997 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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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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This study presents the information required to describe the machine and device resources in the turret punch press environment which are needed for the development of the analysing method for automated production. The description of product and device resources and their interconnectedness is the starting point for method comparison the development of expenses, production planning and the performance of optimisation. The manufacturing method cannot be optimized unless the variables and their interdependence are known. Sheet metal parts in particular may then become remarkably complex, and their automatic manufacture may be difficult or, with some automatic equipment, even impossible if not know manufacturing properties. This thesis consists of three main elements, which constitute the triangulation. In the first phase of triangulation, the manufacture occuring on a turret punch press is examined in order to find the factors that affect the efficiency of production. In the second phase of triangulation, the manufacturability of products on turret punch presses is examined through a set of laboratory tests. The third phase oftriangulation involves an examination of five industry parts. The main key findings of this study are: all possible efficiency in high automation level machining cannot be achieved unless the raw materials used in production and the dependencies of the machine and tools are well known. Machine-specific manufacturability factors for turret punch presses were not taken into account in the industrial case samples. On the grounds of the performed tests and industrial case samples, the designer of a sheet metal product can directly influence the machining time, material loss, energy consumption and the number of tools required on a turret punch press by making decisions in the way presented in the hypothesis of thisstudy. The sheet metal parts to be produced can be optimised to bemanufactured on a turret punch press when the material to be used and the kinds of machine and tool options available are known. This provides in-depth knowledge of the machine and tool properties machine and tool-specifically. None of the optimisation starting points described here is a separate entity; instead, they are all connected to each other.

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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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Conventional threading operations involve two distinct machining processes: drilling and threading. Therefore, it is time consuming for the tools must be changed and the workpiece has to be moved to another machine. This paper presents an analysis of the combined process (drilling followed by threading) using a single tool for both operations: the tap-milling tool. Before presenting the methodology used to evaluate this hybrid tool, the ODS (operating deflection shapes) basics is shortly described. ODS and finite element modeling (FEM) were used during this research to optimize the process aiming to achieve higher stable machining conditions and increasing the tool life. Both methods allowed the determination of the natural frequencies and displacements of the machining center and optimize the workpiece fixture system. The results showed that there is an excellent correlation between the dynamic stability of the machining center-tool holder and the tool life, avoiding a tool premature catastrophic failure. Nevertheless, evidence showed that the tool is very sensitive to work conditions. Undoubtedly, the use of ODS and FEM eliminate empiric decisions concerning the optimization of machining conditions and increase drastically the tool life. After the ODS and FEM studies, it was possible to optimize the process and work material fixture system and machine more than 30,000 threaded holes without reaching the tool life limit and catastrophic fail.

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This paper presents a reliability-based analysis for calculating critical tool life in machining processes. It is possible to determine the running time for each tool involved in the process by obtaining the operations sequence for the machining procedure. Usually, the reliability of an operation depends on three independent factors: operator, machine-tool and cutting tool. The reliability of a part manufacturing process is mainly determined by the cutting time for each job and by the sequence of operations, defined by the series configuration. An algorithm is presented to define when the cutting tool must be changed. The proposed algorithm is used to evaluate the reliability of a manufacturing process composed of turning and drilling operations. The reliability of the turning operation is modeled based on data presented in the literature, and from experimental results, a statistical distribution of drilling tool wear was defined, and the reliability of the drilling process was modeled. (C) 2010 Elsevier Ltd. All rights reserved.

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The use of high-strength aluminium alloys as material for injection molding tools to produce small and medium batches of plastic products as well as prototyping molds is becoming of increasing demand by the tooling industry. These alloys are replacing the traditional use of steel in the cases above because they offer many advantages such as very high thermal conductivity associated with good corrosion and wear resistance presenting good machinability in milling and electrical discharge machining operations. Unfortunately there is little technological knowledge on the Electrical Discharge Machining (EDM) of high-strength aluminium alloys, especially about the AMP 8000 alloy. The duty factor, which means the ratio between pulse duration and pulse cycle time exerts an important role on the performance of EDM. This work has carried out an experimental study on the variation of the duty factor in order to analyze its influence on material removal rate and volumetric relative wear under roughing conditions of EDM process. The results showed that high values of duty factor are possible to be applied without bringing instability into the EDM process and with improvement of material removal rate and volumetric relative wear.

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Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to manufacture metal parts layer by layer by assist of laser beam. The development of the technology from building just prototype parts to functional parts is due to design flexibility. And also possibility to manufacture tailored and optimised components in terms of performance and strength to weight ratio of final parts. The study of energy and raw material consumption in LAM is essential as it might facilitate the adoption and usage of the technique in manufacturing industries. The objective this thesis was find the impact of LAM on environmental and economic aspects and to conduct life cycle inventory of CNC machining and LAM in terms of energy and raw material consumption at production phases. Literature overview in this thesis include sustainability issues in manufacturing industries with focus on environmental and economic aspects. Also life cycle assessment and its applicability in manufacturing industry were studied. UPLCI-CO2PE! Initiative was identified as mostly applied exiting methodology to conduct LCI analysis in discrete manufacturing process like LAM. Many of the reviewed literature had focused to PBF of polymeric material and only few had considered metallic materials. The studies that had included metallic materials had only measured input and output energy or materials of the process and compared to different AM systems without comparing to any competitive process. Neither did any include effect of process variation when building metallic parts with LAM. Experimental testing were carried out to make dissimilar samples with CNC machining and LAM in this thesis. Test samples were designed to include part complexity and weight reductions. PUMA 2500Y lathe machine was used in the CNC machining whereas a modified research machine representing EOSINT M-series was used for the LAM. The raw material used for making the test pieces were stainless steel 316L bar (CNC machined parts) and stainless steel 316L powder (LAM built parts). An analysis of power, time, and the energy consumed in each of the manufacturing processes on production phase showed that LAM utilises more energy than CNC machining. The high energy consumption was as result of duration of production. Energy consumption profiles in CNC machining showed fluctuations with high and low power ranges. LAM energy usage within specific mode (standby, heating, process, sawing) remained relatively constant through the production. CNC machining was limited in terms of manufacturing freedom as it was not possible to manufacture all the designed sample by machining. And the one which was possible was aided with large amount of material removed as waste. Planning phase in LAM was shorter than in CNC machining as the latter required many preparation steps. Specific energy consumption (SEC) were estimated in LAM based on the practical results and assumed platform utilisation. The estimated platform utilisation showed SEC could reduce when more parts were placed in one build than it was in with the empirical results in this thesis (six parts).

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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.