997 resultados para Cutting conditions
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Process planning is a very important industrial activity, since it determines how a part or a product is manufactured. Process planning decisions include machine selection, tool selection, and cutting conditions determination, and thus it is a complex activity. In the presence of unstable demand, flexibility has become a very important characteristic of today's successful industries, for which Flexible Manufacturing Systems (FMSs) have been proposed as a solution. However, we believe that FMS control software is not flexible enough to adapt to different manufacturing system conditions aiming at increasing the system's efficiency. One means to overcome this limitation is to include pre-planned alternatives in the process plan; then planning decisions are made by the control system in real time to select the most appropriate alternative according to the conditions of the shop floor. Some of the advantages of this approach reported in the literature are the reduction of the number of tool setups, and the selection of a replacement machine for executing an operation. To verify whether the presence of alternatives in process plans actually increases the efficiency of the manufacturing system, an investigation was carried out using simulation and design of experiments techniques for alternative plans on a single machine. The proposed methodology and the results are discussed within this paper.
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Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).
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To ensure quality of machined products at minimum machining costs and maximum machining effectiveness, it is very important to select optimum parameters when metal cutting machine tools are employed. Traditionally, the experience of the operator plays a major role in the selection of optimum metal cutting conditions. However, attaining optimum values each time by even a skilled operator is difficult. The non-linear nature of the machining process has compelled engineers to search for more effective methods to attain optimization. The design objective preceding most engineering design activities is simply to minimize the cost of production or to maximize the production efficiency. The main aim of research work reported here is to build robust optimization algorithms by exploiting ideas that nature has to offer from its backyard and using it to solve real world optimization problems in manufacturing processes.In this thesis, after conducting an exhaustive literature review, several optimization techniques used in various manufacturing processes have been identified. The selection of optimal cutting parameters, like depth of cut, feed and speed is a very important issue for every machining process. Experiments have been designed using Taguchi technique and dry turning of SS420 has been performed on Kirlosker turn master 35 lathe. Analysis using S/N and ANOVA were performed to find the optimum level and percentage of contribution of each parameter. By using S/N analysis the optimum machining parameters from the experimentation is obtained.Optimization algorithms begin with one or more design solutions supplied by the user and then iteratively check new design solutions, relative search spaces in order to achieve the true optimum solution. A mathematical model has been developed using response surface analysis for surface roughness and the model was validated using published results from literature.Methodologies in optimization such as Simulated annealing (SA), Particle Swarm Optimization (PSO), Conventional Genetic Algorithm (CGA) and Improved Genetic Algorithm (IGA) are applied to optimize machining parameters while dry turning of SS420 material. All the above algorithms were tested for their efficiency, robustness and accuracy and observe how they often outperform conventional optimization method applied to difficult real world problems. The SA, PSO, CGA and IGA codes were developed using MATLAB. For each evolutionary algorithmic method, optimum cutting conditions are provided to achieve better surface finish.The computational results using SA clearly demonstrated that the proposed solution procedure is quite capable in solving such complicated problems effectively and efficiently. Particle Swarm Optimization (PSO) is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. From the results it has been observed that PSO provides better results and also more computationally efficient.Based on the results obtained using CGA and IGA for the optimization of machining process, the proposed IGA provides better results than the conventional GA. The improved genetic algorithm incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. Finally, a comparison among these algorithms were made for the specific example of dry turning of SS 420 material and arriving at optimum machining parameters of feed, cutting speed, depth of cut and tool nose radius for minimum surface roughness as the criterion. To summarize, the research work fills in conspicuous gaps between research prototypes and industry requirements, by simulating evolutionary procedures seen in nature that optimize its own systems.
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Octopus skin samples were tested under quasi-static and scissor cutting conditions to measure the in-plane material properties and fracture toughness. Samples from all eight arms of one octopus were tested statically to investigate how properties vary from arm to arm. Another nine octopus skins were measured to study the influence of body mass on skin properties. Influence of specimen location on skin mechanical properties was also studied. Material properties of skin, i.e. the Young's modulus, ultimate stress, failure strain and fracture toughness have been plotted against the position of skin along the length of arm or body. Statistical studies were carried out to help analyzing experimental data obtained. Results of this work will be used as guidelines for the design and development of artificial skins for an octopus-inspired robot.
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The demand for plant material of Rhodiola rosea L. (Crassulaceae) for medicinal use has increased recently, amid concerns about its quality and sustainability. We have analysed the content of phenylpropanoids (total rosavins) and salidroside in liquid extracts from 3-year old cultivated plants of European origin, and mapped the influence of plant part (rhizome versus root), genotype, drying, cutting, and extraction solvent to chemical composition. Rhizomes contained 1.5-4 times more salidroside (0.3-0.4% dry wt) and total rosavins (1.2-3.0%) than roots. The qualitative decisive phenylpropanoid content in the extracts was most influenced by plant part, solvent, and genotype, while drying temperature and cutting conditions were of less importance. We have shown that R. rosea from different boreal European provenances can be grown under temperate conditions and identified factors to obtain consistent high quality extracts provided that authentic germplasm is used and distinguished between rhizome, roots and their mixtures.
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Silicon crystal exhibits a ductile regime during machining prior to the onset of fracture when appropriate cutting conditions are applied. The present study shows that the ductile regime is a result of a phase transformation which is indirectly evidenced by the amorphous phase detected in the machined surface. Transmission electron microscopy (TEM) planar view studies were successfully performed on monocrystalline silicon (1 0 0) single point diamond turned. TEM electron diffraction patterns show that the machined surface presents diffuse rings along with traces of crystalline material. This is attributed to crystalline silicon immersed in an amorphous matrix. Furthermore, only diffuse rings in the diffraction patterns of the ductile chip are detected, indicating that it is totally amorphous. © 2000 Elsevier Science B.V. All rights reserved.
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Grinding is a precision machining process which is widely used in the manufacture of components requiring fine tolerances and smooth surfaces. There are several imput parameters (cutting conditions, cutting fluid and grinding wheel type used, dressing conditions etc.) which can affect the process variables (tangential and normal cutting forces, roughness, grinding temperatures, G ratio, etc.) leading to differences in the roughness, in the surface integrity and in the mechanical strength of the ground component. Consequently, the imput parameters must be controlled in order to insure the workpiece final quality. This paper presents a comparative evaluation of the performance of two types of grinding wheels [a conventional (Al2O3) and a superabrasive (CBN)] when grinding a VC131 steel, by the analysis of specific process variables when varying the cutting conditions. Highest values of G ratio and lowest workpiece roughness was observed when using CBN grinding wheels. This confirms the global trend of replacement of alumina grinding wheels by CBN, when grinding DTG (difficult to grind) materials.
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This paper shows a research about the study of the chip's geometry generated in the diving cut-off operation, under several cutting conditions. As a result it was possible to verify tint the cutting conditions and the type of the material being cut can directly affect the chip's geometry.
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We report herein on a comparison of the performance of two different grinding wheels (conventional and CBN) in the transverse cylindrical grinding of a eutectic alloy. Three cutting conditions were tested: rough, semi-finishing and finishing. The parameters of evaluation were the cutting force, roughness and wheel wear. The optimal cutting force and roughness values were obtained when grinding with the conventional wheel, due to the superior dressing operation performed under every cutting condition tested. Although the CBN wheel presented the best G ratio values, they were lower than expected owing to the inappropriate dressing operation applied. Excessive wheel corner wear was detected in both wheels, caused by the grinding kinematics (transverse grinding) employed. In terms of cutting force and roughness, the conventional wheel proved to be the better choice under the conditions tested. However, in terms of the G ratio, a cost analysis is crucial to determine whether the differences between the wheels justify the use of the CBN wheel, in which case the dressing operation requires improvement.
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Due to their high hardness and wear resistance, Si3N4 based ceramics are one of the most suitable cutting tool materials for machining cast iron, nickel alloys and hardened steels. However, their high degree of brittleness usually leads to inconsistent results and sudden catastrophic failures. This necessitates a process optimization when machining superalloys with Si3N4 based ceramic cutting tools. The tools are expected to withstand the heat and pressure developed when machining at higher cutting conditions because of their high hardness and melting point. This paper evaluates the performance of α-SiAlON tool in turning Ti-6Al-4V alloy at high cutting conditions, up to 250 m min-1, without coolant. Tool wear, failure modes and temperature were monitored to access the performance of the cutting tool. Test results showed that the performance of α-SiAl0N tool, in terms of tool life, at the cutting conditions investigated is relatively poor due probably to rapid notching and excessive chipping of the cutting edge. These facts are associated with adhesion and diffusion wear rate that tends to weaken the bond strength of the cutting tool.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Engenharia Mecânica - FEIS
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)