Grinding Wheel Research Articles

Grinding wheel specification cybernetic recommendation with multi-task multi-imbalanced learning in smart manufacturing system

Over the years, the grinding wheels industry has played a crucial role in mechanical engineering. Grinding wheel specification is composed of various factors such as abrasive type, wheel grade, bond type, and more, which are derived from customer workpiece operation information. Traditionally, the determination process of grinding wheel specifications is complicated. Experienced engineers need to check out the limitation and consider the interaction of each factor. When the new specification order comes, engineers have to spend a lot of time on historical data search and discussion. Recently, the application of artificial intelligence attracts more and more attention in the manufacturing industry. Through collecting historical data, the model has the ability to extract the domain knowledge, predict the specification that does not exist, and reduce the decision time. However, when training the model, this grinding wheel specification faced multiple imbalanced targets and multi-task issues. In the past, research efforts primarily focused on studying single-task learning (STL) algorithms. Seldom of them has a systematic way to discuss the model determination of multiple targets and correlation influence, especially on the tabular-type dataset. In this study, we proposed a multiple resampling chain multi-task learning framework to address the issue of data science. To tackle the multi-task imbalance resampling problem, we also proposed a resampling strategy called Multiple Resampling Chain. Moreover, we conducted a sensitivity analysis to examine the correlation effect on model improvement. Finally, we proposed a cyber-recommendation system that integrates the training model and interface to provide a more intuitive way of specification prediction. This system not only can help engineers to improve the time spent on making decisions, but also make the whole manufacturing process to be more intelligent.

Research on chip flute design of variable pitch variable helix end milling cutter based on manufacturability

In this paper, a design method of chip flute structure of variable pitch variable helix (double variable) end milling cutter based on manufacturability is presented, which aims to improve the dynamic balance and milling performance of the tool. The feasible region for grinding the chip flute of a double variable end milling cutter is obtained by solving the numerical model for the shape of the radial cross-section curve of the chip flute, along with the position and orientation of the grinding wheel. The multiple tool-walking grinding method is proposed to avoid the interference and edge cutting between the grinding wheel profile and the chip flute section, and the chip flute structure design criterion is obtained. The error between the grinding simulation results and the design target parameters is about 1 %, which verifies the effectiveness of the design criteria. With the double variable end milling cutter designed by this criterion, the milling vibration amplitude is reduced by about 21 %, and the average surface roughness of the workpiece is reduced by 9.872 μm. The chip flute structure design method proposed in this paper not only meets the manufacturing feasibility, but also effectively improves the milling performance of the tool. On the premise of considering manufacturability, the design method of chip flute as the optimization objective provides a new idea for tool structure design.

Wheel–Ground Interaction Test for Sugarcane Cargo Transshipments

Wheel–Ground Interaction Test for Sugarcane Cargo Transshipments

Fabrication and Application of Grinding Wheels with Soft and Hard Composite Structures for Silicon Carbide Substrate Precision Processing.

In silicon carbide processing, the surface and subsurface damage caused by fixed abrasive grinding significantly affects the allowance of the next polishing process. A novel grinding wheel with a soft and hard composite structure was fabricated for the ultra-precision processing of SiC substrates, and the grinding performance of the grinding wheel was assessed in this study. Different types of gels, heating temperatures, and composition ratios were used to fabricate the grinding wheel. The grinding performance of the grinding wheel was investigated based on the surface integrity and subsurface damage of SiC substrates. The results showed that the grinding wheel with a soft and hard composite structure was successfully fabricated using freeze-dried gel with a heating temperature of 110 °C, and the component ratio of resin to gel was 4:6. A smooth SiC substrate surface with almost no cracks was obtained after processing with the grinding wheel. The abrasive exposure height was controlled by manipulating the type and ratio of the gel. Furthermore, the cutting depth in nanoscale could be achieved by controlling the abrasive exposure height. Therefore, the fabrication and application of the grinding wheels with soft and hard composite structures is important for the ultra-precision processing of large-size SiC substrates.

Profile Optimisation of a Solid Modular Hob in the Machining of Gears Made of Classic and Unusual, Innovative Materials.

Modular hobs are tools with very complex geometry. Regardless of the material of the gear wheels, they determine the accuracy of the gears made in the hobbing machining process. Gears are made of various, often innovative materials depending on the requirements. Sometimes, the materials are characterised by very high hardness (over 65 HRC). The mathematical basis for describing the faces of a hob presented in the article allows for modifying the rack profile shaping the gear wheel's teeth. The model's universality makes it possible to perform numerical simulations of the influence of individual parameters of the hob creation process (geometry of the grinding wheels and their setting in the shaping process) on the profile of the rake and flank surfaces. The cutting edge (rack edge) is the locus of points belonging to both of these surfaces and thus directly impacts the accuracy of the gear wheel that is shaped in the hobbing process. The article summarises the authors' long-term cooperation with the industry, resulting in a series of articles devoted to hobs. The issues presented in the article are significant to the machinery industry and hob manufacturers.

Surface topography prediction of slider races using formed grinding wheel shape and material removal mechanism

Compared with the roughness, the three-dimensional (3D) topography parameters, surface microstructure geometric characteristics and other information can more fully evaluate the grinding quality of the slider raceway surface. In this paper, based on the 3D topography model of the abrasive particle distribution on the surface of the formed grinding wheel, the material removal mechanism between the abrasive particle and the raceway surface is analyzed. With the undeformed chip thickness distribution model as the intermediate variable, the 3D topography model of the slider raceway surface is established, and the model verification is carried out from the roughness and the geometric characteristics of the surface microstructure, respectively. At the same time, the surface microstructure is extracted from the topography model, and the effects of different grinding process parameters on the geometric characteristics such as the height to width ratio, depth to width ratio and distribution density of groove, convex peak and peak valley structures are studied. Results are shown that AS,TH increase from [0.05 0.6 μm] to [0.25 0.8 μm] and FGH grows from [0.11 1.05 μm] to [0.5 1.61 μm] when the grinding depth rises from 1 μm to 4 μm. AS, TH are firstly decreased from [0.17 0.61 μm] to [0.08 0.52 μm] and then increased to [0.26 0.78 μm], and the FGH declines from [0.34 1.01 μm] to [0.16 0.86 μm] and then increases to [0.51 1.38 μm] with the feeding speed is in [25, 28 m/min]. In addition, in the range of grinding wheel linear velocity [28, 34 m/s], the AS,TH decreases from [0.19 0.81 μm] to [0.1 0.55 μm] and the FGH decreases from [0.55 1.6 μm] to [0.2 1.1 μm]. This can prepare for the subsequent research on the impact of the topography characteristics on the friction coefficient and wear amount of the slider raceway surface.

A Method for Identifying the Wear State of Grinding Wheels Based on VMD Denoising and AO-CNN-LSTM

Monitoring the condition of the grinding wheel in real-time during the grinding process is crucial as it directly impacts the precision and quality of the workpiece. Deep learning technology plays a vital role in analyzing the changes in sensor signals and identifying grinding wheel wear during the grinding process. Therefore, this paper innovatively proposes a grinding wheel wear recognition method based on Variational Mode Decomposition (VMD) denoising and Aquila Optimizer—Convolutional Neural Network—Long Short-Term Memory (AO-CNN-LSTM). The paper utilizes Acoustic Emission (AE) signals generated during grinding to identify the condition of the grinding wheel. To address noise interference, the study introduces the VMD algorithm for denoising the sample dataset, enhancing the effectiveness of neural network training. Subsequently, the dataset is fed into the designed Convolutional Neural Network—Long Short-Term Memory (CNN-LSTM) structure with AO-optimized parameters. Experimental results demonstrate that this method achieves high accuracy and performance.

A Real-Time Dual-Task Defect Segmentation Network for Grinding Wheels with Coordinate Attentioned-ASP and Masked Autoencoder

The current network for the dual-task grinding wheel defect semantic segmentation lacks high-precision lightweight designs, making it challenging to balance lightweighting and segmentation accuracy, thus severely limiting its practical application in grinding wheel production lines. Additionally, recent approaches for addressing the natural class imbalance in defect segmentation fail to leverage the inexhaustible unannotated raw data on the production line, posing huge data wastage. Targeting these two issues, firstly, by discovering the similarity between Coordinate Attention (CA) and ASPP, this study has introduced a novel lightweight CA-ASP module to the DeeplabV3+, which is 45.3% smaller in parameter size and 53.2% lower in FLOPs compared to the ASPP, while achieving better segmentation precision. Secondly, we have innovatively leveraged the Masked Autoencoder (MAE) to address imbalance. By developing a new Hybrid MAE and applying it to self-supervised pretraining on tremendous unannotated data, we have significantly uplifted the network’s semantic understanding on the minority classes, which leads to further rises in both the overall accuracy and accuracy of the minorities without additional computational growth. Lastly, transfer learning has been deployed to fully utilize the highly related dual tasks. Experimental results demonstrate that the proposed methods with a real-time latency of 9.512 ms obtain a superior segmentation accuracy on the mIoU score over the compared real-time state-of-the-art methods, excelling in managing the imbalance and ensuring stability on the complicated scenes across the dual tasks.

Analysis of Grindability and Surface Integrity in Creep-Feed Grinding of High-Strength Steels.

Creep-feed grinding of high-strength steel is prone to excessive wheel wear and thermal damage defects, which seriously affects the service performance of parts. To solve the above-mentioned issue, a creep-feed grinding test was carried out on high-strength steel using SG and CBN abrasive wheels. The grindability of high-strength steel was scrutinized in terms of grinding force, machining temperature and grinding specific energy. Moreover, the effects of operation parameters and grinder performances on the surface integrity of the workpiece such as surface morphology, roughness, residual stress and hardness were rigorously studied. The results indicate that, when the instantaneous high temperature in the grinding area reaches above the phase transition temperature of the steel, the local organization of the surface layer changes, leading to thermal damage defects in the components. The outstanding hardness and thermal conductivity of CBN abrasives are more productive in suppressing grinding burns than the high self-sharpening properties of SG grits and a more favorable machining response is achieved. The effects of thermal damage on the surface integrity of high-strength steel grinding are mainly in the form of oxidative discoloration, coating texture, hardness reduction and residual tensile stresses. Within the parameter range of this experiment, CBN grinding wheel reduces grinding specific energy by about 33% compared to SG grinding wheel and can control surface roughness below 0.8 µm. The weight of oxygen element in the burn-out workpiece accounts for 21%, and the thickness of the metamorphic layer is about 40 µm. The essential means of achieving burn-free grinding of high-strength steels is to reduce heat generation and enhance heat evacuation. The results obtained can provide technical guidance for high-quality processing of high-strength steel and precision manufacturing of high-end components.

An Investigation of the Efficient-Precise Continuous Electrochemical Grinding Process of Ti-6Al-4V.

Titanium alloys have many excellent characteristics, and they are widely used in aerospace, biomedicine, and precision engineering. Meanwhile, titanium alloys are difficult to machine and passivate readily. Electrochemical grinding (ECG) is an ideal technology for the efficient-precise machining of titanium alloys. In the ECG process of titanium alloys, the common approach of applying high voltage and active electrolytes to achieve high efficiency of material removal will lead to serious stray corrosion, and the time utilized for the subsequent finishing will be extended greatly. Therefore, the application of ECG in the field of high efficiency and precision machining of titanium alloys is limited. In order to address the aforementioned issues, the present study proposed an efficient-precise continuous ECG (E-P-C-ECG) process for Ti-6Al-4V applying high-pulsed voltage with an optimized duty cycle and low DC voltage in the efficient ECG stage and precise ECG stage, respectively, without changing the grinding wheel. According to the result of the passivation properties tests, the ideal electrolyte was selected. Optimization of the process parameters was implemented experimentally to improve the processing efficiency and precision of ECG of Ti-6Al-4V. Utilizing the process advantages of the proposed process, a thin-walled structure of Ti-6Al-4V was obtained with high efficiency and precision. Compared to the conventional mechanical grinding process, the compressive residual stress of the machined surface and the processing time were reduced by 90.5% and 63.3% respectively, and both the surface roughness and tool wear were obviously improved.

Modeling and validation of the grinding morphology of ordered diamond grinding wheel

Modeling and validation of the grinding morphology of ordered diamond grinding wheel

Characterization and Analysis of Inconel 718 Alloy Ground at Different Speeds

Inconel 718 (IN718) alloy is widely applied to fabricate high temperature resistant or corrosion resistant parts due to its excellent mechanical performance. However, the machining of IN718 alloy is difficult as it may cause serious tool wear and poor surface quality (SQ) of the workpiece. In this work, grinding experiments on IN718 alloy at different speeds were conducted by using a CBN grinding wheel. The relationship between grinding speed, SQ and subsurface damage (SSD) was well studied. With increasing grinding speed, surface roughness decreased, and SQ was greatly improved. Meanwhile, the microhardness of the grinding surface declined as the grinding speed increased. The SSD depth was almost unchanged when the grinding speed was lower than 15 m/s, then it decreased with higher grinding speeds. It was attributed to the mechanical-thermal synergistic effect in the grinding process. The results indicated that increasing grinding speed can effectively improve the SQ and reduce the SSD of IN718 alloy. The conclusion in the work may also provide insight into processing other hard-to-machining materials.

Investigation of the Machined Surface Integrity of WC-High-Entropy Alloy Cemented Carbide

A fine-grained WC-15wt%Al0.5CoCrFeNi cemented carbide was prepared through a vacuum and gas pressure sintering. For achieving high surface integrity, diamond wheel grinding serves as the primary molding process for the machining of WC cemented carbide. To reveal the influence of grinding on the surface integrity of fine-grained WC-HEA cemented carbide, studies were conducted on grinding force, surface microstructure, surface roughness, residual stress, microhardness, and bending strength. The morphological analysis of the ground surface indicated a transition in the material removal mechanism of WC-HEA cemented carbide from ductile removal to brittle removal, with brittle removal becoming predominant as the depth of grinding increases. With the increasing depth of grinding, the grinding force increases, and the grinding force increases while the surface roughness decreases. Correspondingly, there is an improvement in both hardness and bending strength. Additionally, grinding induces high residual compressive stress on the surface, with a maximum compressive stress of 1795 MPa. The bending strength of the material is found to be dependent on the residual stress.

Grinding performance investigation of multidirectional CF/PEEK composites—A comparative with unidirectional CF/PEEK

AbstractTo distinguish the grinding performance of the multidirectional (MD) and unidirectional (UD) carbon fiber‐reinforced thermoplastic (CFRTP) composites, MD and UD carbon fiber‐reinforced poly‐etherether‐ketone (CF/PEEK) composites were employed in this study. Different ply stacking sequences and process parameters were set for grinding experiments. Subsequently, the surface morphologies and roughness were observed and measured. Experimental results indicated that the variations of grinding forces with grinding parameters of MD‐CF/PEEK and UD‐CF/PEEK were consistent. However, the heat transfer mechanism and the effects of grinding parameters on the maximum grinding temperatures were different between the two composites. The grinding forces and temperatures of MD‐CF/PEEK were slightly lower than UD‐CF/PEEK, and MD‐CF/PEEK reached better surface quality under the same parameters, indicating that the grinding performance of MD‐CF/PEEK was not the simple superposition of UD‐CF/PEEK. In addition, the chip formation and material removal mechanism of CF/PEEK were investigated. The grinding performance of MD‐CF/PEEK was primarily dependent on the θ elements of laminate while the grinding performance of UD‐CF/PEEK was closely related to the fiber orientation angles during grinding. This study established a more in‐depth understanding into the grinding performance of MD‐CF/PEEK and provided technical guidance for high‐quality grinding of CFRTP.Highlights The grinding performance of the multidirectional (MD) and unidirectional (UD) carbon fiber‐reinforced poly‐etherether‐ketone (CF/PEEK) is compared. The grinding forces and temperatures of MD‐CF/PEEK are slightly lower than that of UD‐CF/PEEK, and the MD‐CF/PEEK reach a better surface quality under the same grinding parameters. The grinding performance of MD‐CF/PEEK is primarily dependent on the θ elements of laminate, and the change of layering order is not a critical factor. The grinding performance of UD‐CF/PEEK is closely related to the fiber orientation angles during the grinding process. The surface quality of MD‐CFRTP can be effectively improved by reducing the grinding depth and feed speed, and increasing the grinding wheel speed.

Shaping the Topography of the Active Surface of a Ceramic Grinding Wheel with a Stationary Multi-Point Diamond Dresser

Shaping the Topography of the Active Surface of a Ceramic Grinding Wheel with a Stationary Multi-Point Diamond Dresser

A Grinding Method with an Innovative, Efficient, and Weight-Saving Design for Double Helical Gears

Grinding technology exerts an enormous effect on the surface quality of double helical gears, which are subject to stringent requirements in the aviation industry. This study presents a novel gear-gap-space-borrowing grinding method that diverges from existing techniques. Unlike conventional approaches, this method mitigates the design–manufacturing conflict by exploiting the opposing gear gap space. By borrowing space, the grinding wheel’s size can be enlarged to enhance machinability, diminish the width of the undercut, and align with the lightweight design imperative of double helical gears. The relationship between the grinding wheel diameter and the design parameters of double helical gears is analytically established, leading to the formulation of design rules. These rules facilitate the rapid selection of appropriate grinding wheel sizes for the space-borrowing method. Additionally, through geometric modeling and experimental validation, the optimal gear undercut width and the maximum wheel diameter are determined. The validity and accuracy of the proposed method are verified by simulations and experimental investigations. The study quantitatively evaluates the benefits of this method, including the expansion of the grinding wheel size, the reduction in double helical gear weight, and enhancements in processing efficiency and quality, providing a comprehensive comparison and discussion of these improvements.

Enhancing reliability of failure modes and effects analysis dealing with linguistic distribution assessments: A consistency based approach

Failure modes and effects analysis is a proactive reliability-management engineering technique, it has been applied to improve reliability of processes, products, and services. Traditional failure modes and effects analysis method manifests three deficiencies with regard to form of risk assessments, determination of risk factor weights, and exploitation of failure modes’ risk levels. Although numerous studies have contributed to surmount these deficiencies, existing failure modes and effects analysis methods still face such issues. Moreover, a novel drawback has raised when failure modes and effects analysis participants adopt linguistic terms as risk assessments of failure modes, the reliability of linguistic distribution assessments as well as failure modes and effects analysis groups (participants with similar knowledge background are previously classified into a failure modes and effects analysis group) is overlooked. Therefore, this paper introduces the transformation of linguistic distribution assessments into fuzzy preference relations, as more effective modeling for investigating consistency, by using the newly defined possibility degrees of linguistic distribution assessments will be applied to devise four algorithms for enhancing reliability of assessments. Hence, the three deficiencies of traditional failure modes and effects analysis method are solved by means of a novel failure modes and effects analysis framework. Finally, a real example with respect to ranking failure modes of worm wheel grinding machine is developed to verify the performance and advantages of the proposed method, in which ten failure modes are ranked and the one with the highest risk level is selected, and consistency of risk assessments is improved to be acceptable.

Design and Analysis of a Lunar Crewed Vehicle With a Novel Versatile Compliant Suspension Mechanism

Abstract A lunar crewed vehicle (LCV) with improved maneuverability, mobility, and ride comfort is required for astronauts to conduct long-range scientific investigations and resource utilization on the Moon’s surface. This paper concentrates on designing a novel multi-functional compliant suspension for LCV to improve the above-mentioned performance. First, based on the requirement of high-speed traversing on the rough Lunar terrain, the required type of suspension motion is identified and the demanded suspension mechanism is obtained through structural evolution. Then, the kinematic analysis of the proposed suspension mechanism is conducted, and the steering kinematic model of the whole vehicle is established. A compliance analysis is completed, taking into account the actual design characteristics of the suspension mechanism. A multi-degrees-of-freedom dynamics model of the vehicle is developed, considering both wheel–ground separation and the deformation of wheels and soil. Simulations are conducted to verify full vehicle performance with the proposed suspension, and the results reveal that the design features better mobility and comfort in rough terrain with minimum turning radius, peak longitudinal acceleration, and root mean square reduced by 9.5%, 45.1%, and 21.4%, respectively.

Non-linear diamond material removal at increased sliding velocities in ultra-precision grinding

Single crystal diamond machining primarily relies on mechanical grinding, traditionally guided by the simplistic concept of a linear removal rate. However, this conventional approach lacks precision in predicting the resultant shape. This comprehensive study delves into the influence of sliding speed on the material removal rate during the mechanical grinding of diamond, leveraging both theoretical frameworks and experimental exploration. Initially, the impact of sliding velocity is meticulously scrutinized by considering the contact frequency between the diamond and grinding wheel grits, as well as the depth associated with the brittle-ductile transition of diamond material. Subsequently, a model quantifying the effect of sliding velocity is meticulously formulated and rigorously tested through experimentation. The findings of this investigation not only affirm the validity of the theoretical analyses but also underscore the remarkable predictive accuracy of the sliding velocity effect model. These results, situated at the intersection of theory and practice, offer invaluable insights with profound implications for enhancing the efficiency and precision of single crystal diamond machining processes.

An optimized calculation method of the grinding wheel profile for the helical flute forming grinding

An optimized calculation method of the grinding wheel profile for the helical flute forming grinding