Novel Batch Polishing Method of Ceramic Cutting Inserts for Reducing Tool Wear

Ceramic cutting inserts are a type of cutting tool commonly used in high-speed metal cutting applications.However,the wear of these inserts caused by friction between the workpiece and cutting inserts limits their overall effectiveness.In order to improve the tool life and reduce wear,this study introduces an emerging method called magnetic field-assisted batch polishing(MABP)for simultaneously polishing multiple ceramic cutting inserts.Several polishing experiments were conducted under different conditions,and the wear characteristics were clarified by cutting S136H steel.The results showed that after 15 min of polishing,the surface roughness at the flank face,edge,and nose of the inserts was reduced to below 2.5 nm,6.25 nm,and 45.8 nm,respectively.Furthermore,the nose radii of the inserts did not change significantly,and there were no significant changes in the weight percentage of elements before and after polishing.Additionally,the tool life of the batch polished inserts was found to be up to 1.75 times longer than that of unpolished inserts.These findings suggest that the MABP method is an effective way to mass polish ceramic cutting inserts,resulting in significantly reduced tool wear.Furthermore,this novel method offers new possibilities for polishing other tools.

Tool Wear State Recognition with Deep Transfer Learning Based on Spindle Vibration for Milling Process

The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the toolwill generate significant noise and vibration, negatively impacting the accuracy of the forming and the surfaceintegrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wearstate andpromptly replace anyheavilyworn tools toguarantee thequality of the cutting.The conventional tool wearmonitoring models, which are based on machine learning, are specifically built for the intended cutting conditions.However, these models require retraining when the cutting conditions undergo any changes. This method has noapplication value if the cutting conditions frequently change. This manuscript proposes a method for monitoringtool wear basedonunsuperviseddeep transfer learning. Due to the similarity of the tool wear process under varyingworking conditions, a tool wear recognitionmodel that can adapt to both current and previous working conditionshas been developed by utilizing cutting monitoring data from history. To extract and classify cutting vibrationsignals, the unsupervised deep transfer learning network comprises a one-dimensional (1D) convolutional neuralnetwork (CNN) with a multi-layer perceptron (MLP). To achieve distribution alignment of deep features throughthe maximum mean discrepancy algorithm, a domain adaptive layer is embedded in the penultimate layer of thenetwork. A platformformonitoring tool wear during endmilling has been constructed. The proposedmethod wasverified through the execution of a full life test of end milling under multiple working conditions with a Cr12MoVsteel workpiece. Our experiments demonstrate that the transfer learning model maintains a classification accuracyof over 80%. In comparisonwith the most advanced tool wearmonitoring methods, the presentedmodel guaranteessuperior performance in the target domains.

Monitoring Tool Wear States in Turning Based on Wavelet Analysis

To monitor the tool wear states in turning, a new way based on the wavelet transformation to get the signal characters, which can reflect the tool wear states, was proposed. Using discrete dyadic wavelet transform, the acoustic emission(AE) signal of cutting process was decomposed; the root mean square(RMS) values of the decomposed signals at different scales were taken as the feature vector; the technique of fuzzy pattern identification was used to real time monitor the tool wear states. Based on choosing the suitable standard samples, this method can correctly identify the tool wear states. Experiments showed that the technique based on wavelet analysis is suitable for real time implementation in manufacturing application.

TOOL WEAR PATTERNS AND MECHANISMS OF SOLID CEMENTED CARBIDE IN HIGH-SPEED MILLING OF ALUMINUM ALLOY

The wear patterns and wear mechanisms of solid cemented carbide are analyzed in high-speed milling of aluminum alloy. Results show that the dominant wear patterns are coating damage, crater wear, micro-chipping, breakage, and so on. The main wear mechanisms are adhesion, diffusion and fatigue. Compared with conventional speed machining, the effect and impact of thermal-dynamical coupling field play an important role in the cutting tool wear in high-speed milling of aluminum alloy.

INFLUENCE OF COLD NITROGEN GAS AND OIL MIST IN MACHINING NICKEL-BASE K424 ALLOY WITH CERAMIC CUTTING TOOLS

The role of cold nitrogen gas and oil mist on tool wear and surface roughness is investigated in turning the K424 nickel-base super alloy with Sialon and SiC whisker-reinforced alumina ceramic tools. A new cooling system is developed and used to lower the temperature of the compressed nitrogen gas. Experiments are performed in three different cooling/lubrication modes, i.e. the dry cutting, the cold nitrogen gas （CNG）, and the cold nitrogen gas and oil mist （CNGOM）. Experimental results show that the depth-of-cut notching severely limits the tool life in all the cooling/lubrication modes. Compared with the dry cutting, the use of CNG and CNGOMcan yield higher wear rate of depth-of-cut notching and worse surface finish.

Tool Wear and Its Effect on Surface Roughness in Diamond Cutting of Glass Soda-lime

For the technology of diamond cutting of optical glass, the high tool wear rate is a main reason for hindering the practical application of this technology. Many researches on diamond tool wear in glass cutting rest on wear phenomenon describing simply without analyzing the genesis of wear phenomenon and interpreting the formation process of tool wear in mechanics. For in depth understanding of the tool wear and its effect on surface roughness in diamond cutting of glass, experiments of diamond turning with cutting distance increasing gradually are carried out on soda-lime glass. The wear morphology of rake face and flank face, the corresponding surface features of workpiece and the surface roughness, and the material compositions of flank wear area are detected. Experimental results indicate that the flank wear is predominant in diamond cutting glass and the flank wear land is characterized by micro-grooves, some smooth crater on the rake face is also seen. The surface roughness begins to increase rapidly, when the cutting mode changes from ductile to brittle for the aggravation of tool wear with the cutting distance over 150 m. The main mechanisms of inducing tool wear in diamond cutting of glass are diffusion, mechanical friction, thermo-chemical action and abrasive wear. The proposed research makes analysis and research from wear mechanism on the tool wear and its effect on surface roughness in diamond cutting of glass, and provides theoretical basis for minimizing the tool wear in diamond cutting brittle materials, such as optical glass.

Influence of Minimum Quantity Lubrication Parameters on Tool Wear and Surface Roughness in Milling of Forged Steel

The minimum quantity of lubrication（MQL） technique is becoming increasingly more popular due to the safety of environment.Moreover,MQL technique not only leads to economical benefits by way of saving lubricant costs but also presents better machinability.However,the effect of MQL parameters on machining is still not clear,which needs to be overcome.In this paper,the effect of different modes of lubrication,i.e.,conventional way using flushing,dry cutting and using the minimum quantity lubrication（MQL） technique on the machinability in end milling of a forged steel（50CrMnMo）,is investigated.The influence of MQL parameters on tool wear and surface roughness is also discussed.MQL parameters include nozzle direction in relation to feed direction,nozzle elevation angle,distance from the nozzle tip to the cutting zone,lubricant flow rate and air pressure.The investigation results show that MQL technique lowers the tool wear and surface roughness values compared with that of conventional flood cutting fluid supply and dry cutting conditions.Based on the investigations of chip morphology and color,MQL technique reduces the cutting temperature to some extent.The relative nozzle-feed position at 120°,the angle elevation of 60° and distance from nozzle tip to cutting zone at 20 mm provide the prolonged tool life and reduced surface roughness values.This fact is due to the oil mists can penetrate in the inner zones of the tool edges in a very efficient way.Improvement in tool life and surface finish could be achieved utilizing higher oil flow rate and higher compressed air pressure.Moreover,oil flow rate increased from 43.8 mL？h to 58.4 mL？h leads to a small decrease of flank wear,but it is not very significant.The results obtained in this paper can be used to determine optimal conditions for milling of forged steel under MQL conditions.

Experimental and FEM Study of Coated and Uncoated Tools Used for Dry Milling of Compacted Graphite Cast Iron

Compacted graphite cast iron （CG1） has been the material for high-power diesel engines recently, but its increased strength causes poor machinability. In this study, coated and uncoated carbide tools were used in dry milling experiment and FEM simulation to study the machinability of CGI and wear behaviour of tools. The experimental and FEM simulation results show that coated tool has great advantage in dry milling of CGI. SEM and EDS analysis of tool wear indicate the wear morphology and wear mechanism. Adhesive wear is the main mechanism to cause un- coated tool wear, while abrasive wear and delamination wear are the main mechanism to cause coated tool wear. Stress and temperature distribution in FEM simulation help to understand the wear mechanism including the reason for coat- ing peeled off.

WEAR AND LIFE OF PCBN TOOLS WHEN DRY-CUTTING BEARING STEEL GCr15

The wear forms and reasons of PCBN tools when dry-cutting bearing steel GCr15are studied systematically. The effect law of the workpiece hardness on PCBN tools is gained andtool wearing with the quickest speed at the workpiece critical hardness is proved. The life equationat two kinds of workpiece hardness demonstrates that the effect of the cutting speed on the PCBNtool life is less than that of carbide tools and ceramic tools.

Performance evaluation of minimum quantity lubrication by vege-table oil in terms of cutting force,cutting zone temperature,tool wear,job dimension and surface finish in turning AISI-1060 steel

In all machining processes, tool wear is a natural phenomenon and it leads to tool failure. The growing demands for high productivity of machining need use of high cutting velocity and feed rate. Such machining inherently produces high cutting temperature, which not only reduces tool life but also impairs the product quality. Metal cutting fluid changes the performance of machining operations because of their lubrication, cooling and chip flushing functions, but the use of cutting fluid has become more problematic in terms of both employee health and environmental pollution. The minimization of cutting fluid also leads to economical benefits by way of saving lubricant costs and workpiece/tool/machine cleaning cycle time. The concept of minimum quantity lubrication (MQL) has been suggested since a decade ago as a means of addressing the issues of environmental intru- siveness and occupational hazards associated with the airborne cutting fluid particles on factory shop floors. This paper deals with experimental investigation on the role of MQL by vegetable oil on cutting temperature, tool wear, surface roughness and dimen- sional deviation in turning AISI-1060 steel at industrial speed-feed combinations by uncoated carbide insert. The encouraging results include significant reduction in tool wear rate, dimensional inaccuracy and surface roughness by MQL mainly through reduction in the cutting zone temperature and favorable change in the chip-tool and work-tool interaction.

Simulation and experiment analysis on thermal deformation of tool system in single-point diamond turning of aluminum alloy

The aim of this work is to simulate thermal deformation of tool system and investigate the influence of cutting parameters on it in single-point diamond turning(SPDT) of aluminum alloy. The experiments with various cutting parameters were conducted. Cutting temperature was measured by FLIR A315 infrared thermal imager. Tool wear was measured by scanning electron microscope(SEM). The numerical model of heat flux considering tool wear generated in cutting zone was established. Then two-step finite element method(FEM) simulations matching the experimental conditions were carried out to simulate the thermal deformation. In addition, the tests of deformation of tool system were performed to verify previous simulation results. And then the influence of cutting parameters on thermal deformation was investigated. The results show that the temperature and thermal deformation from simulations agree well with the results from experiments in the same conditions. The maximum thermal deformation of tool reaches to 7 μm. The average flank wear width and cutting speed are the dominant factors affecting thermal deformation, and the effective way to decrease the thermal deformation of tool is to control the tool wear and the cutting speed.

Hardening Effect on Machined Surface for Precise Hard Cutting Process with Consideration of Tool Wear

During hard cutting process there is severe thermodynamic coupling effect between cutting tool and workpiece, which causes quenching effect on finished surfaces under certain conditions. However, material phase transformation mechanism of heat treatment in cutting process is different from the one in traditional process, which leads to changes of the formation mechanism of damaged layer on machined workpiece surface. This paper researches on the generation mechanism of damaged layer on machined surface in the process of PCBN tool hard cutting hardened steel Cr12MoV. Rules of temperature change on machined surface and subsurface are got by means of finite element simulation. In phase transformation temperature experiments rapid transformation instrument is employed, and the effect of quenching under cutting conditions on generation of damaged layer is revealed. Based on that, the phase transformation points of temperature under cutting conditions are determined. By experiment, the effects of cutting speed and tool wear on white layer thickness in damaged layer are revealed. The temperature distribution law of third deformation zone is got by establishing the numerical prediction model, and thickness of white layer in damaged layer is predicted, taking the tool wear effect into consideration. The experimental results show that the model prediction is accurate, and the establishment of prediction model provides a reference for wise selection of parameters in precise hard cutting process. For the machining process with high demanding on surface integrity, the generation of damaged layer on machined surface can be controlled precisely by using the prediction model.

Effects of Cutting Parameters on Tool Insert Wear in End Milling of Titanium Alloy Ti6A14V

Titanium alloy is a kind of typical hard-to-cut material due to its low thermal conductivity and high strength at elevated temperatures, this contributes to the fast tool wear in the milling of titanium alloys. The influence of cutting conditions on tool wear has been focused on the turning process, and their influence on tool wear in milling process as well as the influence of tool wear on cutting force coefficients has not been investigated comprehensively. To fully understand the tool wear behavior in milling process with inserts, the influence of cutting parameters on tool wear in the milling of titanium alloys Ti6A14V by using indexable cutters is investigated. The tool wear rate and trends under different feed per tooth, cutting speed, axial depth of cut and radial depth of cut are analyzed. The results show that the feed rate per tooth and the radial depth of cut have a large influence on tool wear in milling Ti6A14V with coated insert. To reduce tool wear, cutting parameters for coated inserts under experimental cutting conditions are set as： feed rate per tooth less than 0.07 mm, radial depth of cut less than 1.0 mm, and cutting speed sets between 60 and 150 m/min. Investigation on the relationship between tool wear and cutting force coefficients shows that tangential edge constant increases with tool wear and cutter edge chipping can lead to a great variety of tangential cutting force coefficient. The proposed research provides the basic data for evaluating the machinability of milling Ti6A14V alloy with coated inserts, and the recommend cutting parameters can be immediately applied in practical production.

Tool State Detection by Harmonic Wavelet and Sample Entropy

It is a fact that acoustic emission(AE) signals contain potentially valuable information for tool wear and breakage monitoring and detection.However,AE stress waves produced in the cutting zone are distorted by the transmission path and the measurement systems,it is difficult to obtain a reliable result by these raw AE data.It is generally known that the process of tool wear belongs to detect weak singularity signals in strong noise.The objective of this paper is to combine Newland Harmonic wavelet and Richman-Moorman(2000) sample entropy for detecting weak singularity signals embedded in strong signals.First,the raw AE signal is decomposed by harmonic wavelet and transformed into the three-dimensional time-frequency mesh map of the harmonic wavelet,at the same time,the contours of the mesh map with log space is induced.Second,the profile map of the three-dimensional time-frequency mesh map is offered,which corresponds to decomposed level on harmonic wavelets.Final,by computing sample entropy in each level,the weak singularity signal can be easily extracted from strong noise.Machining test was carried out on HL-32 NC turning center.This lathe does not have a tailstock.Tungsten carbide finishing tool was used to turn free machining mild steel.The work material was chosen for ease of machining,allowing for generation of surfaces of varying quality without the use of cutting fluids.In turning experiments,the feasibility for tool condition monitoring is demonstrated by 27 kinds of cutting conditions with the sharp tool and the worn tool,54 group data are sampled by AE.The sample entropy of each level of wavelet decomposed for each one of 54 AE datum is computed,wear tool and shaper tool can be distinguished obviously by the sample entropy value at the 12th level,this is a criterion.The proposed research provides a new theoretical basis and a new engineering application on the tool condition monitoring.

Analysis and optimization of drilling parameters for tool wear and hole dimensional accuracy in B_4C reinforced Al-alloy

Cutting parameters were evaluated and optimized based on multiple performance characteristics including tool wear and size error of drilled hole. Taguchi＇s L27, 3-level, 4-factor orthogonal array was used for the tests. It is shown that generally abrasive wear and built up edge （BUE） formation were seen in the tool wear, and the comer wear was also of major importance. Flank wear of the cutting tool was found to be mostly dependent upon particle mass fraction, followed by feed rate, drill hardness and spindle speed, respectively. Among the tools used, TiAlN coated carbide drills showed the best performance with regard to the tool wear as well as hole size. Grey relational analysis indicated that drill material was the more influential parameter than feed rate and spindle speed. The results revealed that optimal combination of the drilling parameters could be used to obtain both minimum tool wear and diametral error.

Cutting Temperature and Tool Wear of Hard Turning Hardened Bearing Steel

A study was undertaken to investigate the performan ce of PCBN tool in the finish turning GCr15 bearing steel with different hardness between 30～64 HRC. The natural thermocouple was used to measure the cutting tem p erature, tool life and cutting temperature were investigated and compared. The m aterial can be heated by this instrument which using low voltage and high elec trical current, while PCBN can’t be heated by electrifying directly, so the ke ntanium layer coating over the PCBN is heated, so the PCBN is heated and its th ermoelectric property is got by this method. [TPP129,+60mm88mm,Y,PZ#] Fig.1 Effect of cutting depth and workpiec hardness on. the cutting temperatureThe objective was to determine the influence of the workpiece hardness on change s in cutting temperature and tool wear characterize. It can be found from Fig.1 that the cutting temperature show an increasing tendency with the improvement of workpiece hardness within the cutting speed scope when the workpiece hardness i s under HRC50. And on the other hand, it is found that the cutting temperature s how the downtrend with the improvement of workpiece hardness when the workpiece hardness is over HRC50. According to experimental results, the critical hard ness when turning hardened GCr15 bearing steel with PCBN tool is about HRC50. Th e wear causes of PCBN tool have been found out through taking photos on the micr o-shape of PCBN poly-laminate initial surface as well as face and flank of wea r tool and analysis on chemical elements. It is discovered that the PCBN tools a re not suitable for cutting the workpiece at nearly critical hardness, because n ear the critical hardness, PCBN wear at the highest speed. For researching the w ear rule of PCBN tool, the tool wear experiments have been carried on by using b earing steel GCr15 at hardness HRC40 and HRC60 with changing cutting speed. The indexes of tool life equations is gained under two kinds of conditions w hich are bigger than 0.6, so the effects of cutting speed on the PCBN tool are m uch less than that of carbide tool and ceramic tool.

Implementation of remote monitoring system for prediction of tool wear and failure using ART2

Remote monitoring of tools for prediction of tool wear in cutting processes was considered, and a method of implementation of a remote-monitoring system previously developed was proposed. Sensor signals were received and tool wear was predicted in the local system using an ART2 algorithm, while the monitoring result was transferred to the remote system via intemet. The monitoring system was installed at an on-site machine tool for monitoring three kinds of tools cutting titanium alloys, and the tool wear was evaluated on the basis of vigilances, similarities between vibration signals received and the normal patterns previously trained. A number of experiments were carried out to evaluate the performance of the proposed system, and the results show that the wears of finishing-cut tools are successfully detected when the moving average vigilance becomes lower than the critical vigilance, thus the appropriate tool replacement time is notified before the breakage.

EFFECT OF TOOL WEAR ON MICROSTRUCTURE, MECHANICAL PROPERTIES AND ACOUSTIC EMISSION OF FRICTION STIR WELDED 6061 Al ALLOY

Tool condition is one of the main concerns in friction stir welding （FSW）, because the geometrical condition of the tool pin including size and shape is strongly connected to the microstrueture and mechanical performance of the weld. Tool wear occurs during FSW, especially for welding metal matrix composites with large amounts of abrasive particles, and high melting point materials, which significantly expedite tool wear and deteriorate the mechanical performance of welds. Tools with different pin-wear levels are used to weld 6061 Al alloy, while acoustic emission （AE） sensing, metallographic sectioning, and tensile testing are employed to evaluate the weld quality in various tool wear conditions. Structural characterization shows that the tool wear interferes with the weld quality and accounts for the formation of voids in the nugget zone. Tensile test analysis of samples verifies that both the ultimate tensile strength and the yield strength are adversely affected by the formation of voids in the nugget due to the tool wear. The failure location during tensile test clearly depends on the state of the tool wear, which led to the analysis of the relationships between the structure of the nugget and tool wear. AE signatures recorded during welding reveal that the AE hits concentrate on the higher amplitudes with increasing tool wear. The results show that the AE sensing provides a potentially effective method for the on-line manitoring of tool wear.

Multi-Scale Convolutional Gated Recurrent Unit Networks for Tool Wear Prediction in Smart Manufacturing

As an integrated application of modern information technologies and artificial intelligence,Prognostic and Health Management(PHM)is important for machine health monitoring.Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry.In this paper,a multi-scale Convolutional Gated Recurrent Unit network(MCGRU)is proposed to address raw sensory data for tool wear prediction.At the bottom of MCGRU,six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network,which augments the adaptability to features of different time scales.These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations.At the top of the MCGRU,a fully connected layer and a regression layer are built for cutting tool wear prediction.Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.

Online tool-wear measurement of small-diameter end mills based on machine vision

The objective of this study was to develop an online tool-wear-measurement scheme for small diameter end-mills based on machine vision to increase tool life and the production efficiency. The geometrical features of wear zone of each end mill were analyzed, and three tool wear criterions of small-diameter end mills were defined. With the uEye camera, macro lens and 3-axis micro milling machine, it was proved the feasibility of measuring flank wear with the milling tests on a 45# steel workpiece. The design of experiment （DOE） showed that Vc was the most remarkable effect factor for the flank wear of small-diameter end mill. The wear curve of the experiments of milling was very similar to the Taylor curve.