평삭공정에서 경면가공을 위한 단결정 및 다결정 다이아몬드 다중공구의 가공성 평가

Effect of tool wear on surface roughness in machining of AA7075/ 10 wt.% SiC composite

The paper presents an experimental investigation to analyze the effects of process parameters on the surface roughness & tool wear in dry machining of Ti-6Al-4V. The process variable used are tool noise radius, feed rate & cutting speed to study their effect on surface roughness and tool wear using coated carbide as cutting tool. The surface roughness of the specimen has been measured with the help stylus-type Profilometer, Surfcom Flex 50A. The tool wear of cutting inserts is analysis by SEM analysis. The results show that the feed rate and nose radius are the significant variable for surface roughness. Surface roughness increases considerably with the increase in feed rate & tool wear and as the nose radius of cutting tool increases, the value of tool wear decreases. The process parameters are optimized for surface roughness.

Mathematical models for surface roughness and tool wear are developed through regression analysis of the experimental data collected from machining. Different particle sizes and flowrates of solid lubricants are employed in the study. Experimental results show a significant effect of solid lubricant particle size and flowrate on surface roughness and tool wear. Decrease in the particle size resulted in reduced tool wear and surface finish improvement. Various machining parameters such as cutting forces, tool wear, and surface roughness improved with an increase in the flowrate of solid lubricant up to a certain level and remained constant at higher flowrates. To estimate the effect of solid lubricants on machining, exponential models are proposed in the present work to predict tool wear and surface roughness as a function of solid lubricant particle size, flowrate, machining time, and cutting force. Predicted values obtained from the developed model and experimental results are compared, and error<10 per cent is observed.

Machining pressed compacts of ceramic and WC-Co materials can be the most cost effective way of forming the bodies prior to sintering when the required number of pieces is small. In this study, in order to clarify the machinability for turning, the and the WC-Co green compacts unsintered were machined under different cutting conditions with various tools. Absorbing chips by vacuum hose decreases tool wear. The tool wear becomes larger in the order of the ceramic, CBN and cemented carbide tools in machining the green compacts. In machining the WC-Co green compacts, the tool wear becomes larger in the order of the ceramic, cemented carbide and CBN tools. The land of cutting edge does not affect tool wear. When machining with cemented carbide tool, the tool wear i equal cutting length is nearly identical in spite of the increase of cutting spee, and the roughness of machined surface was the best in the cutting speed of 90 m/min. The tool wear decreases with the increase of rake angle and relief angle and with the decrease of nose radius. The machined surfaces become worse with the increase of feed rate and depth of cut, and with the decrease of rake angle and relief angle. The tool wear is not affected by the feed and depth of cut.

In general, the optimal control of the cutting process is based on models with the help of which are determined the optimal values of the cutting process parameters, values that are kept constant throughout the machining process, although there are findings that highlight significant changes in the mathematical models that describe the process. Improved dimensional process monitoring systems have appeared, which also include the possibility of monitoring tool wear. The market success of the product is only qualitatively evaluated and used for controlling the machining processes. The list of monitored parameters of the system will have to include the machining error, surface roughness and tool wear rate.

The machining of hard particle reinforced metal matrix composite material is always challenging. The machining behaviour of aluminium-based metal matrix composites (Al-MMCs) can be entirely different from conventional materials. This paper presents an experimental study of the effect of cutting parameters like cutting speed on surface quality and tool wear. Even the matrix material can be ductile, but hard particles and their binding with matrix material can bring a difference in the machinability of composite materials, specially MMCs. Three different MMC compositions, i.e. MMC reinforced with 15%, 20% and 25% SiC, were machined at various cutting speeds and feed rates. Tool wear and surface roughness of the machined surface of MMC were examined. Increased content of SiC increases the mechanical properties like hardness and compressive strength but was found detrimental to tool and surface quality. Tool wear was found increasing with both increasing feed rate and cutting speed. Application of image processing for measurement and prediction of tool wear is attempted by capturing the images of tool insert and processing using a MATLAB® based algorithm. Results are in line with many other research and establish the scope of future work for non-contact measurement of tool wear in real-time.

The application of environment-friendly cutting fluid in machining processes can strongly influence the wear on the cutting tools and the surface finish on workpiece materials. This is only possible, when the cutting fluid provides better penetration into the cutting zone, thereby providing a better cooling and lubricating effect. Therefore, this study aims to show the effect of various cutting fluid cooling conditions and machining parameters on tool flank wear (VB) and surface roughness (Ra) of the work piece while turning AISID2 steel with coated CBN tools. By adopting RSM technique with FCCD and using analysis of variance, the effect of cutting parameters on desired outputs was explored. The results showed that machining time was the most dominant parameter influencing both tool wear and surface roughness. Moreover, cutting fluid conditions also showed considerable contribution towards decreasing tool wear rate and increasing surface finish. In addition, the cutting tools were examined under scanning electron microscope (SEM) together with EDS. It was observed that abrasion along with BUE formation were the most dominant wear mechanism modes at low cutting speeds. However, at higher cutting speed and feed combinations, abrasions followed by diffusion and adhesion were the dominant form of wear mechanisms. Suppression of BUE was observed at higher cutting speeds of CBN tools. Finally, desirability function approach (DFA) was used to find out the optimal cutting parameters for minimum tool wear with the maximum surface finish .

Online Monitoring of Tool Wear and Surface Roughness by using Acoustic and Force Sensors

This research investigates the impact of high-speed and thermal-assisted machining (HS-TAM) on tool wear and surface roughness during the milling of SKD11 steel. The goal is to identify high-speed and elevated temperature zones that can improve machining efficiency, enhance surface quality, minimize costs, and extend tool life. The study involves the high-speed milling of SKD11 steel at various temperature conditions to evaluate the effect of temperature on tool wear and surface roughness. Additionally, experiments are conducted at the highest allowable support temperature with increased high-speed cutting to examine the effect of high speed on tool wear and surface roughness. The study demonstrates the correlation between cutting-tool wear and surface roughness at various high-speed cutting conditions and TAM environments and provides recommendations for cutting speeds and heating temperatures for different quality and productivity objectives. The findings indicate that high-speed milling of SKD11 at 600 m/min and 500 °C can decrease cutting tool-wear height (wear volume) and surface roughness by 82.47% (95.74%) and 91.08%, respectively, compared to machining at room temperature. Furthermore, the higher-speed modes at 500 °C result in a slight increase in wear height and surface roughness for high-speed cutting below 800 m/min, but reduces surface roughness for high-speed cutting beyond 800 m/min, reaching a value of 0.158 µm at the high-speed cutting limit of 1000 m/min.

Identification and estimation of cutting tool wear and surface roughness of the machined surface are important in the milling process. This paper presents the correlation analysis of cutting force, acoustic emission signals, tool life, and surface roughness. We present the details of the dominant features discovery, which have a high correlation with tool wear and surface roughness. The best compound features found by the correlation analysis are verified by multiple regression models and are used to construct fault estimation models. A case study of tool wear and surface roughness estimation is presented. The good agreement between the estimation results of real tool wear and surface roughness data demonstrates the usability of acoustic emission signals in tool condition monitoring.

One of the problem in metal cutting is tool wear. Its close relation to the expected tool life and quality of product, make tool wear become object of investigation. Eventough tool manufacturers always give recommendation on machining parameter, but they don't share the information on tool wear estimation. Some theory on tool wear has been proposed, but still need verification thru experimental works to determine parameters and constants of tool life typical to machine tool condition and machining process. In this research, experimental work and analysis of the influence of spindle speed (n, rpm), feeding speed (Vf, mm/min) and depth of cut (ap, mm)to surface roughness and tool wear on milling process using carbide ballnose with diameter of 10 mm on Al-7075 had been conducted. From the experiment, it can be concluded that tool wear has influence on surface roughness of product. Tool wear could be minimized by choosing optimum spindle speed and feeding speed.

Investigations on tool wear, surface roughness, cutting temperature, and chip formation in machining of Cu-B-CrC composites

Superalloys are generally considered to be difficult to machinability. In recent attempts to facilitate their machinability, minimum quantity lubrication (MQL) has been used due to its positive influence on cutting tool life, the environment and human health. This study focused on the tool life, wear behavior and surface roughness in the milling of nickel-based superalloy Waspaloy. Uncoated carbide tools, PVD (TiAlN)-coated tools and CVD (TiCN + Al2O3 + TiN)-coated tools were used. Experiments were performed with different cooling methods which included dry, wet and MQL. SEM and EDX were used for tool wear behavior and mechanism analyses. A portable measuring instrument and a 3D optical profilometer were employed for surface roughness analyses. Results obtained from the tests showed that during the milling of the Waspaloy, adhesion and abrasion were effective wear mechanisms for the cutting tools. The main wear behaviors were flank wear, crater wear and BUE (built up edge). In addition to these results, reduction in the tool wear, the wet machining and machining with the MQL system provided improvement at the rates of 37.54% and 29.01%, respectively, when compared to the dry machining.

The study attempts to investigate tool wear (flank wear) and surface roughness during finish hard turning of AISI D3 steel (58HRC) with coated carbide (TiSiN-TiAlN coated) cutting tool. Taguchi L9 (3)3 orthogonal array has been applied for experimental design. S/N ratio and ANOVA analyses were performed to identify significant parameters influencing tool wear and surface roughness. The cutting speed and feed were the most significant factors influencing tool wear (flank wear), and feed is the most significant factor influencing surface roughness (Ra). Mathematical models for both response parameters i.e. tool wear and surface roughness were obtained through regression analysis. The confirmation experiments carried out at optimal combination of parameters given by Taguchi’s analysis, predicted the response factors with less than 5% error. In addition, Desirability function module in RSM was applied to arrive at the optimal setting of input parameters to minimize tool wear and surface roughness. The optimal solution provided by desirability function optimization was compared with the optimal setting of parameters given by Taguchi analysis. The optimization results provided by both techniques are in close proximity.

In this study, turning of the cemented carbides that their WC particle size was standardized were carried out with the PCD and the cBN tools. The WC particle diameter of cemented carbides was about 2µm and the Co contents were 10, 15, 20 and 25%, respectively. The influence of the WC particle size and Co contents was investigated. Summary of results are shown as follows: (1) In turning with the PCD tool, the more the Co contents increase, the more the tool wear increases. (2) In turning with the cBN tools, the more the Co contents of the work material increase, the more the tool wear decreases. (3) In turning of the cemented carbides contained the larger quantity of Co, the cBN tools are more effective than the PCD tool.