optimising these parameters can lead to improving the machinability, better surface finish, longer tool life, and overall, more efficient and cost-effective machining processes for wrought aluminium alloys. The machining of wrought aluminium alloys remains a challenging task due to their unique characteristics, such as high strength, thermal conductivity and refined grain structures with mechanical and/or heat treatment. Although considerable progress has been made in the development of cutting tool materials and machining techniques for wrought aluminium alloys, further research is required to improve the machinability of these materials and reduce the associated costs and time needed for production. Having access to relevant information about these characteristics can help industries and researchers make informed decisions and achieve better outcomes when machining of these important materials. Accordingly, in the current research work, a comprehensive study has been carried out on machining of wrought aluminium from different points of view.

A novel trajectory planning method for mobile robotic grinding wind turbine blade

As the core component of wind turbine, wind turbine blade requires two grinding processes in the production. However, mobile robotic automation grinding of wind turbine blades is considered to be a challenging task due to the high aspect ratio and compound surface of the wind turbine blade. The trajectories generated by most robotic grinding trajectory planning algorithms are often found to be inferior in grinding large compound surface workpieces, as they are typically designed for robotic machining with a fixed base. In this paper, a novel iso-planar algorithm based on oriented bounding box (OBB) of the workpiece is developed to plan the grinding trajectories by taking into consideration the characteristics of blade. The constant chord length algorithm employing Taylor quadratic expansion is then developed to discretize trajectory into grinding points. Considering the characteristics of compound surface, a post-processing strategy is proposed to eliminate redundant grinding points and generate consistent tool orientations on compound surface. Based on these three steps, a workstation location optimization model for improving robot manipulability is introduced to determine a series of workstation locations. Furthermore, the grinding and movement synchronization strategy based on mobile platform trajectory interpolation is proposed to enhance the efficiency of machining large workpieces. The simulation and experiments demonstrate the effectiveness of the proposed trajectory planning method for mobile robotic grinding wind turbine blade, the rationality of the optimization model and the feasibility of grinding and movement synchronization strategy.

Scalable and efficient fabrication of surface microstructures using a small wheeled robot with a vibration-cutting tool

Bioinspired microstructure emerges as a powerful technique to enhance the surface functionalities and properties in a seizes of breakthrough areas. However, its application is limited by the scalability of fabrication methods. This study introduces a scalable fabrication technique utilizing a small wheeled robot designed to operate on a workpiece surface. Due to its unique three-point-support design, the robot maintains a stable cutting depth and exhibits high adaptability to large-scale workpieces. Motion stability is calibrated using a laser displacement sensor, achieving a maximum velocity of approximately 3.7 mm/s. Finally, the robot successfully produces microstructures with a height of 8 μm on aluminum workpieces, demonstrating its promising capacity.

A molecular dynamics study on microscopic mechanism of nano-polished single crystal copper

Molecular dynamics simulations are performed to investigate the microscopic mechanism of diamond abrasive grain (DAG) polishing on the surface of single crystal copper (SCC). In this paper, the polishing parameters including the incident angle and the polishing force applied to the DAG are varied to analyze the surface morphology, friction and subsurface damage state of the workpiece. The polishing process on scratched SCC surface was also investigated. It is found that variations in the incident angle and the polishing force have significant effects on the swarf formation and internal structure of the workpiece. At small incident angle, unstable DAG motion and obvious friction fluctuations is observed. As the incident angle becomes larger, the sliding of the DAG on the workpiece surface becomes stable, and the friction force undergoes transition from the rapid growth to the stabilization phase. However, the fluctuation of dislocation density increases with the incident angle. As the polishing force increases, the sliding distance required to reach the peak of dislocation density becomes longer. In addition, the friction as well as the dislocation density show different characteristics on the scratched surface compared to the smooth surface.

Region-Based Approach for Machining Time Improvement in Robot Surface Finishing

Traditionally, in robotic surface finishing, the entire workpiece is processed at a uniform speed, predetermined by the operator, which does not account for variations in the machinability across different regions of the workpiece. This conventional approach often leads to inefficiencies, especially given the diverse geometrical characteristics of workpieces that could potentially allow for different machining speeds. Our study introduces a region-based approach, which improves surface finishing machining time by allowing variable speeds and directions tailored to each region’s specific characteristics. This method leverages a task-oriented strategy integrating robot kinematics and workpiece surface geometry, subdivided by the clustering algorithm. Subsequently, methods for optimization algorithms were developed to calculate each region’s optimal machining speeds and directions. The efficacy of this approach was validated through numerical results on two distinct workpieces, demonstrating significant improvements in machining times. The region-based approach yielded up to a 37% reduction in machining time compared to traditional single-direction machining. Further enhancements were achieved by optimizing the workpiece positioning, which, in our case, added up to an additional 16% improvement from the initial position. Validation processes were conducted to ensure the collaborative robot’s joint velocities remained within safe operational limits while executing the region-based surface finishing strategy.

Box-Behnken Design for MAFM Precision Surface Finishing of Al-6063/SiC/B<sub>4</sub>C Composites: A Comparative Study with Nature-Inspired Algorithms

Precision polishing is difficult for advanced materials like silicon carbide and boron carbide. Magnetic abrasive flow machining (MAFM) has become an effective method for cleaning, deburring, and polishing metal and high-tech engineering parts. By finishing hybrid Al/SiC/B4C-metal matrix composites (MMCs), this research uses MAFM for experimental readings. The present work is innovative due to the aluminum workpiece fixture, hybrid composites, and response surface methodology (RSM) modeling. The neural simulation of the MAFM process and nature-inspired error reduction make it unique. Using six input and two output parameters, a generic framework is created. Box-Behnken design (BBD) of response surface methodology plans and executes 54 runs of experimentation. The hybrid artificial neural network (ANN) technique is used to compare the MAFM process systematically. ANN is used to model parameter input-output relations. To anticipate the created surface accurately, regression models must be precise. These hybrid particle swarm optimization (PSO)-genetic algorithm (GA)-simulated annealing (SA) algorithms optimize the MAFM process. Additionally, trained ANN models outperform the BBD model in prediction. For optimal error reduction, the neural network uses Bayesian regularization with 112 iterations. The ANN model regression graph shows a correlation between inputs and outputs. A scanning electron microscope (SEM) with 300-magnification examines the workpiece surface. According to SEM, MAFM provides fine surface textures, thus reducing abnormalities.

Portable Machine Tools by Small Piezoelectric Robots for Scalable and Waviness‐Adaptive Fabrication of Surface Microstructures

Surface functional microstructures exhibit extensive application requirements in an array of breakthrough areas. One critical problem that restricts their industrial application is the lack of scalable fabrication techniques due to the limitation of conventional machine tools. This study proposes a scalable surface texturing technique using a portable small (30 × 19 × 22 mm) three‐leg robot that walks and works on the workpiece surface. Due to the elliptical tool vibration, microgrooves can be created on the workpiece surface periodically; meanwhile, the machining force drives the robot to walk forward. Surface texturing experiments are conducted on aluminum and copper workpieces to explore the machining performance of the small robot. The robot can reach a maximum moving velocity of 6.3 mm s−1 and can produce microstructures with a spacing of 4–14 μm on workpiece surfaces. Owing to its unique working principle, the small robot can maintain a constant depth of cut, demonstrating its capacity to adapt to the surface waviness of the workpiece. Finally, the motion straightness of the robot is greatly improved by combining it with the auxiliary track, and multiline microstructures are obtained. In short, the developed small robot presents a promising solution to the challenge of scalable surface texturing.

Investigation on the influence of mesoscale geometric features on the surface white layer characteristics in titanium alloy milling using ball end mills

A white layer will be generated on the machined surface when milling titanium alloy. Its existence will make the surface of the workpiece more brittle, and it is easy to produce cracks during the machining process, which greatly harms machining. Aiming at this problem, this paper takes the ball-end milling cutter with mesoscopic geometric characteristics as the research object, establishes the theoretical model of the white layer thickness of the workpiece under the micro-texture and cutting edge factors, analyzes the single factor of micro-texture parameters and cutting edge parameters, and the interaction between them and cutting parameters on the milling force-thermal characteristics and the white layer of the workpiece. The influence law reveals its mechanism from the macro and micro perspectives. It uses the white layer thickness as the evaluation index to optimize the mesoscopic geometric characteristic parameters by using the simulated annealing algorithm. The results demonstrate that the mesoscopic geometric feature of the ball-end milling cutter effectively reduces the thickness of the white layer, achieving a 38% reduction compared to that observed with a non-textured milling cutter. The thickness of the white layer exhibits a positive correlation with the distance L from the blade and a negative correlation with the edge radius R. The interaction between the cutting edge radius R and the cutting depth a p influences the milling force and heat, alters the micro-texture of the workpiece surface, induces the α + β phase transformation, and affects the white layer thickness. Based on the predictive model for white layer thickness, the optimization results for comprehensive milling performance are as follows: R is 59.39 μm, L is 110.01 μm, D is 58.68 μm, L1 is 130.59 μm, a p is 0.30 mm, V is 147.39 mm/min, f is 0.08 mm/z.

Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L18 (6133) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.e., depth of cut, feed rate and cutting speed to study the effect of these parameters on workpiece surface roughness and tool life. The data obtained from special L18 (6133) orthogonal array experimental design in dry finishing turning process is used to train AI models. Multi-layer perceptron based artificial neural networks (MLP-ANNs), support vector machines (SVMs) and decision trees are compared for better understanding ability of low resolution experimental design. The AI models can be used with low resolution experimental design to obtain causal relationships between input and output variables. The best performing operational input ranges are identified for output parameters. AI-response surfaces indicate different tool life behavior for alloy based coated tool inserts and non-alloy based coated tool inserts. The AI-Taguchi hybrid modelling and optimization technique helped in achieving 26% of experimental savings (obtaining causal relation with 26% less number of experiments) compared to conventional Taguchi design combined with two screened factors three levels full factorial experimentation.

Piecewise approximation and local differential compensation of contact stress distribution of workpiece surface in robotic belt grinding

Piecewise approximation and local differential compensation of contact stress distribution of workpiece surface in robotic belt grinding

Characterization of surface integrity of 7075-T6 aluminum alloy subjected to microbiologically induced corrosion during high-speed machining

Microbiologically Influenced Corrosion (MIC) is one of the primary causes of corrosion damage and equipment failure in industrial environments. This paper aims to investigate the impact of microbiologically influenced corrosion on the surface integrity of 7075-T6 aluminum alloy. Through experiments involving cryogenic treatment and machining, the study systematically compares the effects of different microbiologically influenced corrosion environments on 7075-T6 aluminum alloy. Techniques such as X-ray Diffraction (XRD), surface roughness measurement, Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and work hardening were used to elucidate the influence of natural seawater (Planktonic microorganisms, PM) and marine sediment (Benthic microorganisms, BM) corrosion on the surface integrity of 7075-T6 aluminum alloy.The results indicate that, compared to PM corrosion, BM corrosion results in a smaller surface roughness of 7075-T6 aluminum alloy. Specifically, the BM-10d specimen exhibits the smallest roughness at 0.353 μm. XRD and EDS analyses show that the corrosion products after microbiological corrosion are primarily a mixture of Al2O3, AlO(OH), and Al(OH)3. The peak intensity of AlO(OH) in the (200) crystal plane of the BM-5d corrosion product is notably higher than that of the 7075-T6 aluminum alloy under other conditions. In the PM environment, the corrosion products fully cover the entire surface of the workpiece and are accompanied by significant cracking. In contrast, in the BM environment, the corrosion products mainly exhibit a granular structure, are scattered across the workpiece surface, and the exposed substrate can be observed.The microhardness of the aluminum alloy after microbiological corrosion shows a trend of increasing initially, then decreasing, and finally stabilizing. The maximum depth of the hardened layer for PM-10d is 120 μm, with a maximum hardness of 178.74 HV. Compared to PM corrosion, BM corrosion results in a significantly greater hardened layer depth for 7075-T6 aluminum alloy, with the BM-10d hardened layer depth reaching approximately 140 μm and the peak hardness at 185.36 HV. Additionally, in the BM environment, the precipitates are fewer compared to those in the PM environment and exhibit a non-continuous, non-grain-boundary precipitation band.

Lap joining of Ti6Al4V titanium alloy by vortex flow-based friction stir welding

The current study uses a novel vortex flow-based friction stir lap welding (VFSLW) process to weld 1.4 mm thick Ti6Al4V sheets, trying to replace the diffusion bonding in the superplastic forming/diffusion bonding process. The mechanical properties and joining mechanism of the VFSLW joint were investigated. Good weld formation was obtained at 300–350 rpm and 80 mm/min. No hook defect was formed in the lap interface. The lap joint fractured across the stir zone (SZ) in the top plate under the optimal parameters. The cracks initiated from the oxidation defect, where the oxides on the workpiece surface were involved in the SZ by the vortex during the welding. It suggests that a good argon shield is very important for the VFSLW of titanium alloy. The highest tensile strength reaches ~890 MPa, up to 95 % of the base material. The formation of an α + β lamellar structure in the SZ is due to the peak welding temperature exceeding the β-transus temperature. In the bonded zone (BZ), a very thin layer with ultrafine α grains was formed by dynamic recrystallization in the α phase field, although its two sides are α + β lamellar structures. This is because of the oxidation on the workpiece surface during the welding process and the O element is a strong α stabilizer.

The capability of Acoustic Emission features to monitor diamond-coated burr grinding wear and effectiveness

Within manufacturing there is a growing need for autonomous Tool Condition Monitoring (TCM) systems, with the ability to predict tool wear and failure. This need is increased, when using specialised tools such as Diamond-Coated Burrs (DCBs) for grinding high strength ceramics or glass, in which the random nature of the tool, inconsistent manufacturing methods and high wear rates create large variance in tool life. This unpredictable nature leads to a significant fraction of a DCB tool's life being underutilised due to premature replacement. Workpiece surface damage, increased grinding forces and large-scale diamond grain pullout could all be the result of high levels of runout and in-circularity common within electroplated DCBs. As such it is important to not only monitor the overall tool wear but also tool condition. Acoustic Emission (AE) presents as an indirect on-machine sensing method highly suited to grinding applications. The high frequency range of AE, >20 kHz, prevents machine noise from dominating the acquired signals, isolating the micro-scale machining processes within noises machine environments. AE resulting from the grinding process has the potential to monitor not only tool wear but also runout and circularity. A series of DCB wear tests have been conducted, each consisting of the continuous acquisition of AE during grinding and frequent tool surface measurements. Preliminary results demonstrate AE kurtosis can be seen as an indicator of each tool’s runout, representing the fraction of time the tool and workpiece are in contact during a revolution. As a result, an indirect monitoring system capable of monitoring wear and tool state with AE could be utilised within the manufacturing sector.

Recent Patents for Optical Component Polishing Technology

Background: Fluid jet polishing, Airbag polishing, Magnetorheological polishing, and Ion beam polishing are all emerging polishing technologies commonly used for processing optical components, which can be used to manufacture various high-precision and high-quality optical components. Their processing mechanisms are to remove materials by high-speed jet impacting the surface of the workpiece; using a spherical flexible airbag as a polishing tool to obtain a super-smooth surface by adding polishing fluid containing fine abrasives; controlling the magnetic field to form a flexible polishing belt of Magnetorheological fluid, which undergoes relative motion to achieve material removal; using a neutral ion beam to bombard the surface of the workpiece to remove workpiece surface atoms and obtain a super-smooth surface through energy and momentum transfer between ions and workpiece atoms. The characteristics and removal mechanisms of various polishing methods are briefly described, and the advantages and key issues that need to be addressed for each polishing technology are pointed out, and suggestions and prospects for future research, application, and development are also given. Objective: In order to meet the growing demand for high-precision optical components and mass-manufactured optical components, this paper aims to study the various polishing technologies that are continuously improved and suggestions are made for future research and development directions. Method: This paper reviews the current patents related to various polishing technologies, such as Fluid jet polishing, Airbag polishing, Magnetorheological polishing and Ion beam polishing and other representative polishing technologies. Results: Various types of polishing technologies have been studied, and the main problem at the current stage is the lack of accuracy. The problem of the polishing device, such as fluid jet polishing, only considers the change of fluid velocity and pressure to construct the removal function model for analysis and summary, and suggestions for the latest research progress of various polishing technologies are given. Conclusion: The improvement and optimization of polishing technology are beneficial to improving the polishing accuracy and quality of optical components and have great help for the future development of related patents.

Technological support of workpiece surface quality based on local cryogenic impact during processing of austenitic steels

Technological support of workpiece surface quality based on local cryogenic impact during processing of austenitic steels

Optimization of Material Removal Rate and Wear Rate in EDM Machining of Inconel 625 Using a Novel Nano Al-Ni Composite Electrode: A Response Surface Methodology Approach

The electric discharge machine is a novel machining technique. When the tool and the work item do not communicate. Components composed of difficult-to-machine hard materials. In the current experimental inquiry, the process factors that influence the machining concert process and its effectiveness are explored. The response table for each set of machining limitations is used in conjunction with the response surface methodology in the research to determine the appropriate levels of machining factors. The work's machining input parameters are optimized for maximum material removal rate (MRR) and reduce the electrode wear rate (EWR) when electro-discharge machining Inconel 625 using the tool Nano Al-Ni composite electrode. Another analysis of variance is to identify the factors causing the different answers mentioned above. EDAX was also used to investigate the material composition of the workpiece. Machined workpiece surfaces were evaluated using scanning electron microscopy to assess surface accuracy and microstructural characteristics (SEM). The following conclusions may be drawn from this work. The MRR parameter that is most affected is pulse off time. As pulse-off time lengthens, MRR increases. According to the response graph, the greatest MRR value that can be attained under the ideal parameters of Ip = 8A, T-ON = 50μs, and T-OFF= 100μs is 0.0115 g/min. The magnitudes of MRR range from 0.0091 to 0.044 g/min. Impact of T ON and T OFF: Higher EWR is 0.0022 g/min is seen in runs with T ON = 70 μs and T OFF = 100 μs.