967 resultados para Tool life


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The use of hybrid materials including carbon fiber reinforced plastics (CFRPs) and lightweight metals such as titanium are increasing particularly in aerospace applications. Multi-material stacks require a number of holes for the assembly purposes. In this research, drilling trials have been carried out in CFRP, Ti-6Al-4V and CFRP/Ti-6Al-4V stack workpieces using AlTiN coated tungsten carbide drill bit. The effects of process parameters have been investigated. The thrust force, torque, burr formation, delamination, surface roughness and tool wear have been analyzed at various processing condition. The experimental results have shown that the thrust force, torque, burr formation and the average surface roughness increase with the increased feed rate and decrease with the increased cutting speed in drilling of Ti-6Al-4V. In drilling CFRP, delamination and the average surface roughness has similar tendency with the cutting parameters however thrust force and torque rises with the increased cutting speed. The results showed that after making 15 holes in CFRP/Ti-6Al-4V stack, measured thrust forces were increased by 20% in CFRP and by 45% in Ti-6Al-4V. Delamination was found to be much smaller in drilling of CFRP in stack from compared to drilling single CFRP. Tool life was significantly shortened in drilling of stack due to the combination of the wear mechanisms.

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With a significant growth in the use of titanium alloys in the aviation manufacturing industry, the key challenge of making high-quality holes in the aircraft assembly process needs to be addressed. In this work, case studies deploying traditional drilling and helical milling technologies are carried out to investigate the tool life and hole surface integrity for hole-making of titanium alloy. Results show that the helical milling process leads to much longer tool life, generally lower hole surface roughness, and higher hole subsurface microhardness. In addition, no plastically deformed layer or white layer has been observed in holes produced by helical milling. In contrast, a slightly softened region was always present on the drilled surface. The residual stress distributions within the hole surface, including compressive and tensile residual stress, have also been investigated in detail.

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DUE TO COPYRIGHT RESTRICTIONS, ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

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The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

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Cold bulk metal forming has made large-scale production of small complex solid parts economically feasible. Tooling used in metal forming poses many uncertainties in the preliminary cost estimation and production process and continual tool replacement and maintenance dramatically reduces productivity and raises manufacturing cost. In order to tackle this, an on-line tool condition monitoring system using artificial neural network (ANN) to integrate information from multiple sensors for forging process has been developed. Together with the force, acoustic emission signals and process conditions, information developed from theoretical models is integrated into the ANN tool monitoring system to predict tool life and provide the maintenance schedule.


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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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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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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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Tool life is an important factor to be considered during the optimisation of a machining process since cutting parameters can be adjusted to optimise tool changing, reducing cost and time of production. Also the performance of a tool is directly linked to the generated surface roughness and this is important in cases where there are strict surface quality requirements. The prediction of tool life and the resulting surface roughness in milling operations has attracted considerable research efforts. The research reported herein is focused on defining the influence of milling cutting parameters such as cutting speed, feed rate and axial depth of cut, on three major tool performance parameters namely, tool life, material removal and surface roughness. The research is seeking to define methods that will allow the selection of optimal parameters for best tool performance when face milling 416 stainless steel bars. For this study the Taguchi method was applied in a special design of an orthogonal array that allows studying the entire parameter space with only a number of experiments representing savings in cost and time of experiments. The findings were that the cutting speed has the most influence on tool life and surface roughness and very limited influence on material removal. By last tool life can be judged either from tool life or volume of material removal.

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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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In the past, many papers have been presented which show that the coating of cutting tools often yields decreased wear rates and reduced coefficients of friction. Although different theories are proposed, covering areas such as hardness theory, diffusion barrier theory, thermal barrier theory, and reduced friction theory, most have not dealt with the question of how and why the coating of tool substrates with hard materials such as Titanium Nitride (TiN), Titanium Carbide (TiC) and Aluminium Oxide (Al203) transforms the performance and life of cutting tools. This project discusses the complex interrelationship that encompasses the thermal barrier function and the relatively low sliding friction coefficient of TiN on an undulating tool surface, and presents the result of an investigation into the cutting characteristics and performance of EDMed surface-modified carbide cutting tool inserts. The tool inserts were coated with TiN by the physical vapour deposition (PVD) method. PVD coating is also known as Ion-plating which is the general term of the coating method in which the film is created by attracting ionized metal vapour in this the metal was Titanium and ionized gas onto negatively biased substrate surface. Coating by PVD was chosen because it is done at a temperature of not more than 5000C whereas chemical Vapour Deposition CVD process is done at very high temperature of about 8500C and in two stages of heating up the substrates. The high temperatures involved in CVD affects the strength of the (tool) substrates. In this study, comparative cutting tests using TiN-coated control specimens with no EDM surface structures and TiN-coated EDMed tools with a crater-like surface topography were carried out on mild steel grade EN-3. Various cutting speeds were investigated, up to an increase of 40% of the tool manufacturer’s recommended speed. Fifteen minutes of cutting were carried out for each insert at the speeds investigated. Conventional tool inserts normally have a tool life of approximately 15 minutes of cutting. After every five cuts (passes) microscopic pictures of the tool wear profiles were taken, in order to monitor the progressive wear on the rake face and on the flank of the insert. The power load was monitored for each cut taken using an on-board meter on the CNC machine to establish the amount of power needed for each stage of operation. The spindle drive for the machine is an 11 KW/hr motor. Results obtained confirmed the advantages of cutting at all speeds investigated using EDMed coated inserts, in terms of reduced tool wear and low power loads. Moreover, the surface finish on the workpiece was consistently better for the EDMed inserts. The thesis discusses the relevance of the finite element method in the analysis of metal cutting processes, so that metal machinists can design, manufacture and deliver goods (tools) to the market quickly and on time without going through the hassle of trial and error approach for new products. Improvements in manufacturing technologies require better knowledge of modelling metal cutting processes. Technically the use of computational models has a great value in reducing or even eliminating the number of experiments traditionally used for tool design, process selection, machinability evaluation, and chip breakage investigations. In this work, much interest in theoretical and experimental investigations of metal machining were given special attention. Finite element analysis (FEA) was given priority in this study to predict tool wear and coating deformations during machining. Particular attention was devoted to the complicated mechanisms usually associated with metal cutting, such as interfacial friction; heat generated due to friction and severe strain in the cutting region, and high strain rates. It is therefore concluded that Roughened contact surface comprising of peaks and valleys coated with hard materials (TiN) provide wear-resisting properties as the coatings get entrapped in the valleys and help reduce friction at chip-tool interface. The contributions to knowledge: a. Relates to a wear-resisting surface structure for application in contact surfaces and structures in metal cutting and forming tools with ability to give wear-resisting surface profile. b. Provide technique for designing tool with roughened surface comprising of peaks and valleys covered in conformal coating with a material such as TiN, TiC etc which is wear-resisting structure with surface roughness profile compose of valleys which entrap residual coating material during wear thereby enabling the entrapped coating material to give improved wear resistance. c. Provide knowledge for increased tool life through wear resistance, hardness and chemical stability at high temperatures because of reduced friction at the tool-chip and work-tool interfaces due to tool coating, which leads to reduced heat generation at the cutting zones. d. Establishes that Undulating surface topographies on cutting tips tend to hold coating materials longer in the valleys, thus giving enhanced protection to the tool and the tool can cut faster by 40% and last 60% longer than conventional tools on the markets today.

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This study examines the effect of sliding speed and surface temperature on the wear behavior of an unlubricated mild steel-tool steel contact pair using the pin-on-disc test. The operating conditions and contact pair are of interest to the automotive sheet metal stamping industry and the broader metal forming community, where high contact pressures and moderate forming speeds can result in significant frictional heating and thus affect tool life. It will be shown that, while adhesive wear is dominant at the tool steel surface for all sliding speeds examined, the adhesive wear rate is very sensitive to sliding speed during slow speed conditions but relatively insensitive to sliding speed during higher speed conditions. These higher sliding speeds result in high frictional heating, however, the effect of increasing bulk temperature results in a transition from adhesive wear to material removal-dominated mechanisms. It is concluded that there is a distinct difference in the wear response for comparable surface temperature and bulk temperature conditions, at the low to moderate sliding speeds and temperatures examined in this study. The SEM and profilometry analysis show that the technique of increasing sliding speed to replicate bulk temperature conditions (or vice versa), may not result in equivalent wear rates and mechanisms.