α-SiAION: Development and machining test on gray cast iron

The α-SiAlON ceramic cutting tool insert is developed. Silicon nitride and additives powders are pressed and sintered in the form of cutting tool inserts at temperature of 1900 °C. The physics and mechanical properties of the inserts like green density, weight loss, relative density, hardness and fracture toughness are evaluated. Machining studies are conducted on grey cast iron workpiece to evaluate the performance of α-SiAlON ceramic cutting tool. In the paper the cutting tool used in higher speed showed an improvement in the tribological interaction between the cutting tools and the grey cast iron workpiece resulted in a significant reduction of flank wear and roughness, because of better accommodation and the presence of the graphite in gray cast iron. The above results are discussed in terms of their affect at machining parameters on gray cast iron.

Comparative study on turning CI and CGI using silicon nitride cutting tools

There has been a great interest for improving the machining of cast iron materials in the automotive and other industries. Comparative studies for tool used to machine grey cast iron (CI) and compacted graphite iron (CGI) on dry machining were also performed in order to find out why in this case the tool lifetime is not significantly higher. However the machining these materials while considering turning with the traditional high-speed steel and carbide cutting tools present any disadvantages. One of these disadvantages is that all the traditional machining processes involve the cooling fluid to remove the heat generated on workpiece due to friction during cutting. This paper present a new generation of ceramic cutting tool exhibiting improved properties and important advances in machining CI and CGI. The tool performance was analyzed in function of flank wear, temperature and roughness, while can be observed that main effects were found for tool wear, were abrasion to CI and inter-diffusion of constituting elements between tool and CGI, causing crater. However the difference in tool lifetime can be explained by the formation of a MnS layer on the tool surface in the case of grey CI. This layer is missing in the case of CGI.

Study of cutting forces on machinability properties of gray cast iron using new ceramics cutting tools

During gray cast iron cutting, the great rate of mechanical energy from cutting forces is converted into heat. Considerable heat is generated, principally in three areas: the shear zone, rake face and at the clearance side of the cutting edge. Excessive heat will cause undesirable high temperature in the tool which leads to softening of the tool and its accelerated wear and breakage. Nowadays the advanced ceramics are widely used in cutting tools. In this paper a composition special of Si3N4 was sintering, characterized, cut and ground to make SNGN120408 and applyed in machining gray cast iron with hardness equal 205 HB in dry cutting conditions by using digital controlled computer lathe. The tool performance was analysed in function of cutting forces, flank wear, temperature and roughness. Therefore metal removing process is carried out for three different cutting speeds (300 m/min, 600 m/min, and 800 m/min), while a cutting depth of 1 mm and a feed rate of 0.33 mm/rev are kept constant. As a result of the experiments, the lowest main cutting force, which depends on cutting speed, is obtained as 264 N at 600 m/min while the highest main cutting force is recorded as 294 N at 300 m/min.

Fast automatic microstructural segmentation of ferrous alloy samples using optimum-path forest

In this work we propose a novel automatic cast iron segmentation approach based on the Optimum-Path Forest classifier (OPF). Microscopic images from nodular, gray and malleable cast irons are segmented using OPF, and Support Vector Machines (SVM) with Radial Basis Function and SVM without kernel mapping. Results show accurate and fast segmented images, in which OPF outperformed SVMs. Our work is the first into applying OPF for automatic cast iron segmentation. © 2010 Springer-Verlag.

Cutting performance of diamond coated Si3N4 tool during turning

Silicon nitride cutting tools have been used successfully for machining hard materials, like: cast irons, nickel based alloys, etc. However these cutting tools with diamond coating present little information on dry turning operations of gray cast iron. In the present work, Si3N4 square inserts was developed, characterized and subsequently coated with diamond for dry machining operations on gray cast iron. All experiments were conducted with replica. It was used a 1500, 3000, 4500 m cutting length, feed rate of 0.33 mm/rev and keeping the depth of cut constant and equal to 1 mm. The results show that wear in the tool tips of the Si3N4 inserts, in all cutting conditions, was caused by both mechanical and chemical processes. To understand the tool wear mechanisms, a morphological analysis of the inserts, after experiments, has been performed by SEM and optical microscopy. Diamond coated PVD inserts showed to be capable to reach large cutting lengths when machining gray cast iron. © (2010) Trans Tech Publications.

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

A França nas crônicas de Mário de Andrade: o nacional e o estrangeiro no periódico Diário Nacional (1929-1932)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Influência dos elementos de liga nos parâmetros de processo de fundição de ferros fundidos especiais

Pós-graduação em Engenharia Mecânica - FEG