Microstructural, Mechanical and Tribological Characterisation of CVD and PVD Coatings for Metal Cutting Applications

The present thesis focuses on characterisation of microstructure and the resulting mechanical and tribological properties of CVD and PVD coatings used in metal cutting applications. These thin and hard coatings are designed to improve the tribological performance of cutting tools which in metal cutting operations may result in improved cutting performance, lower energy consumption, lower production costs and lower impact on the environment.  In order to increase the understanding of the tribological behaviour of the coating systems a number of friction and wear tests have been performed and evaluated by post-test microscopy and surface analysis. Much of the work has focused on coating cohesive and adhesive strength, surface fatigue resistance, abrasive wear resistance and friction and wear behaviour under sliding contact and metal cutting conditions. The results show that the CVD deposition of accurate crystallographic phases, e.g. α-Al2O3 rather than κ-Al2O3, textures and multilayer structures can increase the wear resistance of Al2O3. However, the characteristics of the interfaces, e.g. topography as well as interfacial porosity, have a strong impact on coating adhesion and consequently on the resulting properties.  Through the deposition of well designed bonding and template layer structures the above problems may be eliminated. Also, the presence of macro-particles in PVD coatings may have a significant impact on the interfacial adhesive strength, increasing the tendency to coating spalling and lowering the surface fatigue resistance, as well as increasing the friction in sliding contacts. Finally, the CVD-Al2O3 coating topography influences the contact conditions in sliding as well as in metal cutting. In summary, the work illuminates the importance of understanding the relationships between deposition process parameters, composition and microstructure, resulting properties and tribological performance of CVD and PVD coatings and how this knowledge can be used to develop the coating materials of tomorrow.

Study of cutting forces on machinability properties of gray cast iron using new ceramics cutting tools

During gray cast iron cutting, the great rate of mechanical energy from cutting forces is converted into heat. Considerable heat is generated, principally in three areas: the shear zone, rake face and at the clearance side of the cutting edge. Excessive heat will cause undesirable high temperature in the tool which leads to softening of the tool and its accelerated wear and breakage. Nowadays the advanced ceramics are widely used in cutting tools. In this paper a composition special of Si3N4 was sintering, characterized, cut and ground to make SNGN120408 and applyed in machining gray cast iron with hardness equal 205 HB in dry cutting conditions by using digital controlled computer lathe. The tool performance was analysed in function of cutting forces, flank wear, temperature and roughness. Therefore metal removing process is carried out for three different cutting speeds (300 m/min, 600 m/min, and 800 m/min), while a cutting depth of 1 mm and a feed rate of 0.33 mm/rev are kept constant. As a result of the experiments, the lowest main cutting force, which depends on cutting speed, is obtained as 264 N at 600 m/min while the highest main cutting force is recorded as 294 N at 300 m/min.

Cutting performance of diamond coated Si3N4 tool during turning

Silicon nitride cutting tools have been used successfully for machining hard materials, like: cast irons, nickel based alloys, etc. However these cutting tools with diamond coating present little information on dry turning operations of gray cast iron. In the present work, Si3N4 square inserts was developed, characterized and subsequently coated with diamond for dry machining operations on gray cast iron. All experiments were conducted with replica. It was used a 1500, 3000, 4500 m cutting length, feed rate of 0.33 mm/rev and keeping the depth of cut constant and equal to 1 mm. The results show that wear in the tool tips of the Si3N4 inserts, in all cutting conditions, was caused by both mechanical and chemical processes. To understand the tool wear mechanisms, a morphological analysis of the inserts, after experiments, has been performed by SEM and optical microscopy. Diamond coated PVD inserts showed to be capable to reach large cutting lengths when machining gray cast iron. © (2010) Trans Tech Publications.

The cutting performance of sialon ceramic tools

The thesis deals with a research programme in which the cutting performance of a new generation of ceramic cutting tool material is evaluated using the turning process. In part one, the performance of commercial Kyon 2000 sialon ceramic inserts is studied when machining a hardened alloy steel under a wide range of cutting conditions. The aim is to formulate a pattern of machining behaviour in which tool wear is related to a theoretical interpretation of the temperatures and stresses generated by the chip-tool interaction. The work involves a correlation of wear measurement and metallographic examination of the wear area with the measurable cutting data. Four main tool failure modes are recognised: (a) flank and crater wear (b) grooving wear (c) deformation wear and (d) brittle failure Results indicate catastrophic edge breakdown under certain conditions. Accordingly in part two, the edge geometry is modified to give a double rake tool; a negative/positive combination. The results are reported for a range of workpiece materials under orthogonal cutting conditions. Significant improvements in the cutting performance are achieved. The improvements are explained by a study of process parameters; cutting forces, chip thickness ratio, chip contact length, temperature distribution, stress distribution and chip formation. In part three, improvements in tool performance are shown to arise when the edge chamfer on a single rake tool is modified. Under optimum edge chamfer conditions a substantial increase in tool life is obtained compared with the commercial cutting geometry.

Modelling the dynamics of cutting during turning

This thesis presents an approach to cutting dynamics during turning based upon the mechanism of deformation of work material around the tool nose known as "ploughing". Starting from the shearing process in the cutting zone and accounting for "ploughing", new mathematical models relating turning force components to cutting conditions, tool geometry and tool vibration are developed. These models are developed separately for steady state and for oscillatory turning with new and worn tools. Experimental results are used to determine mathematical functions expressing the parameters introduced by the steady state model in the case of a new tool. The form of these functions are of general validity though their coefficients are dependent on work and tool materials. Good agreement is achieved between experimental and predicted forces. The model is extended on one hand to include different work material by introducing a hardness factor. The model provides good predictions when predicted forces are compared to present and published experimental results. On the other hand, the extension of the ploughing model to taming with a worn edge showed the ability of the model in predicting machining forces during steady state turning with the worn flank of the tool. In the development of the dynamic models, the dynamic turning force equations define the cutting process as being a system for which vibration of the tool tip in the feed direction is the input and measured forces are the output The model takes into account the shear plane oscillation and the cutting configuration variation in response to tool motion. Theoretical expressions of the turning forces are obtained for new and worn cutting edges. The dynamic analysis revealed the interaction between the cutting mechanism and the machine tool structure. The effect of the machine tool and tool post is accounted for by using experimental data of the transfer function of the tool post system. Steady state coefficients are corrected to include the changes in the cutting configuration with tool vibration and are used in the dynamic model. A series of oscillatory cutting tests at various conditions and various tool flank wear levels are carried out and experimental results are compared with model—predicted forces. Good agreement between predictions and experiments were achieved over a wide range of cutting conditions. This research bridges the gap between the analysis of vibration and turning forces in turning. It offers an explicit expression of the dynamic turning force generated during machining and highlights the relationships between tool wear, tool vibration and turning force. Spectral analysis of tool acceleration and turning force components led to define an "Inertance Power Ratio" as a flank wear monitoring factor. A formulation of an on—line flank wear monitoring methodology is presented and shows how the results of the present model can be applied to practical in—process tool wear monitoring in • turning operations.

Tool cutting force modeling and wear estimation of micro -end-milling operations

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. ^

Tool cutting force modeling and wear estimation of micro-end-milling operations

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.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

Analysis and Optimization of Machining Process Using Evolutionary Algorithms

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.

Design of a biomimetic skin for an octopus-inspired robot– Part I: characterising octopus skin

Octopus skin samples were tested under quasi-static and scissor cutting conditions to measure the in-plane material properties and fracture toughness. Samples from all eight arms of one octopus were tested statically to investigate how properties vary from arm to arm. Another nine octopus skins were measured to study the influence of body mass on skin properties. Influence of specimen location on skin mechanical properties was also studied. Material properties of skin, i.e. the Young's modulus, ultimate stress, failure strain and fracture toughness have been plotted against the position of skin along the length of arm or body. Statistical studies were carried out to help analyzing experimental data obtained. Results of this work will be used as guidelines for the design and development of artificial skins for an octopus-inspired robot.

Effect of provenance, plant part and processing on extract profiles from cultivated European Rhodiola rosea L. for medicinal use.

The demand for plant material of Rhodiola rosea L. (Crassulaceae) for medicinal use has increased recently, amid concerns about its quality and sustainability. We have analysed the content of phenylpropanoids (total rosavins) and salidroside in liquid extracts from 3-year old cultivated plants of European origin, and mapped the influence of plant part (rhizome versus root), genotype, drying, cutting, and extraction solvent to chemical composition. Rhizomes contained 1.5-4 times more salidroside (0.3-0.4% dry wt) and total rosavins (1.2-3.0%) than roots. The qualitative decisive phenylpropanoid content in the extracts was most influenced by plant part, solvent, and genotype, while drying temperature and cutting conditions were of less importance. We have shown that R. rosea from different boreal European provenances can be grown under temperate conditions and identified factors to obtain consistent high quality extracts provided that authentic germplasm is used and distinguished between rhizome, roots and their mixtures.

Surface amorphization in diamond turning of silicon crystal investigated by transmission electron microscopy

Silicon crystal exhibits a ductile regime during machining prior to the onset of fracture when appropriate cutting conditions are applied. The present study shows that the ductile regime is a result of a phase transformation which is indirectly evidenced by the amorphous phase detected in the machined surface. Transmission electron microscopy (TEM) planar view studies were successfully performed on monocrystalline silicon (1 0 0) single point diamond turned. TEM electron diffraction patterns show that the machined surface presents diffuse rings along with traces of crystalline material. This is attributed to crystalline silicon immersed in an amorphous matrix. Furthermore, only diffuse rings in the diffraction patterns of the ductile chip are detected, indicating that it is totally amorphous. © 2000 Elsevier Science B.V. All rights reserved.

Estudo comparativo do desempenho de rebolos com grãos superabrasivos e convencionais

Grinding is a precision machining process which is widely used in the manufacture of components requiring fine tolerances and smooth surfaces. There are several imput parameters (cutting conditions, cutting fluid and grinding wheel type used, dressing conditions etc.) which can affect the process variables (tangential and normal cutting forces, roughness, grinding temperatures, G ratio, etc.) leading to differences in the roughness, in the surface integrity and in the mechanical strength of the ground component. Consequently, the imput parameters must be controlled in order to insure the workpiece final quality. This paper presents a comparative evaluation of the performance of two types of grinding wheels [a conventional (Al2O3) and a superabrasive (CBN)] when grinding a VC131 steel, by the analysis of specific process variables when varying the cutting conditions. Highest values of G ratio and lowest workpiece roughness was observed when using CBN grinding wheels. This confirms the global trend of replacement of alumina grinding wheels by CBN, when grinding DTG (difficult to grind) materials.

Estudo da geometria do cavaco no corte com discos abrasivos

This paper shows a research about the study of the chip's geometry generated in the diving cut-off operation, under several cutting conditions. As a result it was possible to verify tint the cutting conditions and the type of the material being cut can directly affect the chip's geometry.

Transverse cylindrical grinding of a eutectic alloy

We report herein on a comparison of the performance of two different grinding wheels (conventional and CBN) in the transverse cylindrical grinding of a eutectic alloy. Three cutting conditions were tested: rough, semi-finishing and finishing. The parameters of evaluation were the cutting force, roughness and wheel wear. The optimal cutting force and roughness values were obtained when grinding with the conventional wheel, due to the superior dressing operation performed under every cutting condition tested. Although the CBN wheel presented the best G ratio values, they were lower than expected owing to the inappropriate dressing operation applied. Excessive wheel corner wear was detected in both wheels, caused by the grinding kinematics (transverse grinding) employed. In terms of cutting force and roughness, the conventional wheel proved to be the better choice under the conditions tested. However, in terms of the G ratio, a cost analysis is crucial to determine whether the differences between the wheels justify the use of the CBN wheel, in which case the dressing operation requires improvement.