Analysis of the Influence of Sparkout Time on Grinding Using Several Lubrication/Cooling Methods

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Application of the Minimum Quantity Lubrication (MQL) Technique in the Plunge Cylindrical Grinding Operation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Investigation on Surface Finishing of Components Ground with Lapping Kinematics: Lapgrinding Process

Over the last three decades, researchers have responded to the demands of industry to manufacture mechanical components with geometrical tolerance, dimensional tolerance, and surface finishing in nanometer levels. The new lapgrinding process developed in Brazil utilizes lapping kinematics and a flat grinding wheel dressed with a single-point diamond dresser in agreement with overlap factor (U(d)) theory. In the present work, the influences of different U(d) values on dressing (U(d) = 1, 3 e 5) and grain size of the grinding wheel made of silicon carbide (SiC = 800, 600 e 300 mesh) are analyzed on surface finishing of stainless steel AISI 420 flat workpieces submitted to the lapgrinding process. The best results, obtained after 10 minutes of machining, were: average surface roughness (Ra) 1.92 nm; 1.19 mu m flatness deviation of 25.4 mm diameter workpieces and mirrored surface finishing. Given the surface quality achieved, the lapgrinding process can be included among the ultra-precision finishing processes and, depending on the application, the steps of lapping followed by polishing can be replaced by the proposed abrasive process.

Performance of aerodynamic baffles in cylindrical grinding analyzed on the basis of air layer pressure and speed

Over the years, grinding has been considered one of the most important manufacturing processes. Grinding is a high precision process, and the loss of a single workpiece in this stage of the production is unacceptable, fir the value added to the material is very high due to many processes it has already undergone prior to grinding. This study aims to contribute toward the development of an experimental methodology whereby the pressure and speed of the air layer produced by the high rotation of the grinding wheel is evaluated with and without baffles, i.e., in an optimized grinding operation and in a traditional one. Tests were also carried out with steel samples to check the difference in grinding wheel wear with and without the use of baffles.

Influence of the grinding wheel's dive speed on the damage of rectified hardened steels

The world tendency is the increase of the productivity and the production of pieces more and more sophisticated, with high degree of geometric and dimensional tolerances, with good surface finish and low cost. Rectification is responsible for the final finish in the machining process of a material. However, damages generated in this production phase affect all the resources used in the previous processes. Great part of the problems happennig in the rectification process is due to the enormous temperature generated in this activity because of the machining conditions. The dive speed, which is directly related to the productivity, is considered responsible for the damages that occur during rectification, limiting its values to those that do not cause such damages. In this work, through the variation of the dive speed in the process of cylindrical grinding of type ABNT D6 steel, rationalizing the application of two cutting fluids and using a CBN (cubic boron nitrate) abrasive wheel with vitrified blond, the influence of the dive speed on the surface damages of hardened steels was evaluated. The results allowed to say that the dive speed, associated to an efficient cooling and lubrication, didn't provoke thermal damages (including heated zones, cracks and tension stresses) to the material. Residual stresses and the roughness of rectified materials presented a correlation with the machining conditions. The work concluded that it is possible to increase the productivity without provoking damages in the rectified components.

Influence of grinding on the roundness, residual stresses and microstructure of VC131 steel analysed by varying the type of cutting fluid

This paper by R. E. Catai, E. C. Bianchi, P. R de Águia and M. C. Alves reports on the results of an analysis made of roundness errors, residual stresses, and SEM micrographs of VC131 steel. The analysis involved workpieces ground with two types of cutting fluid: synthetic cutting fluid and emulsive oil. In this study, the cutting parameters were kept constant while the type of cutting fluid was varied. The amount of cutting fluid injected in the process was also varied, aiming to identify the ideal amount required to obtain good results without causing structural damage to the workpiece. The SEM analyses of roundness errors and residual stresses revealed that, of the two cutting fluids, emulsive oil provided better tensions due to its greater lubricating power.

Utilization of teflon and aluminum oxide for wheel cleaning in Minimum Quantity Lubrication (MQL) grinding

Researches concerning cooling-lubrication optimization in grinding have been conducted to contribute to a more sustainable process. An alternative to flood coolant is minimum quantity lubrication (MQL), which spray oil droplets in a compressed air jet. However, problems related to wheel cleaning were reported, due to wheel loading by a mixture of chips and oil, resulting in worsening of surface quality. This work aims to evaluate the viability of Teflon and aluminum oxide for wheel cleaning, compared to MQL without cleaning and MQL with cleaning by compressed air, through the following output variables: surface roughness, roundness, wheel wear, grinding power and acoustic emission. Vickers microhardness measurements and optical microscopy were also carried out. The results showed that both materials were efficient in cleaning the wheel, compared to MQL without cleaning, but not as satisfactory as compressed air. Much work is to be done in order to select the right material for wheel cleaning.

Evaluation of different methods of cooling-lubrication in cylindrical grinding of advanced ceramic dip

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Neural tool condition estimation in the grinding of advanced ceramics

Ceramic parts are increasingly replacing metal parts due to their excellent physical, chemical and mechanical properties, however they also make them difficult to manufacture by traditional machining methods. The developments carried out in this work are used to estimate tool wear during the grinding of advanced ceramics. The learning process was fed with data collected from a surface grinding machine with tangential diamond wheel and alumina ceramic test specimens, in three cutting configurations: with depths of cut of 120 mu m, 70 mu m and 20 mu m. The grinding wheel speed was 35m/s and the table speed 2.3m/s. Four neural models were evaluated, namely: Multilayer Perceptron, Radial Basis Function, Generalized Regression Neural Networks and the Adaptive Neuro-Fuzzy Inference System. The models'performance evaluation routines were executed automatically, testing all the possible combinations of inputs, number of neurons, number of layers, and spreading. The computational results reveal that the neural models were highly successful in estimating tool wear, since the errors were lower than 4%.

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

A study on the viability of minimum quantity lubrication with water in grinding of ceramics using a hybrid-bonded diamond wheel

With the currently strict environmental law in present days, researchers and industries are seeking to reduce the amount of cutting fluid used in machining. Minimum quantity lubrication is a potential alternative to reduce environmental impacts and overall process costs. This technique can substantially reduce cutting fluids in grinding, as well as provide better performance in relation to conventional cutting fluid application (abundant fluid flow). The present work aims to test the viability of minimum quantity lubrication (with and without water) in grinding of advanced ceramics, when compared to conventional method (abundant fluid flow). Measured output variables were grinding power, surface roughness, roundness errors and wheel wear, as well as scanning electron micrographs. The results show that minimum quantity lubrication with water (1:1) was superior to conventional lubrication-cooling in terms of surface quality, also reducing wheel wear, when compared to the other methods tested.