Genesis of workpiece roughness generated in surface grinding and polishing of metals

Assuming the grinding wheel surface to be fractal in nature, the maximum envelope profile of the wheel and contact deflections are estimated over a range of length scales. This gives an estimate of the 'no wear' roughness of a surface ground metal. Four test materials, aluminum, copper, titanium, and steel are surface ground and their surface power spectra were estimated. The departure of this power spectra from the 'no wear' estimates is studied in terms of the traction-induced wear damage of the surfaces. The surface power spectra in grinding are influenced by hardness and the power is enhanced by wear damage. No such correlation with hardness was found for the polished surface, the roughness of which is insensitive to mechanical properties and appears to be influenced by microstructure and physical properties of the material.

Roughness generated in surface grinding of metals

When a metal is surface ground the roughness generated is the summation of a function of the wheel roughness and the roughness due to wheel attrition and damage to the workpiece. We identify this function here as a maximum em,elope profile, which is fractal within certain cut off wavelengths determined by the dressing conditions of the wheel. Estimating the global displacement of the binder-grit-workpiece system from the maximum envelope power spectra, we determine the plastic indentation of the workpiece at characteristic length scales using simple contact-mechanical calculation. The estimated roughness corresponds well with that recorded experimentally for hard steel, copper; titanium and aluminium.

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

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.

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.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Effect Of Directionality Of Grinding Marks On Friction And Formation Of Transfer Layer

Surface texture influences friction and transfer layer formation during sliding. In the present investigation, basic studies were conducted using inclined pin-on-plate sliding tester to understand the effect of directionality of surface grinding marks of hard material on friction and transfer layer formation during sliding against soft materials. 080 M40 steel plates were ground to attain different surface roughness with unidirectional grinding marks. Then pins made of soft materials such as pure Al, pure Mg and Al-Mg alloy were slid against the prepared steel plates. Grinding angle (i.e., the angle between direction of sliding and grinding marks) was varied between 0 degrees and 90 degrees in the tests. Experiments were conducted under both dry and lubricated conditions on each plate in ambient environment. It was observed that the transfer layer formation and the coefficient of friction, which has two components adhesion and plowing - depend primarily on the directionality of grinding marks of the harder mating surface, and independent of surface roughness of the harder mating surface. For the case of pure Mg, stick-slip phenomenon was observed under dry condition for all grinding angles and it was absent upto 20 degrees grinding angles under lubricated condition. However, for the case of Al, it was observed only under lubricated conditions for angles exceeding 20 degrees. As regards the alloy, namely, Al-Mg alloy, it, was absent in both conditions. For the case of pure Mg and Al, it was observed that the amplitude of stick-slip motion primarily depends on plowing component of friction. The grinding angle effect on coefficient of friction was attributed to the variation of plowing component of friction with grinding angle.

Effect of directionality of unidirectional grinding marks on friction and transfer layer formation of Mg on steel using inclined scratch test

Surface topography has been known to play an important role in the friction and transfer layer formation during sliding. In the present investigation, EN8 steel flats were ground to attain different surface roughness with unidirectional grinding marks. Pure Mg pins were scratched on these surfaces using an Inclined Scratch Tester to study the influence of directionality of surface grinding marks on coefficient of friction and transfer layer formation. Grinding angle (i.e., the angle between direction of scratch and grinding marks) was varied between 0 degrees and 90 degrees during the tests. Experiments were conducted under both dry and lubricated conditions. Scanning electron micrographs of the contact surfaces of pins and flats were used to reveal the surface features that included the morphology of the transfer layer. It was observed that the average coefficient of friction and transfer layer formation depend primarily on the directionality of the grinding marks but were independent of surface roughness on the harder mating surface. In addition, a stick-slip phenomenon was observed, the amplitude of which depended both on the directionality of grinding marks and the surface roughness of the harder mating surface. The grinding angle effect on the coefficient of friction, which consists of adhesion and plowing components, was attributed to the variation of plowing component of friction. (c) 2006 Elsevier B.V. All rights reserved.

In-process grinding monitoring by 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 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. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. Many statistics have shown effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm (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.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

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.

Advanced ceramics: Evaluation of the mechanism of stock removal and ground surface quality

The aim of this work is to evaluate the mechanism of stock removal and the ground surface quality of advanced ceramics machined by a surface grinding process using diamond grinding wheels. The analysis of the grinding performance was done regarding the cutting surface wear behavior of the grinding wheel for ceramic workpieces. The ground surface was evaluated using Scanning Electron Microscopy (SEM). As a result it can be said that the mechanism of material removal in the grinding of ceramic is largely one of brittle fracture. The increase of the hmax can reduce the tangential force required by the process. Although, it results in an increase in the surface damage, reducing the mechanical properties of the ground component.

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.

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.