The minimum quantity of lubricant (MQL) technique in the surface grinding of steel

This research aimed to analyze the viability of the minimum quantity of lubricant (MQL) technique towards different methods of lubri-refrigeration in surface grinding of steel, considering process quality, wheel life and the viability of using cutting fluids The proposal methods were the conventional (abundant fluid flow), the minimum quantity lubrication (MQL) and the optimized method with Webster nozzle (rounded) This analysis was carried out in equal machining conditions, through the assessment of variables such as grinding force, surface roughness, G ratio (volume of removed material/volume of wheel wear), and microhardness The results showed the possibility of improvement of the grinding process Besides, there is the opportunity for production of high quality workpieces with lower costs The MQL technique showed efficiency in machining with lower depths of cut The optimized method with Webster nozzle applies the fluid in a rational way, without considerable waste Hence, the results show that industry can rationalize and optimize the application of cutting fluids, avoiding inappropriate disposal, inadequate use and consequently environment pollution

The behaviour of resin-bond diamond wheels in the grinding of advanced ceramics

Results are reported of the behaviour of the plane tangential grinding process using diamond grinding wheels. Grinding performance is analysed in terms of the wear behaviour of the wheel in the grinding of ceramic. Discussion of the results concentrates on the wear mechanism of the diamond wheel and the process of material removal.

Production grinding burn detection using acoustic emission and electric power signals

This work uses a monitoring system based on a PC platform, where the acoustic emission and electric power signals generated during the grinding process are used to investigate superficial burning occurrence in a surface grinding operation using two types of steel, three grinding conditions and an Al203 vitrified grinding wheel. Acoustic emission signals on the workpiece and grinding power were measured during a surface plunge operation until the grinding burn happened. From the results the standard deviation of the acoustic emission signal and the maximum electric power were calculated for each grinding pass. The proposed DPO parameter is the product between the power level and acoustic emission standard deviation. The results show that both signals can be used for burning detection, and the parameter DPO is the best indicator for the burning studied in this work. This can be explained by the high dispersion of the acoustic emission RMS level associated to the high power consumption when the grinding wheel lose its sharpness.

The improvement in grinding of inlet engine valves by the adoption of the most effective cuting fluid type

In this paper is presented an experimental research in which the grinding of seating surfaces of inlet engine valves was improved by the adoption of the most effective cutting fluid type, matching the new requirements of cutting fluid application. Four different types of cutting fluids (straight oil and three different types of soluble oils) were analyzed. As qualitative and quantitative evaluation parameters of the performance of the cutting fluids, the roughness, the grinding wheel wear, the cutting force and the workpiece residual stress were determined. As a conclusion, the straight oil was the cutting fluid that presented the best results in all of the parameters analyzed. Copyright © 2000 Society of Automotive Engineers, Inc.

Neural network detection of grinding burn from acoustic emission

An artificial neural network (ANN) approach is proposed for the detection of workpiece `burn', the undesirable change in metallurgical properties of the material produced by overly aggressive or otherwise inappropriate grinding. The grinding acoustic emission (AE) signals for 52100 bearing steel were collected and digested to extract feature vectors that appear to be suitable for ANN processing. Two feature vectors are represented: one concerning band power, kurtosis and skew; and the other autoregressive (AR) coefficients. The result (burn or no-burn) of the signals was identified on the basis of hardness and profile tests after grinding. The trained neural network works remarkably well for burn detection. Other signal-processing approaches are also discussed, and among them the constant false-alarm rate (CFAR) power law and the mean-value deviance (MVD) prove useful.

In-process thermal damage detection in grinding with monitoring via Internet

This work aims the development of a dedicated system for detection of burning in surface grinding process, where the process will constantly be monitored through the acoustic emission and electric power of the induction motor drive. Acquired by an analog-digital converter, algorithms process the signals and a control signal is generated to inform the operator or interrupt the process in case of burning occurrence. Moreover, the system makes possible the process monitoring via Internet. Additionally, a comparative study between parameters DPO and FKS is carried through. In the experimental work one type of. steel (ABNT-1020 annealed) and one type of grinding wheel referred to as TARGA, model ART 3TG80.3 NVHB, were employed.

Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

Transverse cylindrical grinding of a eutectic alloy

We report herein on a comparison of the performance of two different grinding wheels (conventional and CBN) in the transverse cylindrical grinding of a eutectic alloy. Three cutting conditions were tested: rough, semi-finishing and finishing. The parameters of evaluation were the cutting force, roughness and wheel wear. The optimal cutting force and roughness values were obtained when grinding with the conventional wheel, due to the superior dressing operation performed under every cutting condition tested. Although the CBN wheel presented the best G ratio values, they were lower than expected owing to the inappropriate dressing operation applied. Excessive wheel corner wear was detected in both wheels, caused by the grinding kinematics (transverse grinding) employed. In terms of cutting force and roughness, the conventional wheel proved to be the better choice under the conditions tested. However, in terms of the G ratio, a cost analysis is crucial to determine whether the differences between the wheels justify the use of the CBN wheel, in which case the dressing operation requires improvement.

Analysis of diametrical wear of grinding wheel and roundness errors in the machining of steel VC 131

Due to the high industrial competitiveness, the rigorous laws of environmental protection, the necessary reduction of costs, the mechanical industry sees itself forced to worry more and more with the refinement of your processes and products. In this context, can be mentioned the need to eliminate the roundness errors that appear after the grinding process. This work has the objective of verifying if optimized nozzles for the application of cutting fluid in the grinding process can minimize the formation of the roundness errors and the diametrical wear of grinding wheel in the machining of the steel VC 131 with 60 HRc, when compared to the conventional nozzles. These nozzles were analyzed using two types of grinding wheels and two different cutting fluids. Was verified that the nozzle of 3mm of diameter, integral oil and the CBN grinding wheel, were the best options to obtain smaller roundness errors and the lowest diametrical wears of grinding wheels.

Study of thresholds to burning in surface grinding process

This work aims at finding out the threshold to burning in surface grinding process. Acoustic emission and electric power signals are acquired from an analog-digital converter and processed through algorithms in order to generate a control signal to inform the operator or interrupt the process in the case of burning occurrence. The thresholds that dictate the situation of burn and non-burn were studied as well as a comparison between the two parameters was carried out. In the experimental work one type of steel (ABNT-1045 annealed) and one type of grinding wheel referred to as TARGA model 3TG80.3-NV were employed. Copyright © 2005 by ABCM.

Study on the behavior of the Minimum quantity lubricant - MQL technique under different lubricating and cooling conditions when grinding ABNT 4340 steel

The behavior of the minimum quantity lubricant (MQL) technique was analyzed under different lubricating and cooling conditions when grinding ABNT 4340 steel. The comparative analysis of the residual stress values showed that residual compressive stresses were obtained under all the lubrication/cooling conditions and types of abrasive tools employed. The highest residual compressive stress obtained with the aluminum oxide grinding wheel with MQL under the condition of V= 30m/s for air and V= 40ml/h for lubricant was -376MPa against the -160MPa attained with conventional cooling, representing a 135% increase in residual compressive stress. The results show that method and quantity of lubricant and cooling are factors that influence the grinding process.

In-process grinding monitoring through acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding processes. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS. Copyright © 2006 by ABCM.

Global analysis of aerodynamics deflectors efficiency in the grinding process

The conventional, grinding methods in some cases are not very efficient because the arising of thermal damages in the pieces is very common. Optimization methods of cutting fluid application in the grinding zone are essential to prevent thermal problems from interaction of the wheel grains with the workpiece. surface. The optimization can happen through the correct selection of the cut parameters and development of devices that eliminate air layer effects generated around the grinding wheel. This article will collaborate with the development of an experimentation methodology which allows evaluating, comparatively, the performance of the deflectors in the cutting region to minimize the air layer effect of the high speed of the grinding wheel. The air layers make the cutting fluid jet to dissipate in the machine. An optimized nozzle was used in order to compare the results with the conventional method (without baffles or deflectors) of cutting fluid application. The results showed the high eficciency of the deflectors or baffles in the finish results. Copyright © 2006 by ABCM.

Methodology for automatic selection of passes in surface grinding

The main purpose of this work is the development of computational tools in order to assist the on-line automatic detection of burn in the surface grinding process. Most of the parameters currently employed in the burning recognition (DPO, FKS, DPKS, DIFP, among others) do not incorporate routines for automatic selection of the grinding passes, therefore, requiring the user's interference for the choice of the active region. Several methods were employed in the passes extraction; however, those with the best results are presented in this article. Tests carried out in a surface-grinding machine have shown the success of the algorithms developed for pass extraction. Copyright © 2007 by ABCM.