Multi-scale simulation of the nano-metric cutting process

Molecular dynamics (MD) simulation and the finite element (FE) method are two popular numerical techniques for the simulation of machining processes. The two methods have their own strengths and limitations. MD simulation can cover the phenomena occurring at nano-metric scale but is limited by the computational cost and capacity, whilst the FE method is suitable for modelling meso- to macro-scale machining and for simulating macro-parameters, such as the temperature in a cutting zone, the stress/strain distribution and cutting forces, etc. With the successful application of multi-scale simulations in many research fields, the application of simulation to the machining processes is emerging, particularly in relation to machined surface generation and integrity formation, i.e. the machined surface roughness, residual stress, micro-hardness, microstructure and fatigue. Based on the quasi-continuum (QC) method, the multi-scale simulation of nano-metric cutting has been proposed. Cutting simulations are performed on single-crystal aluminium to investigate the chip formation, generation and propagation of the material dislocation during the cutting process. In addition, the effect of the tool rake angle on the cutting force and internal stress under the workpiece surface is investigated: The cutting force and internal stress in the workpiece material decrease with the increase of the rake angle. Finally, to ease multi-scale modelling and its simulation steps and to increase their speed, a computationally efficient MATLAB-based programme has been developed, which facilitates the geometrical modelling of cutting, the simulation conditions, the implementation of simulation and the analysis of results within a unified integrated virtual-simulation environment

A Study of Tool Wear Using Statistical Analysis of Metal Cutting Acoustic Emission

levels predicted by the theoretical relation, we have extracted data from [10] sufficient to compute the AE generated in the primary deformation zone per the first term of (1). For this purpose, Zorev's data for machining plain medium-carbon steel (40 steel) with nominal rake of ten degrees was used. For given speed and feed, cutting ratio r c and average actual rake angle a a were scaled from the experimental curves and used to compute shear angle as cos a a 4> = arctan : (2) r c -sin a a Then a measure of the predicted acoustic emission in the primary zone was computed as [ cos en. ~1 ^ M>l'l-^-7 TT A 0) sm<£ cos(0 -a a ) J where K= C 4 T k ln has been taken as constant. Referring again to the data in Summary While it is difficult, if not impossible, to isolate a single effect in an oblique cutting operation, our experimental results provide strong evidence of a link between presence of a builtup edge and increased acoustic emission activity. We have hypothesized that the primary reason for this link is the increase in effective rake angle associated with the existence of a BUE. Calculated results using published experimental data in an existing theoretical relation appear to support the hypothesis. While the theoretical equation was developed for orthogonal Cutting, it is nevertheless reasonable to apply it here to qualitatively examine our explanation of the experimental results. Finally, we note that our use of equation (3) ignores acoustic emission in the secondary and tertiary zones. The existence of a BUE would generally increase AE energy from these sources, so their inclusion should further support the experimental evidence presented here. Further investigations are needed in order to better understand the BUE and acoustic emission relationship. It is planned to explore a wider range of workpiece materials, rake angle variations, and feeds. In future cutting experiments, comprehensive cutting force data will be obtained for correlation with AE measurements and BUE observations. Ultimately, it may be necessary to employ a quick-stop mechanism to quantify the built-up edge versus cutting conditions for inclusion in a process model. References 1 Iwata, K., and Moriwaki, T., "An Application of Acoustic Emission Monitoring to In-Process Sensing of Tool Wear," Annals of the CIRP, Vol. 26, No. 1, 1977, pp. 21-26. 2 Dornfeld, D. A., and Kannatey-Asibu, E" "Acoustic Emission During Orthogonal Metal Cutting," International Journal of Mechanical Science, Vol. 22, No. 5, 1980, pp. 285-296. 3 Kannatey-Asibu, E., and Dornfeld, D. A., "Quantitative Relationships for Acoustic Emission from Orthogonal Metal Cutting," ASME JOURNAL OF ENGINEERING FOR INDUSTRY, Vol. 103, 1981, pp. 330-340. 4 Kannatey-Asibu, E., and Dornfeld, D. A., "A Study of Tool Wear Using Statistical Analysis of Metal Cutting Acoustic Emission," Wear, Vol. 76, No. 2, 1982, pp. 247-261. 5 Moriwaki, T., "Detection for Cutting Tool Fracture by Acoustic Emission Measurement," Annals of the CIRP, Vol. 29, No. 1, 1980, pp. 35-40. 6 Diei, E. N., and Dornfeld, D. A., "Acoustic Emission Sensing of Tool Wear in Face Milling," ASME JOURNAL OF ENGINEERING FOR INDUSTRY, Vol. 109, No. 3, 1987, pp. 234-240. 7 Yu, Q., and Hutton, D. V., "Liquid Coupled Acoustic Emission Measurement for Milling Operations," Proceedings of the 16th North American Manufacturing Research Conference, University of Illinois, 1988, pp. 403-407. 8 Shaw, M. C, Cook, N. H., and Smith, P. A., "The Mechanics of Three Dimensional Metal Cutting," Transactions of the ASME, Vol. 74, No. 6, 1952, pp. 1055-1064 Lee, E. H., and Shaffer, B. W" "The Theory of Plasticity Applied to a Problem of Machining," ASME Journal of Applied Mechanics, Vol. 73, 1954, pp. 405-413. 10 Zorev, N. N., Metal Cutting Mechanics, Pergamon Press, 1965, Chap. 4. 11 Shaw, Milton C, Metal Cutting Principles, Clarendon Press, Oxford, 1984. Effects of Geometric and Process Parameters on Introduction Drilling is economically one of the most important manufacturing operations [1], and drill structural properties have a direct bearing on the performance of the drilling process. The vibration signal generated during drilling may be used for drill wear and breakage detection [2][3][4][5]. Drill bit stability becomes important when drilling small holes or drilling at high speeds [6][7][8]. The importance of drill bit vibrations on hole quality has also been emphasized by numerous authors [9][10][11]. Hole quality in turn is important for the performance of the manufactured part. For example, in the aircraft industry, defective fastener holes are known to promote fatigue, and result in catastrophic failure of aircraft wings or other structural elements The early research in drilling concentrated on the investigation of drilling as an orthogonal cutting process Modeling The model and solution method used to obtain the results presented here has been described in detail in a previous paper One part of the computer program calculates drill bit cross sectional properties. First the user inputs the coordinates of certain points obtained from measurements on a drill cross section. For analysis purposes the drill cross section is approximated using 4 curves connecting 5 points along the boundary (see Results and Discussion Drill bit bending frequencies depend upon both process parameters, and geometric parameters. Process parameters considered here are the rotational speed and feedrate. Geometric parameters are the drill length, drill flute helix angle, drill cross sectional area, cross sectional area moments of inertias, and drill point geometry. Considered here are the drill cross sectional geometry, and the drill flute helix angle. For sensitivity studies in terms of these parameters a nominal drill with diameter D -9.525 mm is used at two different lengths, / = 0.1 m and, / = 0.2 m. All finite element solutions are obtained for clamped-pinned boundary conditions. Since rotating shafts with dissimilar moments of inertia have different frequencies for forward and reverse precession Drill Helix Angle. The helix angle, |8 0 , is one of the most important structural properties of drill bits, and its effect on the bending frequencies is shown in Drill Rotational Speed. In Figs. 6 and 7 the effect of spindle speed, a>o, on the bending frequencies of short and long drills is illustrated. As the spindle speed increases both forward and reverse precession frequencies in two orthogonal directions increase. This effect, as shown in where, / is the feedrate, H b the Brinell hardness of the workpiece, w the web thickness, D the drill diameter, and C x and C 2 are constants. For a given drill, thrust force increases with the feedrate. Feedrate affects the depth of cut, and the tool life. Hence, it is typically optimized with respect to tool life. However, for long and thin drills the feedrate is decided solely based on the buckling condition of the drill bit [6][7] Transverse Forces. To test the significance of the transverse cutting force components on drill bit vibrations a simulation is performed. The drill bits considered are subjected to a random transverse cutting force, well within the limits of transverse cutting forces typically measured while drilling. This random force is applied to the drill after lowpass filtering. Summary and Conclusions The predictions of a previously presented and validated [18] model are used to show the importance of various parameters on drill bit performance. In particular the effects of rotational speed, thrust force, helix angle, and cross sectional properties are discussed. The rotational speed has a direct effect on the stability of the drill bits, but this effect is not significant for standard spindle speeds and short drills. However, when slender drills are used higher rotational speeds are shown to cause instability. Thrust force also becomes important for long slender drills. It is shown that for long slender drills of dimensions readily available in the market, low feedrates should be used to prevent buckling. Helix angle affects drill bits by increasing the transverse stability of the drills. Typically an untwisted (/3 0 = 0 rad/m) drill will have a minimum bending stiffness that is half that of a twisted one. It is shown that the contribution of the helix angle to the bending stiffness becomes negligible after approximately 1.5 turns along the length. The effect of cross sectional properties of twist drills on bending frequencies is also investigated. It is found that, while retaining the basic geometry of the drill cross section, not much improvement can be achieved. The model of drill vibrations presented here is potentially useful for studies in drill design, process optimization, and process control. Although the model presented here is rather general, it may be desirable to incorporate some extensions to more complex drill geometries (e.g., multiple flutes). It is also desirable to combine this type of vibration model with a model of the cutting process in drilling (e.g., Acknowledgments The authors would like to thank Dr. James MacBain for his valuable contributions to the development of the model, and to acknowledge the financial support of the Industrial Technology Institute and TRW Inc. References 1 Khang, C. H., "Research Goals in High Speed Drilling," SME Paper No. MR77-384, 1977. 2 Braun, S., Lenz, E., and Wu, C. L., "Signature Analysis Applied to Drilling," ASME Paper No. 81-Det-9, 1981. 3 Yee, W. K., and Bloomquist, D. S., "On Line Method of Determining Tool Wear by Time Domain Analysis," SME Paper No. MR82-901, 1982. 4 Yee, K. W., "On Line Use of Drill-Up for On-Line Determination of Drill Wear," SME Paper, No. MS84-914, 1984. 5 Moore, T., and Reif, Z., "Using Vibration Data to Detect Drill Breakage in High Volume," SME Paper No. MS84-908, 1984. 6 Burnham, M. W., "An Analysis of Drill Deflection for Deep Miniature Holes," ASME Paper No. MR80-956, 1980. 7 Burnham, M. W., "The Mechanics of Drilling Small Holes," 10th North American Manufacturing Research Conference, Ontario, May 1983. 8 Wilson, A. J., "Failure of a Drill Near Critical Speed," ASME Paper No. 84-WA/ DE-22, 1984. 9 Fuji, H., Marui, E., and Satsoki, E., "Whirling Vibration in Drilling, Part 1: Cause of Vibration and Role of Chisel Edge," ASME Journal of Engineering for Industry, Vol. 100, No. 3, August 1986. 10 Fuji, H., Marui, E., and Satoski, E., "Whirling Vibrations in Drilling, Part 2: Influence of Drill Geometry, Particularly of the Drill Flank on the Initiation of Vibration," ASME JOURNAL OF ENGINEERING TOR INDUSTRY, Vol. 100, No. 3, August 1986. 11 Reinhall, P. G., and Storti, D. W., "Modeling and Analysis of the Dynamics of a Drill Penetrating a Thin Plate," ASME Paper No. 86-WA-33, 1986. 12 Rudd, J. L., and Gray, T. D., "Quantification of Fastener-Hole Quality," Journal of Aircraft, Vol. 15, No. 3, March 1978, pp. 143-147. 13 Renshaw, T., Wongwiwat, K., and Sarrantonio, A., "Comparison of Properties of Joints Prepared by Ultrasonic Welding and Other Means,'' Journal of Aircraft, Vol. 20, No. 6, June 1983, pp. 552-556. 14 Magrab, E., and Glisin, D. E., "Buckling Loads and Natural Frequencies of Twist Drills," ASME Paper No. 84-WA/ Prod-12, 1984. 15 Uisoy, A. G., "A Lumped Parameter Model for the Transverse Vibration of Drill Bits," inHardt, D. E., and Book, W. J., eds, Control of Manufacturing Process and Robotic Systems, ASME, 1983, pp. 15-25. 16 Uisoy, A. G., and Tekinalp, O., "Dynamic Modeling of Transverse Drill Bit Vibrations," Annals of the CIRP, Vol. 33, No. 1, 1984, pp. 253-258. 17 MacBain, J. C, Harding, K. G., and Tekinalp, O., "Vibration Modes and Frequencies of Twist Drills Using Laser Holographic Interferometry," Symposium on Sensors and Controls for Manufacturing, ASME Winter Annual Meeting, November 17-22, 1985, Miami Beach, Florida. 18 Tekinalp, O., and Uisoy, A-G., "Modeling and Finite Element Analysis of Drill Bit Vibrations," ASME Journal of Vibration, Acoustics, Stress and Reliability in Design, Vol. Ill, No. 2, April 1989, pp. 148-155. 19 Galloway, D. F., "Some Experiments on the Influence of Various Factors on Drill Performance," ASME Transactions, Vol. 77, July 1957, pp. 191-230. 20 Oxford, C. J., Jr., "On the Drilling of Metals-I Basic Mechanics of the Process," Transactions, Vol. 77, Feb. 1955, pp. 103-114. 21 Shaw, M. C, and Oxford, C. J., Jr., "On the Drilling of Metals^II Torque and Thrust in Drilling," ASME Transactions, Vol. 79, January 1957. 22 Williams, R. A., "A Study of the Drilling Process," ASME Journal of Engineering for Industry, November 1974, pp. 1207-1215 23 Oxford, C. J., "Review of Some Recent Developments in the Design and Application of Twist Drills," Advances in Machine Tool Design and Research, 1967, pp. 845-861. 24 Kaldor, S., and Lenz, E., "Drill Point Geometry and Optimization," ASME Journal of Engineering for Industry, Vol. 105, February 1982, pp. 173-18

Исследовательская деятельность эколого-биологической направленности в НОУ "Эврика" - эффективное средство профессиональной ориентации учащихся

В статье научно-исследовательская деятельность эколого-биологической направленности старшеклассников НОУ "Эврика" г. Нижнего Новгорода рассматривается как одна из значимых инновационных форм профессионального самоопределения. Материалом исследования послужил анализ программ конференции городского научного общества учащихся "Эврика" и судьбы выпускников данного общества. Отмечена тенденция роста популярности эколого-биологических исследований среди старшеклассников г. Нижнего Новгорода и успешное вхождение в профессию выпускников научного общества учащихся.In the article, the research activity of the ecology and biology of senior pupils of the scientific society of the pupils "Eureka" in Nizhny Novgorod is considered as one of the significant innovative forms of professional self-determination. The material of the study was the analysis of the programs of the conference of the city scientific society of the students "Eureka" and the fate of the graduates of this society. The tendency of growth of popularity of ecological and biological researches among senior pupils of Nizhny Novgorod and successful entry into the profession of graduates of the scientific society of students is noted

Investigation of acoustic emission for use as a wheel-to-workpiece proximity sensor in fixed-abrasive grinding

This paper reports on the feasibility of using Acoustic Emission (AE) for sensing the proximity of a grinding wheel to a glass workpiece, both prior to contact and in the early stages of contact. Our measured AE signals indicate that we can track the position of the grinding wheel as it approaches the workpiece through the turbulent coolant layer and than as contact initiates with a workpiece during spherical generation. Our data for the initial contact region is dominated by cyclical bursts of AE that appear to correspond to tool spindle motion errors. Our principal goal is to minimize the time required to {open_quote}find the part{close_quote} without damaging the surface of a brittle workmaterial, i.e. during the transition from a fast approach to the much slower final in-feed required for the grinding operation. Our results also suggest that AE is useful as a gauging signal in determining the position of the grinding wheel with respect to the machine tool

Sensor integration using neural networks for intelligent tool condition monitoring, Trans.

A framework for intelligent sensors in unmanned machining is proposed. In the absence of human operators, the process monitoring function has to be performed with sensors and associated decision-making systems which are able to interpret incoming sensor information and decide on the appropriate control action. In this paper, neural networks are used to integrate information from multiple sensors (acoustic emission and force) in order to recognize the occurrence of tool wear in a turning operation. The superior learning and noise suppression abilities of these networks enable high success rates for recognizing tool wear under a range of machining conditions. The parallel computation ability of these networks offers the potential for constructing intelligent sensor systems that are able to learn, perform sensor fusion, recognize process abnormalities, and initiate control actions in real-time manufacturing environments. Introduction Successful automation of machining operations relies, to a great extent, on the ability to recognize process abnormalities and initiate corrective action. In the absence of human operators, this function has to be performed with sensors and associated decision-making systems which are able to interpret incoming sensor information and decide on the appropriate control action. According to Intelligent sensor systems are expected to replace the knowledge, experience, and sensory and pattern recognition abilities of human operators. Successful implementations of these tasks depend on two factors: first, the quality of information generated by the monitoring sensors and second, the techniques used to process this information in order to make decisions. The first factor relates to the type and number of sensors used, and the signal/noise ratio of the information generated by these sensors. The second factor concerns the learning and decision-making procedures used to analyze this information in the context of the process state. Sensing strategies for unmanned machining should aim at integrating both these factors, thereby allowing for a sensor system design which possesses the ability to successfully mimic the sensory abilities and pattern recognition skills of human operators. Metal cutting operations constitute a large percentage of current manufacturing activity (Barash, 1980). As a result, there is a strong thrust in research directed at automating the process. An important component of this research is aimed at developing reliable sensor technology for detecting factors such as chip form, tool condition, workpiece roughness, machine vibrations and bearing failure. Tool wear monitoring, which is the focus of the current work, is an area of active research, primarily because the condition of the tool exerts a strong influence on the surface finish and dimensional integrity of the workpiece and vibration levels of the machine tool. The development of reliable tool wear monitoring systems is also expected to reduce tool material costs and machine down times associated with tool change operations. Additionally, the availability of such systems is vital for implementing optimal strategies (such as adaptive control with optimization) in unmanned machining operations. Several sensing strategies for tool wear detection have been proposed and evaluated in a number of review articles In this paper, we present a technique for intelligent tool condition monitoring which employs information from multiple sensors. This information is integrated via a neural network, a parallel computing architecture which can learn to recognize patterns of sensor information and associate them with decisions on the tool wear state. Initial efforts by Intelligent Sensor Systems for Tool Wear Monitoring A human operator can detect whether a tool is fresh or worn by observing the machining operation and associating patterns of sensory cues with a decision on the tool state. The sensory information used to make this decision is usually of various types: visual (observation of chip color, presence of smoke, deteriorating surface finish of the workpiece), audio (sound generated by rubbing action of tool flank on workpiece), and olfactory (smell of smoke generated due to machining with a worn tool). Associating the sensory cues with tool wear depends to a great extent on the knowledge and experience of the operator. In many cases, information from a single sensor, say audio, may not be sufficient and visual information may also be necessary. The fact that human operators are very successful at the process monitoring task suggests that one possible method for designing computer-based monitoring systems is to model their learning and decision-making abilities after those of a-htiman operator. The philosophy pursued in this paper is that an "intelligent sensor system" should be able to emulate as closely as possible, the learning) pattern recognition and sensor fusion abilities of human operators. Human pattern recognition is a highly developed and poorly understood characteristic, and the task of simulating it on a computer is a formidable one. The factors involved in human pattern recognition and how they may be mapped in order to develop computer-based pattern recognition capability is shown in Use of Multiple Sensors In the current work, it was decided to use AE and cutting force information in order to develop an intelligent tool condition monitoring system. The primary and secondary shear zones are important sources of AE when cutting with a fresh tool. The root mean square (RMS) level of the AE signal (V RMS ) measures the total power level of the signal and has been found to be sensitive to the degree of flank wear in a turning operation. Experiments conducted by Lan (1983) for machining of SAE 4340 steel with carbide tools indicate that V RMS increases with machining time due to increased flank wear. However, in cases where the crater wear is significant, V RMS tends to decrease or remains constant. Since the presence of flank wear is expected to increase V RMS , Lan concluded that the effect of crater wear is to cause a drop in V RMS . The fact that V RMS remains constant with increased tool wear due to opposing effects of flank and crater wear makes it difficult to 220/Vol. 112, AUGUST 1990 Transactions of the ASME design an AE-based tool wear monitoring system which uses only information on the RMS level of the signal. Emel and Kannatey-Asibu (1988) present experimental data which shows that the power spectrum is sensitive to tool wear and process conditions. Results for machining of AISI 1060 with carbide inserts The performance of an AE-based tool wear monitoring system can be enhanced by complementing the AE information with information from other sensors mounted on the machine tool (for example, force or power sensors). The magnitude of the cutting force is sensitive to the occurrence of tool wear in a turning operation (Andrews and Tlusty, 1983). According to The AE and cutting force information relate to different effects of tool wear. Acoustic emission is sensitive to the microscopic activities (and the resulting stress waves) related to plastic deformation and friction in the cutting zone. The cutting force spectrum is sensitive to the vibrations induced in the tool and workpiece due to the effects of flank wear. The advantage of using AE and cutting force sensors is that they provide information relating to microscopic (stress waves) and macroscopic (vibrations) effects of tool wear. This helps provide better signal features to the pattern classifier, allowing a greater reliability in making decisions on the state of tool wear. Background on Neural Networks The human brain consists of a large number of interconnected neurons, each possessing very simple computational abilities. However, the interactions (through a dense system of connections of "synapses") between the neurons allows for parallel processing of information, which greatly enhances the speed of computation and causes a large amount of knowledge to be brought to bear in processing this information In this paper, a special class of neural networks called feedforward networks is used for tool wear monitoring in a machining operation. A software implementation of this network on a serial computer is used as the learning and decisionmaking component. The structure of this type of a network is shown i

Statistical properties of acoustic emission signals from metal cutting processes

Acoustic Emission (AE) data from single point turning machining are analysed in this paper in order to gain a greater insight of the signal statistical properties for Tool Condition Monitoring (TCM) applications. A statistical analysis of the time series data amplitude and root mean square (RMS) value at various tool wear levels are performed, �nding that ageing features can be revealed in all cases from the observed experimental histograms. In particular, AE data amplitudes are shown to be distributed with a power-law behaviour above a cross-over value. An analytic model for the RMS values probability density function (pdf) is obtained resorting to the Jaynes' maximum entropy principle (MEp); novel technique of constraining the modelling function under few fractional moments, instead of a greater amount of ordinary moments, leads to well-tailored functions for experimental histograms.Comment: 16 pages, 7 figure

The Commonwealth Trans-Antarctic Expedition 1955-58 - How the crossing of Antarctica moved New Zealand to recognise its Antarctic heritage and take an equal place among Antarctic nations

The thesis analyses the expedition (TAE) led by Dr.Vivian Fuchs and Sir Edmund Hillary from three vantage points: 1)the years from 1948 to 1955 leading up to the expedition 2) the interaction between the IGY and the TAE projects and 3) the role of the US Navy as the expedition unfolded. The thesis also investigates key events including the purchase of the ship Endeavour from Britain, the competition for leadership of the UK and NZ parties, the 'dash to the Pole' by Hillary, and the search for base sites and routes to the Polar Plateau. The thesis contains an overview historical introduction, a comprehensive literature review as well as a broad-based set of conclusions