Improving minimum quantity lubrication in CBN grinding using compressed air wheel cleaning

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

Cerâmicas avançadas no processo de retificação cilíndrica externa de mergulho utilizando a técnica da mínima quantidade de lubrificação (MQL) com rebolos diamantados

Nas últimas duas décadas, as cerâmicas avançadas têm sido exaustivamente utilizadas em aplicações na indústria devido às suas propriedades de elevada resistência ao desgaste e dureza. Entretanto, ainda se tem um alto custo agregado ao acabamento da peça. Esse acabamento geralmente é feito pelo processo de retificação, único processo economicamente viável que produz superfícies de elevada qualidade e precisão geométrica. Nesse contexto, as empresas vêm buscando a otimização no processo de retificação como, por exemplo, a redução do fluxo de fluido de corte utilizado, o que também visa atender exigências mundiais de preservação ambiental. Desta forma, este projeto pretendeu explorar a técnica da Mínima Quantidade de Lubrificação (MQL) na retificação cilíndrica externa de mergulho em cerâmicas com rebolos diamantados. Foram utilizados dois métodos de refrigeração: o convencional e o MQL, com três avanços de corte para cada caso. Foram usados um bocal convencional e um bocal para o MQL, tendo este um uniformizador de saída do jato. Foram analisadas como variáveis de saída: a emissão acústica, relação G, aspecto da superfície via microscopia eletrônica de varredura (MEV), rugosidade e circularidade. Assim, embora a refrigeração convencional ainda apresente os melhores resultados em comparação com a refrigeração com MQL, esta última pode atender os requisitos necessários para diversas aplicações, em especial quando utilizadas baixas espessuras equivalentes de corte (h eq). Além disso, a técnica de MQL possui a vantagem de gerar um menor impacto ambiental em comparação com a lubrificação convencional, devido ao uso mínimo de fluido de corte cujo descarte é cada vez mais regulamentado e custoso.

Surface finishing of flat pieces when submitted to lapping kinematics on abrasive disc dressed under several overlap factors

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

Characterization and application of PZT/PU and graphite doped PZT/PU composite

Composites, made of lead zirconate titanate (PZT) ceramic powder and castor oil-based polyurethane (PU), were prepared in the film form. The films were obtained in the thickness range 100-300 mum using up to 50/50 vol.% of ceramic. Another composite (PZT/C/PU) was obtained by adding a small amount (1.0 vol.%) of graphite (C) to the PZT/PU composite. By increasing the conductivity of PU-containing graphite, polarization of PZT could be carried out with better efficiency. A comparison of piezo- and pyroelectric activities and spatial distribution of polarization between graphite doped and undoped composites reveal the advantages of using semiconductor filler. These composites were used as sensors to detect acoustic emission (AE). The detection was made using two simulated sources of AE, i.e., ball bearing drop and pencil lead break. PZT/C/PU composite was able to detect both flexural and extensional components of wave vibration. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Dressing monitoring with a digital signal processor

Grinding is a finishing process in machining operations, and the topology of the grinding tool is responsible for producing the desired result on the surface of the machined material The tool topology is modeled in the dressing process and precision is therefore extremely important This study presents a solution in the monitoring of the dressing process, using a digital signal processor (DSP) operating in real time to detect the optimal dressing moment To confirm the monitoring efficiency by DSP, the results were compared with those of a data acquisition system (DAQ) and offline processing The method employed here consisted of analyzing the acoustic emission and electrical power signal by applying the DPO and DPKS parameters The analysis of the results allowed us to conclude that the application of the DPO and DPKS parameters can be substituted by processing of the mean acoustic emission signal, thus reducing the computational effort

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.

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.

Automatic system for thermal damage detection in manufacturing process with Internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. 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.

Grinding of hardened steels using optimized cooling

Grinding - the final machining process of a workpiece - requires large amounts of cutting fluids for the lubrication, cooling and removal of chips. These fluids are highly aggressive to the environment. With the technological advances of recent years, the worldwide trend is to produce increasingly sophisticated components with very strict geometric and dimensional tolerances, good surface finish, at low costs, and particularly without damaging the environment. The latter requirement can be achieved by recycling cutting fluids, which is a costly solution, or by drastically reducing the amount of cutting fluids employed in the grinding process. This alternative was investigated here by varying the plunge velocity in the plunge cylindrical grinding of ABNT D6 steel, rationalizing the application of two cutting fluids and using a superabrasive CBN (cubic boron nitride) grinding wheel with vitrified binder to evaluate the output parameters of tangential cutting force, acoustic emission, roughness, roundness, tool wear, residual stress and surface integrity, using scanning electron microscopy (SEM) to examine the test specimens. The performance of the cutting fluid, grinding wheel and plunge velocity were analyzed to identify the best machining conditions which allowed for a reduction of the cutting fluid volume, reducing the machining time without impairing the geometric and dimensional parameters, and the surface finish and integrity of the machined components.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Influence of optimized lubrication-cooling and minimum quantity lubrication on the cutting forces, on the geometric quality of the surfaces and on the micro-structural integrity of hardened steel parts

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

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Lógica ANFIS aplicada na estimação da rugosidade e do desgaste da ferramenta de corte no processo de retificação plana de cerâmicas avançadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)