868 resultados para tool wear


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Tool wear is a very important subject affecting the economics of machining, especially in tapping, since it is one of the last operations to be performed within most operation sequences. In the present study, some aspects of tapping such as the mechanisms and types of wear were investigated in taps working at conventional and high-speed cutting (HSC). Additionally, different types of coatings and cooling /lubrication conditions were used. The tapping operation (M8 x 1.25) was performed in through holes with two cutting speeds (30 and 60 m/min) in grey cast iron GG25. Lubrication conditions tested were dry and with minimal quantity of lubricant. Tap materials were manufactured by powder metallurgy and coated with (TiAl)N and with TiCN. A go-non-go gauge criterion was used to assess tool life. The wear and surface aspects of the tools and workpiece were evaluated by scanning electron microscopy and energy dissipation spectroscopy. Torque signals were also measured during the tests. The main wear mechanism observed was adhesion, although some abrasion and diffusion may also have occurred, and the main type of wear was flank wear. The adhesion of workpiece material on the tool was the main and decisive factor ending tool life. Tool coatings proved to be an efficient way to minimize adhesion. Torque signals followed the same pattern as the flank wear and no significant change was observed when the cutting speed was increased.

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Huolimatta korkeasta automaatioasteesta sorvausteollisuudessa, muutama keskeinen ongelma estää sorvauksen täydellisen automatisoinnin. Yksi näistä ongelmista on työkalun kuluminen. Tämä työ keskittyy toteuttamaan automaattisen järjestelmän kulumisen, erityisesti viistekulumisen, mittaukseen konenäön avulla. Kulumisen mittausjärjestelmä poistaa manuaalisen mittauksen tarpeen ja minimoi ajan, joka käytetään työkalun kulumisen mittaukseen. Mittauksen lisäksi tutkitaan kulumisen mallinnusta sekä ennustamista. Automaattinen mittausjärjestelmä sijoitettiin sorvin sisälle ja järjestelmä integroitiin onnistuneesti ulkopuolisten järjestelmien kanssa. Tehdyt kokeet osoittivat, että mittausjärjestelmä kykenee mittaamaan työkalun kulumisen järjestelmän oikeassa ympäristössä. Mittausjärjestelmä pystyy myös kestämään häiriöitä, jotka ovat konenäköjärjestelmille yleisiä. Työkalun kulumista mallinnusta tutkittiin useilla eri menetelmillä. Näihin kuuluivat muiden muassa neuroverkot ja tukivektoriregressio. Kokeet osoittivat, että tutkitut mallit pystyivät ennustamaan työkalun kulumisasteen käytetyn ajan perusteella. Parhaan tuloksen antoivat neuroverkot Bayesiläisellä regularisoinnilla.

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The main goal of this work is to study the influence of cutting conditions - cutting speed, feed velocity and feed per tooth - on tool life and surface finish of the workpiece in the face milling of flat surfaces. Aiming to achieve this goal, several milling experiments were carried out with different cutting speeds, feed velocities and feeds per tooth. In the first phase of the experiments, cutting speed was varied without varying feed velocity, which caused a variation in feed per tooth. In the second phase of the experiments, cutting speed and feed velocity were varied in such a way that feed per tooth was kept constant. Tool flank wear and surface roughness of the workpiece were measured as cutting time elapsed. The main conclusions of this work are that a) cutting speed has a strong influence on tool life, regardless of whether feed velocity or feed per tooth varies and b) an increase in surface roughness of the workpiece is not closely related to an increase in wear of the primary cutting edge.

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Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq)

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This research addresses the application of friction stir welding (FWS) of titanium alloy Ti–6Al–4V. Friction stir welding is a recent process, developed in the 1990s for aluminum joining; this joining process is being increasingly applied in many industries from basic materials, such as steel alloys, to high performance alloys, such as titanium. It is a process in great development and has its economic advantages when compared to conventional welding. For high performance alloys such as titanium, a major problem to overcome is the construction of tools that can withstand the extreme process environment. In the literature, the possibilities approached are only few tungsten alloys. Early experiments with tools made of cemented carbide (WC) showed optimistic results consistent with the literature. It was initially thought that WC tools may be an option to the FSW process since it is possible to improve the wear resistance of the tool. The metallographic analysis of the welds did not show primary defects of voids (tunneling) or similar internal defects due to processing, only defects related to tool wear which can cause loss of weld quality. The severe tool wear caused loss of surface quality and inclusions of fragments inside the joining, which should be corrected or mitigated by means of coating techniques on tool, or the replacement of cemented carbide with tungsten alloys, as found in the literature.

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There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

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Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

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This work is undertaken in the attempt to understand the processes at work at the cutting edge of the twist drill. Extensive drill life testing performed by the University has reinforced a survey of previously published information. This work demonstrated that there are two specific aspects of drilling which have not previously been explained comprehensively. The first concerns the interrelating of process data between differing drilling situations, There is no method currently available which allows the cutting geometry of drilling to be defined numerically so that such comparisons, where made, are purely subjective. Section one examines this problem by taking as an example a 4.5mm drill suitable for use with aluminium. This drill is examined using a prototype solid modelling program to explore how the required numerical information may be generated. The second aspect is the analysis of drill stiffness. What aspects of drill stiffness provide the very great difference in performance between short flute length, medium flute length and long flute length drills? These differences exist between drills of identical point geometry and the practical superiority of short drills has been known to shop floor drilling operatives since drilling was first introduced. This problem has been dismissed repeatedly as over complicated but section two provides a first approximation and shows that at least for smaller drills of 4. 5mm the effects are highly significant. Once the cutting action of the twist drill is defined geometrically there is a huge body of machinability data that becomes applicable to the drilling process. Work remains to interpret the very high inclination angles of the drill cutting process in terms of cutting forces and tool wear but aspects of drill design may already be looked at in new ways with the prospect of a more analytical approach rather than the present mix of experience and trial and error. Other problems are specific to the twist drill, such as the behaviour of the chips in the flute. It is now possible to predict the initial direction of chip flow leaving the drill cutting edge. For the future the parameters of further chip behaviour may also be explored within this geometric model.

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Developing a means of predicting tool life has been and continues to be a focus of much research effort. A common experience in attempting to replicate such efforts is an inability to achieve the levels of agreement between theory and practice of the original researcher or to extrapolate the work to different materials or cutting conditions to those originally used. This thesis sets out to examine why most equations or models when replicated do not give good agreements. One reason which was found is that researchers in wear prediction, their predictions are limited because they generally fail to properly identify the nature of wear mechanisms operative in their study. Also they fail to identify or recognise factors having a significant influence on wear such as bar diameter. Also in this research the similarities and differences between the two processes of single point turning and drilling are examined through a series of tests. A literature survey was undertaken in wear and wear prediction. As a result it was found that there was a paucity in information and research in the work of drilling as compared to the turning operation. This was extended to the lack of standards that exist for the drilling operation. One reason for this scarcity in information on drilling is due to the complexity of the drilling and the tool geometry of the drill. In the comparative drilling and turning tests performed in this work, the same tool material; HSS, and similar work material was used in order to eliminate the differences which may occur due to this factor. Results of the tests were evaluated and compared for the two operations and SEM photographs were taken for the chips produced. Specific test results were obtained for the cutting temperatures and forces of the tool. It was found that cutting temperature is influenced by various factors like tool geometry and cutting speed, and the temperature itself influenced the tool wear and wear mechanisms that act on the tool. It was found and proven that bar diameter influences the temperature, a factor not considered previously.

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Surface finish is one of the most relevant aspects of machining operations, since it is one of the principle methods to assess quality. Also, surface finish influences mechanical properties such as fatigue behavior, wear, corrosion, etc. The feed, the cutting speed, the cutting tool material, the workpiece material and the cutting tool wear are some of the most important factors that affects the surface roughness of the machined surface. Due to the importance of the martensitic 416 stainless steel in the petroleum industry, especially in valve parts and pump shafts, this material was selected to study the influence of the feed per tooth and cutting speed on tool wear and surface integrity. Also the influence of tool wear on surface roughness is analyzed. Results showed that high values of roughness are obtained when using low cutting speed and feed per tooth and by using these conditions tool wear decreases prolonging tool life. Copyright © 2009 by ASME.

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During a machining process, cutting parameters must be taken into account, since depending on them the cutting edge starts to wear out to the point that tool can fail and needs to be change, which increases the cost and time of production. Since wear is a negative phenomenon on the cutting tool, due to the fact that tool life is reduced, it is important to optimize the cutting variables to be used during the machining process, in order to increase tool life. This research is focused on the influence of cutting parameters such as cutting speed, feed per tooth and axial depth of cut on tool wear during a face milling operation. The Taguchi method is applied in this study, since it uses a special design of orthogonal array to study the entire parameters space, with only few numbers of experiments. Also a relationship between tool wear and the cutting parameters is presented. For the studies, a martensitic 416 stainless steel was selected, due to the importance of this material in the machining of valve parts and pump shafts. Copyright © 2009 by ASME.

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This licentiate thesis has the main focus on evaluation of the wear of coated and uncoated polycrystalline cubic boron nitride cutting tool used in cutting operations against hardened steel. And to exam the surface finish and integrity of the work material used. Harder work material, higher cutting speed and cost reductions result in the development of harder and more wear resistance cutting tools. Although PCBN cutting tools have been used in over 30 years, little work have been done on PVD coated PCBN cutting tools. Therefore hard turning and hard milling experiments with PVD coated and uncoated cutting tools have been performed and evaluated. The coatings used in the present study are TiSiN and TiAlN. The wear scar and surface integrity have been examined with help of several different characterization techniques, for example scanning electron microscopy and Auger electron spectroscopy.   The results showed that the PCBN cutting tools used displayed crater wear, flank wear and edge micro chipping. While the influence of the coating on the crater and flank wear was very small and the coating showed a high tendency to spalling. Scratch testing of coated PCBN showed that, the TiAlN coating resulted in major adhesive fractures. This displays the importance of understanding the effect of different types of lapping/grinding processes in the pre-treatment of hard and super hard substrate materials and the amount and type of damage that they can create. For the cutting tools used in turning, patches of a adhered layer, mainly consisting of FexOy were shown at both the crater and flank. And for the cutting tools used in milling a tribofilm consisting of SixOy covered the crater. A combination of tribochemical reactions, adhesive wear and mild abrasive wear is believed to control the flank and crater wear of the PCBN cutting tools. On a microscopic scale the difference phases of the PCBN cutting tool used in turning showed different wear characteristics. The machined surface of the work material showed a smooth surface with a Ra-value in the range of 100-200 nm for the turned surface and 100-150 nm for the milled surface. With increasing crater and flank wear in combination with edge chipping the machined surface becomes rougher and showed a higher Ra-value. For the cutting tools used in milling the tendency to micro edge chipping was significant higher when milling the tools steels showing a higher hard phase content and a lower heat conductivity resulting in higher mechanical and thermal stresses at the cutting edge.

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The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. ^ The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc. ^

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The applications of micro-end-milling operations have increased recently. A Micro-End-Milling Operation Guide and Research Tool (MOGART) package has been developed for the study and monitoring of micro-end-milling operations. It includes an analytical cutting force model, neural network based data mapping and forecasting processes, and genetic algorithms based optimization routines. MOGART uses neural networks to estimate tool machinability and forecast tool wear from the experimental cutting force data, and genetic algorithms with the analytical model to monitor tool wear, breakage, run-out, cutting conditions from the cutting force profiles. The performance of MOGART has been tested on the experimental data of over 800 experimental cases and very good agreement has been observed between the theoretical and experimental results. The MOGART package has been applied to the micro-end-milling operation study of Engineering Prototype Center of Radio Technology Division of Motorola Inc.

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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.