Polycrystalline Diamond Tools Research Articles

Influence of cutting speed and particulate content on polycrystalline diamond tool wear in machining AA7075/TiB2 in situ aluminum matrix composites

Aluminum alloy AA7075 was reinforced with in-situ synthesized TiB2 particles (0–12 wt%) to prepare aluminum matrix composites (AMCs) by casting. The cast composite bars were machined using polycrystalline diamond (PCD) tool inserts. The influence of cutting speed and TiB2 particle content on the tool wear was quantified. The rake face, flank face, and machined surface morphologies were studied using a field emission scanning electron microscope (FESEM). Energy dispersive X-ray analysis (EDS) was carried out on the rake face across a defined line. The increase in cutting speed and TiB2 particle content increased the tool wear. The highest cutting conditions accelerated tool wear and caused chipping. The mechanisms responsible for tool wear were identified as adhesion, abrasion, chipping and diffusion. The state of the tool wear was directly reflected on the machined surface in the form of deposited material and feed mark ridges.

Study on Surface Characteristics and Work Hardening of SiCp/Al Composites by SCCO2-MQL Combined with Ultrasonic Vibration Milling

This study investigated the milling of SiCp/Al composite materials using Polycrystalline Diamond (PCD) tools under various machining conditions, including dry cutting conditions, supercritical carbon dioxide (SCCO2) conditions, supercritical carbon dioxide cooling with minimum quantity lubrication (SCCO2-MQL) conditions, ultrasonic vibration conditions, and supercritical carbon dioxide cooling with minimum quantity lubrication combined with ultrasonic vibration conditions. The objective was to compare the surface roughness and morphology of the materials under different machining conditions. Furthermore, under dry cutting conditions and SCCO2-MQL combined with ultrasonic vibration, the effects of different milling parameters on the surface roughness and morphology of SiCp/Al composite materials were investigated through a univariate experiment. Microhardness tests were carried out on the machined workpieces to explore the influence of process conditions and milling parameters on work hardening. The experimental results indicate that among all the tested machining conditions, the SCCO2-MQL in combination with the ultrasonic vibration process significantly reduced the surface roughness of the material. When the milling speed was increased from 40 m/min to 120 m/min, both the surface roughness and the degree of work hardening first increased and then decreased. As the feed rate or cutting depth increased, the degree of work hardening also increased. Therefore, under SCCO2-MQL combined with ultrasonic vibration conditions, it is recommended to use a milling speed of more than 60 m/min and avoid using high feed rates and cutting depths in order to optimize the machining performance.

Influence of micro-textured polycrystalline diamond tools on the machining performance of titanium alloy Ti-6Al-4V in dry turning

Influence of micro-textured polycrystalline diamond tools on the machining performance of titanium alloy Ti-6Al-4V in dry turning

Laser processing characteristics of PCD tool and modeling analysis

Through in-depth analysis of the experimental details and forming patterns of the nanosecond laser ablation polycrystalline diamond (PCD) textured tool processing system, this study explores the microscopic morphology and dimensions of micro-pits texture on the surface of PCD tools influenced by defocus amount, laser power, and pulse frequency. Experimental results indicate that the micro-pit textures generated under different parameters exhibit diversity, including rounded structure, fragments, recast layers, and heat-affected zones. The diameter and depth of micro-pits are comprehensively affected by defocus amount, laser power, and pulse frequency, showing complex patterns. After a thorough analysis of the effects of each parameter on the texture morphology, an artificial neural network (ANN) model is introduced for the prediction of micro-pit dimensions. Through model training and optimization, accurate predictions of micro-pit diameter and depth are obtained. In comparison to traditional regression models, the ANN model demonstrates outstanding predictive performance, validating its applicability in complex machining processes. This study not only provides a profound understanding of the processing patterns of PCD textured tools but also offers an effective predictive model for the optimization and control of similar future machining processes.

Tool Condition Monitoring Using Machine Tool Spindle Current and Long Short-Term Memory Neural Network Model Analysis.

In cutting processes, tool condition affects the quality of the manufactured parts. As such, an essential component to prevent unplanned downtime and to assure machining quality is having information about the state of the cutting tool. The primary function of it is to alert the operator that the tool has reached or is reaching a level of wear beyond which behaviour is unreliable. In this paper, the tool condition is being monitored by analysing the electric current on the main spindle via an artificial intelligence model utilising an LSTM neural network. In the current study, the tool is monitored while working on a cylindrical raw piece made of AA6013 aluminium alloy with a custom polycrystalline diamond tool for the purposes of monitoring the wear of these tools. Spindle current characteristics were obtained using external measuring equipment to not influence the operation of the machine included in a larger production line. As a novel approach, an artificial intelligence model based on an LSTM neural network is utilised for the analysis of the spindle current obtained during a manufacturing cycle and assessing the tool wear range in real time. The neural network was designed and trained to notice significant characteristics of the captured current signal. The conducted research serves as a proof of concept for the use of an LSTM neural network-based model as a method of monitoring the condition of cutting tools.

Machine learning for predicting laser ablation groove characteristics in polycrystalline diamond

This paper explores machine learning’s role in predicting laser-machined micro-groove texture on Polycrystalline Diamond (PCD) surfaces. PCD has been used for manufacturing ideal cutting insert due to its exceptional attributes, including hardness and thermal conductivity. Surface micro-texturing enhances accuracy and tool lifespan through micro-textures on tool surfaces. Laser micromachining, especially for its precision and efficiency, stands out among methods. Six regression models—Elastic Net, Random Forest, Gradient Boosting Regression, XGBoost Regression, Bayesian Regression, and Gaussian Process Regression—are used to predict groove depth and width based on laser parameters like energy, defocus, and speed. Experiments involve a nanosecond laser system and a commercial PCD tool. Results indicate both Gradient Boosting and XGBoost excel in predicting micro-groove texture. XGBoost slightly outperforms, credited to its enhancements over Gradient Boosting. This paper concludes that machine learning models, especially XGBoost and Gradient Boosting, effectively forecast micro-groove features on laser-machined PCD surfaces, offering insights for further research and practical applications in this domain.

Influence of Abrasive Grain Protrusion on High-Quality Machining of Cemented Carbide Using PCD Ball End Mills

In this study, cemented carbide was machined to a high quality using polycrystalline diamond (PCD) ball end mills characterized by various surface textures. The effect of the surface texture of the tools on the machining characteristics was studied using two types of PCD tools featuring abrasive diamond grains at various protrusion heights. In addition, a single crystal diamond tool with the same shape as that of the PCD tool was fabricated, and the experiment was repeated to study the differences in machining characteristics. The polished PCD tool yielded a high-quality machined surface with an average surface roughness of 1 nm. The polished PCD tool yielded superior sample surface roughness compared to the PCD tool for feed rates of 10–500 mm/min. The use of a polished PCD tool enables the efficient elimination of material through plastic flow, leading to the attainment of a high-quality machined surface while preventing the adhesion of materials on the tool surface. A single crystal diamond tool can also be used for machining cemented carbide within a feed rate range of 10–200 mm/min; however, its performance is inferior to that of a polished PCD tool. Experiments confirmed that the polished PCD tool was the most effective among the tested tools for the precision machining of cemented carbide.

Cryogenic assisted femtosecond laser ablation of polycrystalline diamond

Polycrystalline diamond (PCD) tools have gained popularity in machining industry ascribed to superior surface quality and durability at elevated temperature and abrasive forces. A major obstacle for high-speed PCD machining is the excessive heat production that transcend the heat dissipation capacity, resulting in reduced tool life and performance. Surface microstructures on PCD tools can improve thermal performance by increasing the heat transfer area and reducing the thermal contact resistance, therefore enhancement in durability and operation. Femtosecond laser processing is a non-contact, high precision and low thermal effect technique for creating superior quality microstructures. This study investigates the effects of cryogenic-assisted femtosecond laser processing in improvement of diamond microstructures quality. Initially the effects of different laser settings on the performance of the process were investigated by conducting single-factor experiments at ambient conditions. Later, the effects of cryogenic assistance on diamond irradiation, surface quality and chemical changes were investigated utilizing laser confocal scanning microscopy (LCSM), scanning electron microscopy (SEM) and Raman spectroscopy. Cryogenic laser ablation had no effect on the diamond removal rate, on contrary improved the surface quality by reducing the surface roughness and graphite disorderliness. This study reports superior surface quality finish for cryogenic assisted laser ablation than ambient conditions therefore it is recommended to irradiate PCD at low temperatures.

An experimental approach to characterize the performance of PCD and PCBN tools in milling nano Al-8081-Zr/Mg/TiO2 metal matrix composites using multi-sensor data fusion

To prevent the quality of the finished product from declining, precision manufacturing procedures need reliable cutting tool wear detection. Cutting tool material, workpiece attributes, cutting conditions and conditions, and excessive cutting forces creating vibrations causing chatter impacting tool wear finally leading to tool failure all have an impact on tool performance. This paper presents a multisensory data fusion approach that assigns sensors at nearfield sites during the machining process to monitor the tool condition. The study investigates the performance of polycrystalline diamond (PCD) and Polycrystalline Cubic Boron Nitride (PCBN) cutting tools during the machining of nano metal matrix composites reinforced with Zr/Mg/TiO2 (15%). The method correlates signal features with experimental results to provide a reliable empirical approach to monitor the cause of tool flank wear and displacement, leading to failure. The experimental investigation it is found the cutting forces showed significant effect on flank wear affecting surface finish and tool life. Tool performance was successful monitoring and predicted instantly based on the signature analysis of vibrations and forces during machining helped accurately analyzed factors affecting tool wear at uncertain cutting conditions using FDA analysis. The study provides insights into the PCD and PCBN tools’ performance characteristics.

Effect of PCD tool wear on surface morphology and material removal mechanisms in the micro-drilling of Cf/SiC composites: Experiment and simulation

This study investigates the polycrystalline diamond (PCD) tool's wear mechanism and the effect of tool wear on hole morphology in the micro-drilling of Cf/SiC composites. A 2D woven material model and tool wear model are created for the drilling simulation. The findings indicate that the wear mechanisms of the tools are mainly abrasive and adhesive. As the tool is worn, the quality of the hole entrance/exit and the shape accuracy deteriorate, and the surface roughness of the hole wall increases. Furthermore, a blunt cutting-edge radius shifts material removal from a shear effect to a compressive effect, transitioning from micro-brittle to macro-brittle removal. Notably, the simulation results approximately agree with the experimental results.

Investigation of in-plane and out-of-plane micro-hole drilling on 2D-Cf/SiC composites

Carbon fiber-reinforced silicon carbide matrix composites (Cf/SiCs) are extensively utilized in the field of aviation and aerospace because of their superior mechanical qualities. However, it is difficult to machine high-quality small holes on them. To investigate the characteristics of micro-drilling on Cf/SiCs, the polycrystalline diamond (PCD) tool was used to machine holes on the in-plan and out-of-plan surfaces of Cf/SiC composites. The drilling force, the hole morphology and quality were explored. The mechanisms of material removal and tool wear were studied. The size effect during the micro-drilling process was also investigated. The outcomes showed that the out-of-plane drilling process yielded more thrust force and torque than the in-plane drilling process. The main forms of damage at the hole entrance and exit are tearing and burrs during in-plane drilling. The damage is mainly in the form of edge breaking caused by debonding and fracture of longitudinal fiber during out-of-plane drilling. The surface defects of the hole exit and entrance during out-of-plane drilling are fewer than those during in-plane drilling. The roundness errors of holes during in-plane drilling are fewer than those during out-of-plane drilling. Additionally, the surface roughness of the hole wall during in-plane drilling is less. Besides, brittle and ductile removal areas were observed at different fiber orientation angles (FOA). Furthermore, the rapid rise in specific cutting energy and the deterioration of surface quality when the feed rate is much smaller than the cutting edge proves the presence of the size effect. A new observation was that the abrasive wear of the flank face and chisel edge during out-of-plane drilling was more severe than that of in-plane drilling.

Analysis of chip compression ratio in turning of polyoxymethylene copolymer

The turning process is influenced by a synergy of various parameters that affect the machining mechanisms and the resulting process efficiency. Among these factors, the evaluation of chip morphology is of paramount importance and can often be quantified by the chip compression ratio. This key figure serves as a quantitative measure of the overall plastic deformation and provides information about the energy expended during cutting and the friction behavior at the interface between the chip and the cutting tool. This research is specifically concerned with modeling and analyzing the chip compression ratio during dry turning of polyoxymethylene copolymer (POM-C) using a polycrystalline diamond (PCD) tool. The experimental setup comprised a face-centered, central compound test in which three main parameters — depth of cut, feed rate and cutting speed - were adjusted to each other. After conducting the turning experiments and collecting the measurement data, a second-order mathematical model was formulated to establish the relationship between the turning parameters and the chip compression ratio. Statistical analysis of the results revealed notable main effects of depth of cut and feed rate, a quadratic effect of depth of cut and an interaction effect between feed rate and cutting speed, all of which have a significant effect on the change in chip compression ratio.

Ultra-short pulsed laser processing of single crystalline diamonds for tooling applications

This study investigates the feasibility of using ultra-short pulsed (USP) lasers to fabricate single crystalline diamond (SCD) tools. SCD has exceptional mechanical, tribological, and thermal properties and offers excellent performance in the precision machining of hard and brittle materials over polycrystalline diamond and diamond-coated tools. However, the anisotropic nature of the SCD makes it difficult for laser machining because the material shows susceptibility to cracking, defect growth, and breakout depending on its crystallographic orientation. Anisotropy needs to be considered while optimizing the geometry of the tool to minimize wear and improve tool performance. An advanced four-axis laser machining approach with optimized laser parameters and temporal beam shaping is used to mitigate challenges related to defect growth and orientation dependence, leading to the production of high-quality single cutting-edge SCD tools. Cylindrical diamonds and diamond crystals with top surface planes {100} and {111} are used in the study. The occurrence of defects in the diamond when laser machined and their dependence on the crystallographic orientation along the circumference of the diamond is thoroughly investigated via SEM, electron backscatter diffraction, and light microscopy images. Finally, the laser-manufactured SCD tools are tested by turning fully sintered zirconia ceramics (3Y-TZP-A). USP laser machining of SCD is demonstrated to be a viable alternative to traditional manufacturing methods for producing high-quality SCD tools with unique properties and performance. The results further emphasize the importance of understanding the crystallographic orientation dependence when laser machining crystalline materials like diamonds.

Cutting performance and wear behavior of diamond, coated cemented carbide and PCBN tools during milling of Cf/SiC composites

As an advanced material, Cf/SiC composites are wildly used in many aerospace industries due to their excellent properties. However, machining the material often encounters many problems, such as poor machining quality, severe tool wear, and low processing efficiency. Tool materials have a significant influence on the cutting performance of tools and the surface quality of the workpiece being machined. In this study, milling experiments have been performed on Cf/SiC composites with different tools. The tool wear pattern, progression, mechanisms, and milling temperature were investigated. The machined surface quality and removal mechanisms of Cf/SiC composites were studied. The results indicated that polycrystalline diamond (PCD) tools have better cutting performance in milling Cf/SiC composites than other tools. Surface defects, milling temperature, and machined surface roughness (Sa = 2.9 μm) obtained by machining Cf/SiC composites using the PCD tool would be lower. The material removal mode is brittle fracture, and the surface damage (including fiber debonding, fiber pullout, and pits, etc.) is related to the direction of the fibers. Fibers in the X and Y directions can lead to more machined surface defects. Since hard particles formed in the machining process and protruding fibers constantly scratched the flank face, diamond grains were spalled off from PCD tools, resulting in abrasive wear.

Effect of tool wear on machining quality in milling Cf/SiC composites with PCD tool

Carbon fiber reinforced silicon carbide ceramic matrix (Cf/SiC) composites have great application potential in aerospace. But their high hardness and anisotropy cause rapid tool wear during machining, which affects machining quality and efficiency. However, tool wear mechanisms in milling Cf/SiC composites are still unclear. There is a lack of research on the relationship between tool wear and cutting performance. In this paper, milling experiments on 2.5D Cf/SiC composites were conducted using polycrystalline diamond (PCD) cutters. The tool wear mechanisms and effect of tool wear on surface roughness, milling force, burr damage, surface microstructure and chips were explored. The results show that abrasive wear caused by chips continuously scraping tool material and diamond particle fragmentation and falling off caused by sprouting and expansion of cracks inside grain were primary causes of tool failure. The formation mechanism of burr damage was analyzed. It was proved that the peak radius of cutting edge Rpeak and flank wear VB could reflect cutting capabilities. It was found that increasing flank wear had regrinding effects on the cutting edge, which affects the peak radius. The degree of burr damage was related to these two parameters. Tool wear changed the surface formation mechanism. Before tool wear, carbon fibers were primarily removed through the micro-brittle fracture, with low surface roughness. The flank face and chips scratched the workpiece like abrasive grains after tool wear, leaving scratches on the surface and increasing surface roughness from 1.27 μm to 2.25 μm.

Evaluation of milling performance of 50-μm D-shaped carbide tool, polycrystalline diamond-coated carbide tool, and polycrystalline diamond tool

Evaluation of milling performance of 50-μm D-shaped carbide tool, polycrystalline diamond-coated carbide tool, and polycrystalline diamond tool

Effect of Turning Parameter and Fiber Pullout on Machinability of Unidirectional EGFRP under Cryogenic Condition

The non-homogeneous and anisotropic nature of composites poses challenges during machining, requiring the use of specialized cutting tools. GFRP materials were selected for their excellent elasticity, corrosion resistance, and high strength, making them ideal for applications in the aerospace and automotive industries. In this work, the surface quality of UD-GFRP composite bars during CNC machining in diverse machining conditions (dry, wet, and cryogenic) was investigated while considering the fiber-pullout issue. The UD-EGFRP composite materials have been machined with a polycrystalline diamond tool. The Taguchi-L9 orthogonal-array technique is used to investigate and further analysis. Three independent-variables feed rate, rotational speed or cutting speed, and depth of cut have been taken into account for their optimal design to get better machinability of EGFRP. This study also investigates the delamination criterion in composites and establishes the correlation between its input parameters and output responses. The findings revealed that cryogenic machining led to a notable improvement of 25.21% in surface roughness compared to the other lubrication methods. Also, the reduction from 84 µm to 34 µm in fiber-pullout signifies that cryogenic cooling effectively mitigated the occurrence of fiber-pullout.

Design of discrete-edge polycrystalline diamond tool and its cutting performance in milling Cf/SiC composites

Carbon fiber-reinforced silicon carbide matrix (Cf/SiC) composites are used extensively in many fields because of their superior properties, such as high specific strength and high specific modulus. However, Cf/SiC composites are typically difficult to machine materials due to their high hardness and anisotropy. Its machining easily leads to high cutting force, short tool life, and poor surface quality. The tool structure shows a significant impact on the cutting performance, which can further affect the cutting force and surface quality. In this study, a novel polycrystalline diamond (PCD) tool with discrete-edge structure was designed for milling Cf/SiC composites, which was devised with tiny microgrooves on the peripheral edge, and the geometric parameters were optimized by finite element simulation method. The cutting performance of the designed discrete-edge PCD tool in milling of Cf/SiC composites was studied. Cutting force, machined surface quality, tool wear mechanisms, and tool life were comprehensively investigated. Comparative experiments were also carried out with conventional straight-edge PCD tools by using identical cutting parameters. The cutting force when using the discrete-edge PCD tool gradually decreased with increasing cutting speed. The machined surface roughness Sa reached 3.5 μm at cutting speed of 125 m⋅min−1 with the discrete-edge tool. Surface defects in terms of fiber pullout, debonding, and cavities were reduced by the discrete-edge tool. The life of the discrete-edge PCD tool was 1.875 times that of the conventional PCD tool. The study illustrates that the cutting performance of the designed discrete-edge PCD tool is better than that of the conventional straight-edge PCD tool.

Machining performance and wear behaviour of polycrystalline diamond and coated carbide tools during milling of titanium alloy Ti-54M

Polycrystalline diamond (PCD) is currently under development as a new generation of cutting tool material for titanium alloy machining applications. The unrivaled high temperature hardness possessed by PCD offers the potential for higher levels of productivity compared to tungsten carbide, the current industry standard tool material, through facilitating higher cutting speeds. This study investigates the performance of various PCD tool grades during square shoulder milling of Ti-54M. The influence of PCD grain size on dominant wear mechanism has been established, revealing that a smaller, sub 1 μm, grain size offers improvements in tool life due to superior fracture toughness compared to larger grained material. For fine grained PCD, loss of tool material through a cyclic process of workpiece adhesion followed by grain pull-out was identified to be the predominant wear mechanism, contrasting the mechanical fracture dominated wear observed for the larger grained PCD grades. The influence of insert microgeometry was also investigated through honing of the cutting edge radii. An increased tendency for edge fracture was demonstrated when machining with larger radii tooling which was attributed to increased cutting forces. Finally, the study has compared the surface integrity response of the workpiece following PCD and carbide machining, revealing considerably lower levels of microstructural damage and cutting forces when machining with PCD. This highlights the potential benefits of PCD in finishing applications, whereby high speed machining can be employed to reduce the impact on component surface integrity.

Simulation and experimental study on milling mechanism and tool wear of low volume SiCp/Al composites

Silicon carbide particles reinforced aluminum matrix composites are widely used in national defense and related high-end technology fields due to their excellent mechanical properties. To explore the milling mechanism and tool wear mechanism of low-volume SiCp/Al composites in high velocity milling, the milling experiments for 20% volume SiCp/Al2009 composites were performed using a polycrystalline diamond (PCD) tools. A three-dimensional milling model of SiCp/Al composite was established considering the random distribution of SiC particles, the influence of milling parameters on surface quality was comprehensively analyzed and its cutting mechanism was described, and the wear forms and mechanism of PCD tools were revealed during milling of SiCp/Al composites. The result showed that the cutting depth is the main factor affecting the machined surface quality, followed by the spindle speed, and the feed rate has the smallest effect on it. It was observed that when spindle speed ( n) was 17,000 r/min, the feed rate ( f) was 8 mm/min, the depth of cut ( ap) was 0.04 mm, the surface roughness value was the smallest, Ra was 0.056 μm. The surface morphology was mainly manifested as pits, cracks, burrs, and so on, subsurface defects included particle breakage, peeling, and matrix cracks, and the tool wear forms included chipping, flaking, and bond wear.