994 resultados para Machining time


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An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine's capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine's potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

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根据对零件制造精度和效率的关注程度的不同,开发出了多种分层算法。在同等加工时间的情况下,根据加工精度的不同,将这些分层算法分为等层厚分层算法和适应性分层算法两类。通过对STL模型、原始CAD模型和点云数据的分析,讨论了两类分层算法的研究和发展,然后介绍了斜边分层算法和曲面分层算法等先进分层算法的原理和成果,最后讨论了快速成型分层算法的研究方向和趋势。

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Titanium and its alloys provide high strength-to-weight ratios, good fatigue strength and increased corrosion resistance compared with others materials. Its acceptance in aerospace has been limited by costs considerations such as high cost of raw material, high buy-to-fly ratios and expensive machining operations. Significant cost reductions can be obtained by vacuum sintering and powder metallurgy (P/M) techniques by producing near net shapes and consequently minimizing material waste and machining time. The Ti 35Nb alloy exhibit a low modulus of elasticity. Stemming from the unique combination of high strength, low modulus of elasticity and low density, this alloy is intrinsically more resistant to shock and explosion damages than most other engineering materials. Samples were produced by mixing of initial metallic powders followed by uniaxial and cold isostatic pressing with subsequent densification by sintering between 900 and 1600 °C, in vacuum. Sintering behavior was studied by means of dilatometry. Sintered samples were characterized for phase composition, microstructure and microhardness by X-ray diffraction, scanning electron microscopy and Vickers indentation, respectively. Density was measured by Archimedes method. Copyright © 2004 Society of Automotive Engineers, Inc.

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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.

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Currently productivity is a concern in large firms and in heavy machining industries could not be otherwise . The issue of time in the process becomes a relevant and worthy of analysis point , especially that the setup time becomes a critical issue to be addressed . Due to the size of the equipment studied ( heavy machining ) and especially with regard to the characteristics of the machine tool and the parts to be machined , generally robust and large parts , the preparation of such parts shall be made accurately to the machining has a good result as planned . With the setup acting as a limiter of productivity growth in this sector , actions constantly in search of reducing downtimes and optimization are taken . This study aimed to conduct a study that confirms increased productivity by reducing the machining time , especially setup time and also with the implementation of organizational tools. Actions taken in heavy machining industry Arm L- 580 Liebherr company in Brazil specifically in CNC Boring PAMA Speedram 3000 were analyzed . Through a qualitative study using the method of case study , it was examined before and after the sector and reducing setup times . Evidencing the shares through figures and collection times . The end result of this analysis was to verify that through simple actions productivity and organization in the area were directly affected in a positive way , and supporting organizational change throughout training were taught to be incorporated into the company culture

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La mejora continua de los procesos de fabricación es fundamental para alcanzar niveles óptimos de productividad, calidad y coste en la producción de componentes y productos. Para ello es necesario disponer de modelos que relacionen de forma precisa las variables que intervienen en el proceso de corte. Esta investigación tiene como objetivo determinar la influencia de la velocidad de corte y el avance en el desgaste del flanco de los insertos de carburos recubiertos GC1115 y GC2015 y en la rugosidad superficial de la pieza mecanizada de la pieza en el torneado de alta velocidad en seco del acero AISI 316L. Se utilizaron entre otros los métodos de observación científica, experimental, medición, inteligencia artificial y estadísticos. El inserto GC1115 consigue el mejor resultado de acuerdo al gráfico de medias y de las ecuaciones de regresión múltiple de desgaste del flanco para v= 350 m/min, mientras que para las restantes velocidades el inserto GC2015 consigue el mejor desempeño. El mejor comportamiento en cuanto a la rugosidad superficial de la pieza mecanizada se obtuvo con el inserto GC1115 en las velocidades de 350 m/min y 400 m/min, en la velocidad de 450 m/min el mejor resultado correspondió al inserto GC2015. Se analizaron dos criterios nuevos, el coeficiente de vida útil de la herramienta de corte en relación al volumen de metal cortado y el coeficiente de rugosidad superficial de la pieza mecanizada en relación al volumen de metal cortado. Fueron determinados los modelos de regresión múltiple que permitieron calcular el tiempo de mecanizado de los insertos sin que alcanzaran el límite del criterio de desgaste del flanco. Los modelos desarrollados fueron evaluados por sus capacidades de predicción con los valores medidos experimentalmente. ABSTRACT The continuous improvement of manufacturing processes is critical to achieving optimal levels of productivity, quality and cost in the production of components and products. This is necessary to have models that accurately relate the variables involved in the cutting process. This research aims to determine the influence of the cutting speed and feed on the flank wear of carbide inserts coated by GC1115 and GC2015 and the surface roughness of the workpiece for turning dry high speed steel AISI 316L. Among various scientific methods this study were used of observation, experiment, measurement, statistical and artificial intelligence. The GC1115 insert gets the best result according to the graph of means and multiple regression equations of flank wear for v = 350 m / min, while for the other speeds the GC2015 insert gets the best performance. Two approaches are discussed, the life ratio of the cutting tool relative to the cut volume and surface roughness coefficient in relation to the cut volume. Multiple regression models were determined to calculate the machining time of the inserts without reaching the limit of the criterion flank wear. The developed models were evaluated for their predictive capabilities with the experimentally measured values.

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A parallel kinematic machine (PKM) topology can only give its best performance when its geometrical parameters are optimized. In this paper, dimensional synthesis of a newly developed PKM is presented for the first time. An optimization method is developed with the objective to maximize both workspace volume and global dexterity of the PKM. Results show that the method can effectively identify design parameter changes under different weighted objectives. The PKM with optimized dimensions has a large workspace to footprint ratio and a large well-conditioned workspace, hence justifies its suitability for large volume machining.

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The Glenn Research Centre of NASA, USA (www.grc.nasa.gov/WWW/SiC/, silicon carbide electronics) is in pursuit of realizing bulk manufacturing of silicon carbide (SiC), specifically by mechanical means. Single point diamond turning (SPDT) technology which employs diamond (the hardest naturally-occurring material realized to date) as a cutting tool to cut a workpiece is a highly productive manufacturing process. However, machining SiC using SPDT is a complex process and, while several experimental and analytical studies presented to date aid in the understanding of several critical processes of machining SiC, the current knowledge on the ductile behaviour of SiC is still sparse. This is due to a number of simultaneously occurring physical phenomena that may take place on multiple length and time scales. For example, nucleation of dislocation can take place at small inclusions that are of a few atoms in size and once nucleated, the interaction of these nucleations can manifest stresses on the micrometre length scales. The understanding of how stresses manifest during fracture in the brittle range, or dislocations/phase transformations in the ductile range, is crucial in understanding the brittle–ductile transition in SiC. Furthermore, there is a need to incorporate an appropriate simulation-based approach in the manufacturing research on SiC, owing primarily to the number of uncertainties in the experimental research that includes wear of the cutting tool, poor controllability of the nano-regime machining scale (effective thickness of cut), and coolant effects (interfacial phenomena between the tool, workpiece/chip and coolant), etc. In this review, these two problems are combined together to posit an improved understanding on the current theoretical knowledge on the SPDT of SiC obtained from molecular dynamics simulation.

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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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INVESTIGATION INTO CURRENT EFFICIENCY FOR PULSE ELECTROCHEMICAL MACHINING OF NICKEL ALLOY Yu Zhang, M.S. University of Nebraska, 2010 Adviser: Kamlakar P. Rajurkar Electrochemical machining (ECM) is a nontraditional manufacturing process that can machine difficult-to-cut materials. In ECM, material is removed by controlled electrochemical dissolution of an anodic workpiece in an electrochemical cell. ECM has extensive applications in automotive, petroleum, aerospace, textile, medical, and electronics industries. Improving current efficiency is a challenging task for any electro-physical or electrochemical machining processes. The current efficiency is defined as the ratio of the observed amount of metal dissolved to the theoretical amount predicted from Faraday’s law, for the same specified conditions of electrochemical equivalent, current, etc [1]. In macro ECM, electrolyte conductivity greatly influences the current efficiency of the process. Since there is a certain limit to enhance the conductivity of the electrolyte, a process innovation is needed for further improvement in current efficiency in ECM. Pulse electrochemical machining (PECM) is one such approach in which the electrolyte conductivity is improved by electrolyte flushing in pulse off-time. The aim of this research is to study the influence of major factors on current efficiency in a pulse electrochemical machining process in macro scale and to develop a linear regression model for predicting current efficiency of the process. An in-house designed electrochemical cell was used for machining nickel alloy (ASTM B435) by PECM. The effects of current density, type of electrolyte, and electrolyte flow rate, on current efficiency under different experimental conditions were studied. Results indicated that current efficiency is dependent on electrolyte, electrolyte flow rate, and current density. Linear regression models of current efficiency were compared with twenty new data points graphically and quantitatively. Models developed were close enough to the actual results to be reliable. In addition, an attempt has been made in this work to consider those factors in PECM that have not been investigated in earlier works. This was done by simulating the process by using COMSOL software. However, it was found that the results from this attempt were not substantially different from the earlier reported studies.

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Product miniaturization for applications in fields such as biotechnology, medical devices, aerospace, optics and communications has made the advancement of micromachining techniques essential. Machining of hard and brittle materials such as ceramics, glass and silicon is a formidable task. Rotary ultrasonic machining (RUM) is capable of machining these materials. RUM is a hybrid machining process which combines the mechanism of material removal of conventional grinding and ultrasonic machining. Downscaling of RUM for micro scale machining is essential to generate miniature features or parts from hard and brittle materials. The goal of this thesis is to conduct a feasibility study and to develop a knowledge base for micro rotary ultrasonic machining (MRUM). Positive outcome of the feasibility study led to a comprehensive investigation on the effect of process parameters. The effect of spindle speed, grit size, vibration amplitude, tool geometry, static load and coolant on the material removal rate (MRR) of MRUM was studied. In general, MRR was found to increase with increase in spindle speed, vibration amplitude and static load. MRR was also noted to depend upon the abrasive grit size and tool geometry. The behavior of the cutting forces was modeled using time series analysis. Being a vibration assisted machining process, heat generation in MRUM is low which is essential for bone machining. Capability of MRUM process for machining bone tissue was investigated. Finally, to estimate the MRR a predictive model was proposed. The experimental and the theoretical results exhibited a matching trend.

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Deep hole drilling is one of the most complicated metal cutting processes and one of the most difficult to perform on CNC machine-tools or machining centres under conditions of limited manpower or unmanned operation. This research work investigates aspects of the deep hole drilling process with small diameter twist drills and presents a prototype system for real time process monitoring and adaptive control; two main research objectives are fulfilled in particular : First objective is the experimental investigation of the mechanics of the deep hole drilling process, using twist drills without internal coolant supply, in the range of diarneters Ø 2.4 to Ø4.5 mm and working length up to 40 diameters. The definition of the problems associated with the low strength of these tools and the study of mechanisms of catastrophic failure which manifest themselves well before and along with the classic mechanism of tool wear. The relationships between drilling thrust and torque with the depth of penetration and the various machining conditions are also investigated and the experimental evidence suggests that the process is inherently unstable at depths beyond a few diameters. Second objective is the design and implementation of a system for intelligent CNC deep hole drilling, the main task of which is to ensure integrity of the process and the safety of the tool and the workpiece. This task is achieved by means of interfacing the CNC system of the machine tool to an external computer which performs the following functions: On-line monitoring of the drilling thrust and torque, adaptive control of feed rate, spindle speed and tool penetration (Z-axis), indirect monitoring of tool wear by pattern recognition of variations of the drilling thrust with cumulative cutting time and drilled depth, operation as a data base for tools and workpieces and finally issuing of alarms and diagnostic messages.

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The mechanism of "Helical Interference" in milled slots is examined and a coherent theory for the geometry of such surfaces is presented. An examination of the relevant literature shows a fragmented approach to the problem owing to its normally destructive nature, so a complete analysis is developed for slots of constant lead, thus giving a united and exact theory for many different setting parameters and a range of cutter shapes. For the first time, a theory is developed to explain the "Interference Surface" generated in variable lead slots for cylindrical work and attention is drawn to other practical surfaces, such as cones, where variable leads are encountered. Although generally outside the scope of this work, an introductory analysis of these cases is considered in order to develop the cylindrical theory. Special emphasis is laid upon practical areas where the interference mechanism can be used constructively and its application as the rake face of a cutting tool is discussed. A theory of rake angle for such cutting tools is given for commonly used planes, and relative variations in calculated rake angle between planes is examined. Practical tests are conducted to validate both constant lead and variable lead theories and some design improvements to the conventional dividing head are suggested in order to manufacture variable lead workpieces, by use of a "superposed" rotation. A prototype machine is manufactured and its kinematic principle given for both linear and non-linearly varying superposed rotations. Practical workpieces of the former type are manufactured and compared with analytical predictions,while theoretical curves are generated for non-linear workpieces and then compared with those of linear geometry. Finally suggestions are made for the application of these principles to the manufacture of spiral bevel gears, using the "Interference Surface" along a cone as the tooth form.

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Diffusion equations that use time fractional derivatives are attractive because they describe a wealth of problems involving non-Markovian Random walks. The time fractional diffusion equation (TFDE) is obtained from the standard diffusion equation by replacing the first-order time derivative with a fractional derivative of order α ∈ (0, 1). Developing numerical methods for solving fractional partial differential equations is a new research field and the theoretical analysis of the numerical methods associated with them is not fully developed. In this paper an explicit conservative difference approximation (ECDA) for TFDE is proposed. We give a detailed analysis for this ECDA and generate discrete models of random walk suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation. The stability and convergence of the ECDA for TFDE in a bounded domain are discussed. Finally, some numerical examples are presented to show the application of the present technique.