ObjectivesPolycrystalline diamond (PCD) blades are widely used in precision machining and high-speed machining. However, as a high-hardness and brittle material, PCD has a more complex material removal mechanism compared to other materials, making it prone to surface defects and edge chipping during the grinding process. These defects increase the cutting force and cutting deformation of PCD blades. Furthermore, these defects are geometrically replicated on the machined surface, thereby affecting the machining accuracy of the workpiece and shortening the blade's service life. This paper aims to improve grinding quality by investigating the optimal process parameters for grinding PCD blades.MethodsBased on the floating grinding process, the orthogonal experimental method is employed to investigate the influence of diamond grinding wheels, PCD diamond particle size, grinding wheel speed, and table tuning pressure on the workpiece grinding quality. The cutting edge radius, cutting edge defect, and flank roughness are used as evaluation indicators for the PCD tool grinding quality to optimize the grinding process parameters. High-definition microscopy, scanning electron microscopy, and surface profilometry are utilized to observe the PCD tools and conduct an in-depth study of the material removal mechanism.ResultsConclusions are derived through meticulous analysis of the experiments, which reveals that the PCD composite flake particle size exerts a substantial influence on the flank roughness, cutting edge radius, and cutting edge defect of PCD blades. Furthermore, the cutting edge defect and flank roughness of PCD blades are found to be significantly influenced by the use of diamond grinding wheels. Additionally, the table tuning pressure is found to have a substantial impact on the cutting edge radius. The removal mechanism of PCD blades is principally based on brittle removal, with plastic removal playing a supplementary role. The process of brittle removal in PCD blades encompasses a variety of mechanisms, including crushing along the crystal, through the crystal, deconstruction, and scaling removal.ConclusionsBy combining the influence patterns of grinding process parameters on tool grinding quality, the optimal process parameters are obtained. Under the conditions of a 6/8 metal-based grinding wheel, CMX850 composite sheet, a grinding wheel speed of 1 000 r/min, and a table tuning pressure of 151 N, the blade's cutting edge defect is 2.45 μm, the cutting edge radius is 3.28 μm, and the flank roughness is 0.015 μm. Moreover, under these conditions, the proportion of material undergoing plastic removal is significantly higher than under other process conditions, and the resulting surface quality of the PCD tool is relatively smooth.
ObjectivesTo address the low drilling efficiency and frequent "bit balling" or slipping issues encountered by conventional impregnated diamond bits when drilling through hard, dense, and weakly abrasive formations characterized by rock Mohs hardness exceeding 7 in a major hydropower project exploration area in Tibet, this study aims to design an innovative impregnated diamond bit featuring a multi-stage matrix block with helical distribution structure. The core objective is to enhance the proportion of volumetric rock fragmentation by modifying the bit-rock interaction mechanism, thereby improving the rate of penetration and drilling efficiency in such challenging formations. The research focuses on elucidating the rock fragmentation mechanism of the novel bit and optimizing its key structural parameters through finite element simulation, providing a new technical approach for drilling difficulties in these formations.MethodsFirstly, based on the rock fragmentation principle of impregnated diamond bits, a bit with a multi-stage helically distributed matrix block structure was designed from the perspective of increasing rock fracture free surfaces and inducing volumetric fragmentation. The innovation lies in the bit face configuration, where wear-resistant spiral matrix blocks and weakened ordinary matrix are alternately arranged, forming a unique helical pattern. Additionally, annular gauge blocks are set at the inner and outer diameters of the bit to ensure drilling stability. Based on theoretical analysis of its rock fragmentation mechanism including ridge formation, increased free surfaces, and radial thrust action, finite element simulation using Abaqus software was employed to optimize the bit structural parameters. The Drucker-Prager model was selected as the rock constitutive model to simulate elastoplastic deformation and progressive damage failure processes of rock. Taking the block-to-slot ratio (the ratio of spiral block thickness to inter-block slot width) as the key variable, the force and torque characteristics of five bit types with block-to-slot ratios of 1∶0, 1∶1, 1∶2, 1∶3, and 1∶4 were comparatively analyzed under fixed conditions of 1.5 mm block thickness, 6 mm/s penetration rate, and 6 r/s rotational speed. Based on this, internal and external gauge structures were further introduced to comparatively analyze the mechanical responses of bits with different gauge parameters, determining the optimal bit face structure combination.ResultsThe simulation results indicate that: (1) Without gauge structure, the reaction force on the bit in the z-axis (drilling direction) decreases as the block-to-slot ratio reduces, being maximum at 1∶0 and minimum at 1∶4, with no significant differences among the reaction forces at ratios of 1∶2, 1∶3, and 1∶4. (2) Regarding torque, the z-axis torque on the bit is maximum at a block-to-slot ratio of 1∶1 and minimum at 1∶2; the z-axis torques on bits with ratios of 1∶2, 1∶3, and 1∶4 are all lower than those on bits with ratios of 1∶0 and 1∶1, with no significant differences among the three. (3) All helically arranged bits exhibit significant eccentric forces and eccentric torques in the x and y axes directions, while such eccentric phenomena are not pronounced for the flat-bottom bit with a ratio of 1∶0. (4) The addition of gauge structures increases the bit face area, leading to a certain increase in z-axis reaction force, but shows no significant effect on z-axis torque. However, the incorporation of gauge structures significantly reduces the eccentric forces and eccentric torques on the bit in the x and y axes directions, effectively enhancing drilling stability.ConclusionsThis study has successfully designed an impregnated diamond bit with multi-stage helically distributed matrix blocks, and verified through simulation its feasibility for application in hard, dense, and weakly abrasive formations. The research reveals the mechanism by which the helical arrangement structure enhances rock fragmentation efficiency through inducing ridge formation and volumetric fragmentation. The optimal bit face structural parameters are determined as follows: spiral block thickness of 1.5 mm, inter-block slot spacing of 4.5 mm (corresponding to a block-to-slot ratio of 1∶2) or 4.0 mm, and gauge block thickness of 1.5 mm. This parameter combination can reduce the reaction force and torque required for drilling while effectively controlling eccentric loads, achieving a balance between drilling efficiency and stability. The innovation of this study lies in introducing the helical distribution concept into the matrix block design of impregnated diamond bits, addressing the hard rock slipping problem by altering the bottom-hole stress field and increasing volumetric fragmentation, rather than simply relying on contact area reduction.
Objectives:Diamond,renowned for its exceptional hardness,high thermal conductivity,remarkable wear resistance,and chemical inertness,has become indispensable in the cutting of semiconductor materials such as silicon carbide(SiC),sapphire,and gallium nitride.As demand for these advanced materials grows in the electronics and optoelectronics industries,the performance requirements for cutting tools become increasingly stringent.This paper aims to provide a systematic review of the current state of three primary diamond wire saw preparation technologies:electroplating,resin bonding,and brazing.The objective is to critically analyze and compare these fabrication methods,elucidating their respective principles,advantages,limitations,and influence on cutting performance across different applications.Furthermore,by identifying key technical challenges,this review proposes viable directions for future research and process optimization to enhance the comprehensive performance of diamond wire saws.Methods:This study undertakes a thorough review of existing literature,encompassing key research findings from both domestic and international academic sources.The methodology involves a structured comparative analysis of the three preparation technologies,examining their specific technical characteristics,including base wire materials,bonding mechanisms between diamond abrasives and the substrate,diamond grit properties(size,shape,concentration,and surface condition),preparation apparatus,and critical process parameters.Beyond technical description,this review analyzes the performance of the resulting wire saws during actual cutting operations,evaluating key indicators such as cutting efficiency,surface quality of sliced wafers,tool wear mechanisms,lifespan,and cutting stability.By correlating manufacturing parameters with performance outcomes,the primary factors influencing the efficacy of each wire saw type are identified and discussed.Results:Electroplated diamond wire saws,owing to their mature and well-established preparation process achieve large-scale industrial application in cutting materials such as photovoltaic silicon crystals,sapphire,and marble.However,a significant limitation lies in the relatively low bonding strength between the diamond grits and the substrate,which restricts the tool's lifespan and cutting efficiency when processing high-hardness materials like silicon carbide(SiC)and sapphire.Nevertheless,their inadequate heat resistance and wear resistance constrain their applicability in high-speed cutting scenarios.In contrast,brazed diamond wire saws achieve substantially enhanced bonding strength through a metallurgical bond between the diamond and the matrix.This results in superior cutting performance and durability compared to the other two technologies.Despite these advantages,the brazing process itself presents technical bottlenecks,notably thermal damage to the diamond grits,such as graphitization,and a decline in the mechanical properties of the base wire,necessitating further research and process optimization.Conclusions:Diamond wire saw technology evolves along three distinct paths,each offering unique advantages and limitations that determine suitability for specific cutting tasks.Electroplated saws dominate current industrial practice due to maturity and low cost but are performance-limited by low bond strength for ultra-hard materials.Resin-bonded saws provide flexibility and good surface finish but are constrained by poor thermal stability.Brazed saws offer the highest theoretical performance due to superior metallurgical bonding but face challenges related to thermal damage to both the diamond and the wire substrate.Future research should focus on overcoming these barriers:for brazed wires,developing novel filler alloys with lower melting points to mitigate thermal damage and implementing advanced thermal management strategies;for electroplated and resin-bonded wires,exploring composite matrices and modified resins with enhanced thermal conductivity.Through these targeted improvements,the comprehensive performance of diamond wire saws can be significantly elevated to meet the increasing demands of advanced material processing industries.
SignificanceCutting tools are indispensable key instruments in the manufacturing industry, whose performance status directly affects machining quality, production efficiency, and equipment safety. Accurate prediction of the remaining useful life (RUL) of tools not only enables the intelligent transition from "scheduled replacement" to "condition-based replacement" but also significantly reduces resource waste caused by premature tool changes, workpiece scrapping and even equipment damage risks due to delayed replacement. With the deep integration of industrial automation, digitalization, and smart manufacturing, tool RUL prediction has become one of the core technologies in intelligent manufacturing and predictive maintenance, holding substantial engineering application value and theoretical research significance for enhancing the overall competitiveness of the manufacturing industry.ProgressThis paper systematically reviews the research progress in methods for predicting the remaining useful life of cutting tools. Based on their prediction principles, these methods are categorized into four main types, and their modeling ideas, applicable scenarios, advantages, and disadvantages are analyzed in depth. (1) Physics-based model prediction methods: These methods start from the physical mechanisms of tool wear, constructing mathematical models to describe the wear process, such as wear mechanism models, cutting force coefficient models, and finite element models. Their advantage lies in having clear physical significance and strong interpretability, making them particularly suitable for stable machining processes with well-understood mechanisms. However, these methods rely on accurate modeling of multiple physical fields in complex machining environments, face difficulties in parameter identification, and exhibit weak adaptability to dynamically changing working conditions. (2) Data-driven statistical model prediction methods: These methods do not rely on physical mechanisms but instead analyze historical monitoring data to build RUL prediction models using statistical laws. They mainly include empirical wear models (e.g., Taylor's formula and its extended forms) and stochastic process models (e.g., Wiener process, Gamma process, inverse Gaussian process). Such methods demonstrate good fitting capability when data is sufficient and can quantify prediction uncertainty, but their performance is limited by data quality and quantity, and their generalization ability is usually weak. (3) Artificial intelligence-based prediction methods: With the advancement of big data and computing power, artificial intelligence methods represented by machine learning and deep learning show great potential in tool RUL prediction. Machine learning models (e.g., SVM, RVM, AR, HMM) are adept at handling small-sample and nonlinear problems; deep learning models (e.g., RNN, LSTM, CNN, DBN) can automatically extract deep features from raw sensor data and possess stronger capabilities for temporal modeling and pattern recognition. Although AI methods offer high prediction accuracy and strong adaptability, their "black-box" nature leads to poor interpretability, and they require large volumes of high-quality labeled data. (4) Hybrid model prediction methods: To compensate for the limitations of single-method approaches, researchers in recent years tend to construct hybrid models that integrate the advantages of physics-based knowledge, data statistics, and artificial intelligence. For example, combining physical models with data-driven methods, or introducing stochastic modeling of the degradation process into the AI framework, to balance prediction accuracy and model reliability. Through multi-source information fusion and complementarity, hybrid models significantly enhance RUL prediction capability under complex working conditions, representing a current hot research direction.Conclusions and ProspectsThrough a systematic review of existing research, it can be concluded that tool RUL prediction methods evolve from single models to multi-method fusion, and from offline analysis to online intelligent diagnosis. However, this field still faces the following major challenges. (1) Reliability of machining signal acquisition and processing: Industrial field data is often plagued by noise interference and incomplete sampling. There is an urgent need to develop more robust feature extraction and signal denoising methods, and to explore real-time data acquisition technologies based on new sensing methods such as intelligent tool holders. (2) Effective fusion of multi-sensor data: Effectively integrating multi-source heterogeneous information (e.g., force, vibration, acoustic emission) and extracting common features strongly correlated with tool degradation from them are key to enhancing model robustness. (3) Balancing model accuracy and generalization ability: Most current models perform well under specific conditions but are prone to performance degradation in application scenarios with varying tool materials and machining parameters. Future research needs to explore cross-condition, adaptive, and lightweight model architectures. (4) Improving the interpretability of hybrid models: Although hybrid models have advantages in accuracy, their decision-making processes often lack transparency. Enhancing model interpretability so that their predictions can be understood and trusted by engineers is a crucial link in promoting technology implementation.
ObjectivesAt present, China's oil and gas exploration and development are gradually advancing towards deep and ultra-deep well fields, which have the characteristics of high environmental temperature, high rock strength, and complex formations. Therefore, higher requirements are put forward for the long-term and efficient performances of rock-breaking tools. Polycrystalline diamond compact (PDC) cutting cutter are formed by combining artificial diamond micro-powder with a tungsten carbide matrix through high-temperature and high-pressure sintering technology. They possess the high hardness, high wear resistance, and high thermal conductivity of diamond, as well as the high strength and good impact toughness of tungsten carbide, and are essential core materials and tools for oil and gas exploration and development. The content of metal phases such as Co and W in the polycrystalline diamond (PCD) layer has a decisive influence on the synthesis and performance of PDC cutting cutters. The study of metallic phases can provide an in-depth understanding of the performance, the microstructure and the failure mechanism of PDC cutting cutters.MethodsIn the research and development of PDC cutting cutters, Co removal technology, composite doping technology, and structural design technology have been widely applied and have achieved excellent drilling results. For example, the wear resistance and thermal stability of PDC cutters can be enhanced by reducing the metal content in the PCD layer, and the impact toughness of PDC cutters can be enhanced by adding WC-Co metal. However, the research on the influence mechanism of metal content on the performance of PDC cutters is relatively scarce. Therefore, three types of PDC cutting cutters with different WC-Co contents were prepared using the high-temperature and high-pressure method and a uniform powder mixing process. The distribution of metallic phases and microscopic morphology characteristics in PDC are analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM), and the wear resistance and impact resistance are compared and tested using a vertical turret lathe and a drop hammer impact tester. Meanwhile, the microstructure of the grinding section and impact fracture surface after performance testing of PDC cutting cutters are observed to further explore the influence of metal content in PCD on the mechanical properties and failure mechanism of PDC cutting cutters.ResultsThree types of PDC cutters with different WC-Co contents, namely cutter #1, cutter #2, and cutter #3, are prepared using the uniform powder mixing method and cobalt removal treatment. The PCD layers are uniform, and the metal phase content gradually increases from cutter #1 to cutter #3. All three types of PDC cutters are well sintered, and the addition of WC-Co metal phase reduces the number of D-D bonds in the PCD layer. The removal of Co improves the wear resistance of PDC cutters, while the metal phase content is negatively correlated with the wear resistance of PDC cutters. As the WC-Co content increases, the roughness of the worn surfaces of PDC cutters increase, and the number of intergranular microcrack fractures at the grinding mouth increases. At the same time, the increase in metal phase content significantly improves the impact resistance of PDC cutters. The impact resistance of cutter #3 is much higher than that of cutter #1 and cutter #2. The reason is that the metallic phase in the PCD layer plays a key role in hindering the propagation of microcracks.ConclusionsAn increase in the content of metallic phases will microscopically change the bonding degree of the diamond skeleton, the morphology of the ground surface and the fracture mode of microcracks, and will macroscopically directly affect the mechanical properties of PDC cutters. That is, changes in the microstructure of PDC cutters directly affect the quality of their macroscopic properties.
