Grinding Of Advanced Ceramics Research Articles

The wear mechanisms of diamond grits in grinding of alumina and yttria-stabilized zirconia under different cooling-lubrication schemes

Abrasion is the primary wear mechanism of diamond grits during grinding of advanced ceramics. This work not only highlights some unreported modes of wear of diamond grits but also illustrates and describes their mechanisms while grinding two dissimilar advanced ceramics, viz. alumina and yttria-stabilized zirconia (YSZ). Long-cycle plunge grinding of the ceramics was conducted with single-layer electroplated diamond wheels at 30 m/s and 50 m/s grinding speeds under three different cooling-lubrication schemes – flood cooling (FC), MQL-soluble oil (MQL-SO) and MQL-neat oil (MQL-NO). Radial wheel wear was measured employing indirect profilometry. Diamond grits on the electroplated wheels were observed under SEM before and after grinding to identify and characterize various modes of wear. Severe wheel loading was observed while grinding alumina and YSZ under FC and MQL-SO. Indentation fatigue fracture was found to be the dominant mode of diamond grit wear during alumina grinding under wheel loading conditions. The wear of diamond grits during YSZ grinding was dominated by thermal fatigue fracture at a higher grinding speed of 50 m/s. Thermal degradation of diamond grits was examined with Raman spectroscopy which revealed graphitization of some of the active diamond grits after YSZ grinding under FC and MQL-NO at 50 m/s.

The Correlation of Vibration Signal Features in Grinding of Advanced Ceramics

Monitoring the grinding of ceramics using the vibration signal has been presented as an alternative for the diagnosis of the workpiece surface. This paper has the objective of studying the vibration signal through spectral analysis in order to monitor the grinding process, and looking for the best parameters that could be related to the surface integrity in the finished workpieces of ceramics. Thus, grinding tests were carried out on alumina ceramic specimens in different depths of cut. The workpieces were evaluated after grinding process by measuring the surface roughness Ra and confocal microscopy. For monitoring was used an accelerometer and vibration signal was collected by an oscilloscope. Digital signal processing techniques were performed, identifying a range of frequencies between 800 Hz and 2 kHz that best correlate with the condition of the machined ceramic. There was a correlation between the vibration and the integrity of the ceramics workpiece after grinding process. Moreover, the increase of the vibration is directly proportional to the surface roughness each cutting depth used. It follows that the vibration can be used to monitor the grinding of ceramics due to their relationship with the condition of the workpieces.

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.

Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics

Grinding wheel wear, which is a very complex phenomenon, causes changes in most of the shapes and properties of the tool during machining, reducing the efficiency of the grinding operation and impairing workpiece quality. Therefore, monitoring the condition of the tool during the grinding process plays a key role in the quality of workpieces being manufactured. In this study, diamond tool wear was estimated during the grinding of advanced ceramics using intelligent systems composed of four types of neural networks. Experimental tests were performed on a surface grinding machine and tool wear was measured by the imprint method throughout the tests. Acoustic emission and cutting power signals were acquired during the tests and statistics were obtained from these signals. Training and validating algorithms were developed for the intelligent systems in order to automatically obtain the best estimation models. The combination of signals and statistics along with the intelligent systems brings an innovative aspect to the grinding process. The results indicate that the models are highly successful in estimating tool wear.

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 120μm, 70μm and 20μm. 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%.

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

The current work presents a study of alternative methods of cooling-lubrication for the external plunge grinding of advanced ceramics using diamond wheels. These two alternative methods, which are intended to reduce cutting fluid expenses, are commonly referred to as the optimized cooling-lubrication method and minimal quantity of lubrication (MQL). The techniques were evaluated by process monitoring and by the assessment of output variables such as tangential cutting force, G ratio, roundness errors, surface roughness, microstructure and residual stresses measured by X-ray diffraction. The obtained results showed that the two proposed techniques can replace the conventional cooling-lubrication method, i.e., flood coolant. In particular, optimized cooling-lubrication method reduced wheel wear and produced workpieces with the best geometric and dimensional finishes, while MQL significantly reduced the amount of fluid employed in the process without harming the workpiece quality.

Slot Grinding of Advanced Ceramics with Brazed Diamond Cut-Off Wheels

Based on the analysis of problems of diamond cut-off wheels used in slot grinding of ceramics at present, a brazed diamond cut-off wheel was produced and analyzed. Two typical advanced ceramics, alumina and silicon nitride, were used as the workpiece materials. In the experiments of slot grinding of ceramics, grinding ratio, wear process of the wheel and grinding quality of the work were studied. Experimental results showed that the brazed diamond cut-off wheel obtained good grinding ratio and abrasive resistance. The surface roughness of ground silicon nitride was better than that of alumina.

Numerical Simulation on Grinding of Advanced Ceramics

Ceramics are increasingly used in many advanced science and technology due to their excellent properties. Grinding is the most efficient and effective technique to achieve high dimensional accuracy and surface integrity of ground ceramic workpiece at optimum cost efficiency. The indentation/ scratch approaches are widely used in studying the grinding process. In this paper, the grinding technology and grinding induced damage of advanced ceramics are briefly reviewed. Based on MSC.Marc software, a FEM model for the Vicker’s indentation/scratch is established to simulate the abrasive grinding process, the stress and strain distribution in the advanced ceramics under a Vicker’s indenter are presented and discussed. The related elastic modulus is obtained by the nanoindentation tests.

High Speed Grinding of Advanced Ceramics: A Review

In this paper, the characteristics of high speed grinding of advanced ceramics, including alumina, alumina-titania, zirconia, silicon nitride and silicon carbide, were reviewed. The associated material removal mechanisms were discussed. Pragmatic technologies for the high speed grinding of advanced ceramics were also presented.

Study on the grinding of advanced ceramics with slotted diamond wheels

Slotted diamond wheel grinding is a new machining technology. In this paper, an experimental study on the cutting force and the grinding temperature for ceramic face grinding using slotted diamond wheels is presented. Moreover, the empirical relationships related with the material removal rate, the surface roughness, the depth of cut, the wheel speed and the grain size are discussed. With these relationships, a temperature field for face grinding has been built. The work contributes to the fundamental theories for optimal design of slotted diamond wheels.

Basics of Process Parameter Selection in Grinding of Advanced Ceramics

The operational properties and the performance of components consisting of advanced ceramic materials, for example silicon carbide and silicon nitride, are mainly influenced by processing technology and process conditions. In grinding operations grain engagement and process kinematics determine the resulting surface topography as well as the degree of potential rim defects. The modelling of grain engagement and the computation of uncut chip thickness describe suitable ranges for process parameters resulting in minimized subsurface damages of the ceramic part. By means of single grain diamond scratch tests the limiting uncut chip thickness at the transition between plastic deformation of workpiece material and the occurrence of brittle microchippings during chip removal is evaluated. Based on theoretical models and experimental investigations a contribution to practical applications in grinding of advanced ceramics is explained.

Grinding of advanced ceramics.

Grinding of advanced ceramics.