Effect of different methods of cutting fluid application on turning of a difficult-to-machine steel (SAE EV-8)

In this study, different methods of cutting fluid application are used in turning of a difficult-to-machine steel (SAE EV-8). Initially, a semisynthetic cutting fluid was applied using a conventional method (i.e. overhead flood cooling), minimum quantity of cutting fluid, and pulverization. A lubricant of vegetable oil (minimum quantity of lubricant) was also applied using the minimum quantity method. Thereafter, a cutting fluid jet under high pressure (3.0 MPa) was singly applied in the following regions: chip-tool interface, top surface of the chip (between workpiece and chip) and tool-workpiece contact. Moreover, two other methods were used: an interflow between conventional application and chip-tool interface jet (combined method) and, finally, three jets simultaneously applied. In order to carry out these tests, it was necessary to set up a high-pressure system using a piston pump for generating a cutting fluid jet, a venturi for fluid application (minimum quantity of cutting fluid and minimum quantity of lubricant) and a nozzle for cutting fluid pulverization. The output variables analyzed included tool life, surface roughness, cutting tool temperature, cutting force, chip form, chip compression rate and machined specimen microstructure. Among the results, it can be observed that the tool life increases and the cutting force decreases with the application of cutting fluid jet, mainly when it is directed to the chip-tool interface. Excluding the methods involving jet fluid, the conventional method seems to be more efficient than other methods of low pressure, such as minimum quantity of volume and pulverization, when considering just the cutting tool wear. © 2013 IMechE.

Different methods of cutting fluid application on turning of a difficult-to-machine steel

Different methods of cutting fluid application are used on turning of a difficult-tomachine steel (SAE EV-8). A semi-synthetic cutting fluid was applied using a conventional method, minimum quantity of cutting fluid (MQCF), and pulverization. By the minimum quantity method was also applied a lubricant of vegetable oil (MQL). Thereafter, a cutting fluid jet under high pressure (3.0 MPa) was singly applied in the following regions: chip-tool interface; top surface of the chip; and tool-workpiece contact. Two other methods were used: an interflow between conventional application and chip-tool interface jet and, finally, three jets simultaneously applied. In order to carry out these tests, it was necessary to set up a high pressure system using a piston pump for generating a cutting fluid jet, a Venturi for fluid application (MQCF and MQL), and a nozzle for cutting fluid pulverization. The output variables analyzed included tool life, surface roughness, cutting tool temperature, cutting force, chip form, chip compression rate and machined specimen microstructure. It can be observed that the tool life increases and the cutting force decreases with the application of cutting fluid jet, mainly when it is directed to the chip-tool interface. Excluding the methods involving jet fluid, the conventional method seems to be more efficient than other methods of low pressure. © (2013) Trans Tech Publications, Switzerland.

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.

Use of slag/sugar cane bagasse ash (SCBA) blends in the production of alkali-activated materials

Blast furnace slag (BFS)/sugar cane bagasse ash (SCBA) blends were assessed for the production of alkali-activated pastes and mortars. SCBA was collected from a lagoon in which wastes from a sugar cane industry were poured. After previous dry and grinding processes, SCBA was chemically characterized: it had a large percentage of organic matter (ca. 25%). Solutions of sodium hydroxide and sodium silicate were used as activating reagents. Different BFS/SCBA mixtures were studied, replacing part of the BFS by SCBA from 0 to 40% by weight. The mechanical strength of mortar was measured, obtaining values about 60 MPa of compressive strength for BFS/SCBA systems after 270 days of curing at 20 °C. Also, microstructural properties were assessed by means of SEM, TGA, XRD, pH, electrical conductivity, FTIR spectroscopy and MIP. Results showed a good stability of matrices developed by means of alkali-activation. It was demonstrated that sugar cane bagasse ash is an interesting source for preparing alkali-activated binders. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Prospects for the use of municipal tree pruning wastes in particleboard production

The purpose of this study was to evaluate the physical and mechanical properties of particleboard made with pruning wastes from Ipê (Tabebuia serratifolia) and Chapéu-de-Sol (Terminalia catappa) trees. Particleboards were prepared with both wood species, using all the material produced by grinding the pruning wastes. The particleboards had dimensions of 45×45 cm, a thickness of approximately 11.5 mm and an average density of 664 kg/m3. A urea-formaldehyde adhesive was used in the proportion of 12% of the dry particle mass. The particleboards were pressed at a temperature of 130 C for 10 mins. The physical and mechanical properties analyzed were density, moisture content, thickness swelling, percentage of lignin and cellulose, modulus of resilience, modulus of elasticity and tensile strength parallel to the grain, accordingly to the standards NBR 14810 and CS 236-66 (1968). The particleboards were considered to be of medium density. The particle size significantly affected the static bending strength and tensile strength parallel to the grain. Ipê presented better results, demonstrating a potential for the production and use of particleboard made from this species. © The Author(s) 2013.

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.

Fontes e doses de potássio na cultura do café (Coffea arabica L.)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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)

Avaliação de modelos neurais aplicados na estimação de parâmetros da retificação de cerâmicas avançadas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimação do diâmetro de furos em processo de furação utilizando sistemas de inteligência artificial: uma análise comparativa entre diferentes técnicas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação de níveis de desgaste de dressadores de ponta única utilizando sinais de emissão acústica e redes neurais artificiais

Pós-graduação em Engenharia Elétrica - FEB

Efeito da hidrólise enzimática seguida da moagem em moinho de bolas sobre as características estruturais e físico-químicas do amido de madioquinha-salsa

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Retificação da alumina com rebolo diamantado usando diferentes métodos de lubri-refrigeração

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de superfícies de peças retificadas com o uso de redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Resistência adesiva de reparos em resina composta: tratamento da superfície com ponta diamantada, jato de óxido de alumínio e laser de Er:YAG

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)