Study of Vibration assisted machining process

Aquest projecte s'ha realitzat amb l'objectiu de dissenyar, produir i caracteritzar una eina de mecanitzat assistida per vibració per a operacions d'acabat en torn. Més concretament, s'ha desenvolupat una sèrie d'experiments per tal de caracteritzar l'eina per a l'acabat de superfícies d'acer C45E. El disseny de l'eina incorpora un sonotrode adherit a la tija de l'eina que la converteix en una eina VAM, el disseny actual desenvolupat per tot l'equip DEFAM està protegit sota la patent ES1253134. Un cop dissenyat, fabricat i adaptat a l'torn CNC, s'han realitzat proves de forma manual per obtenir un bon punt de partida de les condicions de tall a aplicar en el procés de mecanitzat. Amb aquestes condicions, s'ha dut a terme la fase d'experimentació, realitzant provetes per a anàlisi. No només s'ha analitzat la vida a fatiga d'aquestes provetes, sinó que també s'ha mesurat la textura de la superfície, així com la seva duresa. Els resultats obtinguts han estat satisfactoris, complint així les expectatives inicialment plantejades.Este proyecto se ha realizado con el objetivo de diseñar, producir y caracterizar una herramienta de mecanizado asistida por vibración para operaciones de acabado en torno. Más concretamente, se ha desarrollado una serie de experimentos con el fin de caracterizar la herramienta para el acabado de superficies de acero C45E. El diseño de la herramienta incorpora un sonotrodo adherido al vástago de la herramienta que la convierte en una herramienta VAM, el diseño actual desarrollado por todo el equipo DEFAM está bajo el número de patente ES1253134. Una vez diseñado, fabricado y adaptado al torno CNC, se han realizado pruebas de forma manual para obtener un buen punto de partida de las condiciones de corte a aplicar en el proceso de mecanizado. Con estas condiciones, se ha llevado a cabo la fase de experimentación, realizando probetas para análisis. No solo se ha analizado la vida a fatiga de estas probetas, sino que también se ha medido la textura de la superficie, así como su dureza. Los resultados obtenidos han sido satisfactorios, cumpliendo así las expectativas inicialmente planteadas.This project has been carried out with the aim of designing, producing and characterizing a vibration-assisted machining tool for finishing operations on a lathe. More specifically, a series of experiments has been developed in order to characterize the tool for surface finishing of C45E steel. The tool design incorporates a sonotrode attached to the tool shank which converts it in a VAM tool, the current design developed by all the DEFAM team is under patent number ES1253134. Once designed, manufactured and adapted to the CNC lathe, tests have been carried out manually to obtain a good starting point for the cutting conditions to be applied in the machining process. With these conditions, the experimentation phase has been carried out, making test specimens for analysis. Not only the fatigue life has been analyzed from these specimens, but the surface texture has also been measured, as well as its hardness. The results obtained have been satisfactory, thus meeting the expectations initially set

Thermal error compensation of a 5-axis machine tool using indigenous temperature sensors and CNC integrated Python code validated with a machined test piece

Achieving high workpiece accuracy is the long-term goal of machine tool designers. There are many causes for workpiece inaccuracy, with thermal errors being the most common. Indirect compensation (using prediction models for thermal errors) is a promising strategy to reduce thermal errors without increasing machine tool costs. The modelling approach uses transfer functions to deal with this issue; it is an established dynamic method with a physical basis, and its modelling and calculation speed are suitable for real-time applications. This research presents compensation for the main internal and external heat sources affecting the 5-axis machine tool structure including spindle rotation, three linear axes movements, rotary C axis and time-varying environmental temperature influence, save for the cutting process. A mathematical model using transfer functions is implemented directly into the control system of a milling centre to compensate for thermal errors in real time using Python programming language. The inputs of the compensation algorithm are indigenous temperature sensors used primarily for diagnostic purposes in the machine. Therefore, no additional temperature sensors are necessary. This achieved a significant reduction in thermal errors in three machine directions X, Y and Z during verification testing lasting over 60 hours. Moreover, a thermal test piece was machined to verify the industrial applicability of the introduced approach. The results of the transfer function model compared with the machine tool’s multiple linear regression compensation model are discussed

Development of hybrid micro machining approaches and test-bed

High precision miniature and micro products which possess 3D complex structures or free-form surfaces are now being widely used in industry. These micro products require to be fabricated by several machining processes and the integration of these various machining processes onto one machine becomes necessary since this will help reduce realignment errors and also increase the machining efficiency. This thesis describes the development and testing of several hybrid machining approaches for machines which are typically used to produce micro products such as micro fluidic moulds, solar concentrator moulds, micro grooves in brittle materials and micro structured milling cutters. These are: (a) micro milling and laser deburring; (b) micro grinding involving laser pre-heating; (c) micro milling and laser polishing. The hybrid micro milling/ laser deburring process was tested during the fabrication of a micro fluidic injection mould. Micro burrs on the channel of micro fluidic mould generated during micro milling were completely removed by developed laser deburring process. This approach can achieve a good surface finish on a micro fluidic mould. The hybrid laser assisted micro grinding process was investigated by fabricating a set of micro grooves on brittle materials, including Al2O3 and Si3N4. The workpiece was pre-heated by laser to increase its temperature above that of the brittle to ductile transition phase interface. It was found that lower cutting forces were apparent in the grinding process when used to machine brittle materials. It was also found that laser assisted grinding helped achieve a very good surface finish and reduced subsurface damage. The final hybrid machining approach tested involved micro milling and laser polishing to fabricate solar concentrator moulds. Such a mould requires a good surface finish in order to accurately guide light focusing on a target. The laser polishing process was successfully used to remove any unwanted cutting marks generated by a previous micro milling process. Abstract iii As a novel extension to this hybrid machine world, a focussed ion beam (FIB) fabrication approach was researched regarding the generation of microstructures on the rake faces of milling cutters with the aim of reducing cutter cutting forces and increasing tool life. The tool wear resistance performance of these microstructured tools was evaluated through three sets of slot milling trials on a NAK80 specimen with the results indicating that micro structured micro milling cutters of this kind can effectively improve the tool wear resistance performance. A microstructure in a direction perpendicular to the cutting edge was found to be the best structure for deferring tool wear and obtaining prolonged tool life. This approach can potentially be further integrated into a hybrid precision machine such that micro structure cutters can be fabricated in-situ using a laser machining process. The conceptual design of a 5-axis hybrid machine which incorporates micro milling, grinding and laser machining has been proposed as a test-bed for the above hybrid micro machining approach. Through finite element analysis, the best configuration was found to be a closed-loop vertical machine which has one rotary stage on the worktable and another on machining head. In this thesis, the effectiveness of these novel hybrid machining approaches have been fully demonstrated through machining several microproducts. Recommendations for future work are suggested to focus on further scientific understanding of hybrid machining processes, the development of a laser repairing approach and the integration of a controller for the proposed hybrid machine

Development of the UMAC-based control system with application to 5-axis ultraprecision micromilling machines

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Increasing demands from end users in the fields of optics, defence, automotive, medical, aerospace, etc. for high precision 3D miniaturized components and microstructures from a range of materials have driven the development in micro and nano machining and changed the manufacturing realm. Conventional manufacturing processes such as chemical etching and LIGA are found unfavourable or limited due to production time required and have led mechanical micro machining to grow further. Mechanical micro machining is an ideal method to produce high accuracy micro components and micro milling is the most flexible enabling process and is thus able to generate a wider variety of complex micro components and microstructures. Ultraprecision micromilling machine tools are required so as to meet the accuracy, surface finish and geometrical complexity of components and parts. Typical manufacturing requirements are high dimensional accuracy being better than 1 micron, flatness and roundness better than 50 nm and surface finish ranging between 10 and 50 nm. Manufacture of high precision components and parts require very intricate material removal procedure. There are five key components that include machine tools, cutting tools, material properties, operation variables and environmental conditions, which constitute in manufacturing high quality components and parts. End users assess the performance of a machine tool based on the dimensional accuracy and surface quality of machined parts including the machining time. In this thesis, the emphasis is on the design and development of a control system for a 5-axis bench-type ultraprecision micromilling machine- Ultra-Mill. On the one hand, the developed control system is able to offer high motion and positioning accuracy, dynamic stiffness and thermal stability for motion control, which are essential for achieving the machining accuracy and surface finish desired. On the other hand, the control system is able to undertake in-process inspection and condition monitoring of the machine tool and process. The control of multi-axis precision machines with high-speed and high-accuracy motions and positioning are desirable to manufacture components with high accuracy and complex features to increase productivity and maintain machine stability, etc. The development of the control system has focused on fast, accurate and robust positioning requirements at the machine system design stage. Apart from the mechanical design, the performance of the entire precision systems is greatly dependent on diverse electrical and electronics subsystems, controllers, drive instruments, feedback devices, inspection and monitoring system and software. There are some variables that dynamically alter the system behaviour and sensitivity to disturbance that are not ignorable in the micro and nano machining realm. In this research, a structured framework has been developed and integrated to aid the design and development of the control system. The framework includes critically reviewing the state of the art of ultraprecision machining tools, understanding the control system technologies involved, highlighting the advantages and disadvantages of various control system methods for ultraprecision machines, understanding what is required by end-users and formulating what actually makes a machine tool be an ultraprecision machine particularly from the control system perspective. In the design and development stage, the possession of mechatronic know-how is essential as the design and development of the Ultra-Mill is a multidisciplinary field. Simulation and modelling tool such as Matlab/Simulink is used to model the most suitable control system design. The developed control system was validated through machining trials to observe the achievable accuracy, experiments and testing of subsystems individually (slide system, tooling system, monitoring system, etc.). This thesis has successfully demonstrated the design and development of the control system for a 5-axis ultraprecision machine tool- Ultra-Mill, with high performance characteristics, fast, accurate, precise, etc. for motion and positioning, high dynamic stiffness, robustness and thermal stability, whereby was provided and maintained by the control system

An investigation on micro cutting mechanics: Modelling, simulations and experimental case studies

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University London.Micro cutting is becoming increasingly important since miniature and micro components/products have become more and more demanded in precision engineering applications and consumer goods in a daily life. Meanwhile, it has not been thoroughly investigated yet. Scientific understanding of the fundamentals in micro cutting mechanics and physics is vital for micro manufacturing of micro or miniature components and products. Consequently, the scientific investigation on micro cutting mechanics is critically needed, particularly on its key fundamental aspects on which a systematic approach and key enabling technologies are developed for micro manufacturing. Therefore, three key fundamental aspects of micro cutting mechanics have been identified for this PhD project and a comprehensive systematic research has been performed through both theoretical and experiment-based investigations. The three aspects of micro cutting mechanics mainly include dynamic stiffness investigation, innovative micro cutting force modelling, and the study on micro cutting heat, temperature and their partitioned distribution. All experiment-based investigations are undertaken on a diamond turning machine test rig supported with a fast tool servo (FTS) using different reconfigured experimental setups. The finite element (FE)-based analysis is conducted to further support the in-depth analysis on the micro cutting phenomena especially the modelling and simulation of micro cutting force and temperature. Accordingly, both micro cutting force modelling and micro cutting temperature are investigated using modelling and simulation supported by well-designed experimental cutting trials and validations.The investigation on dynamic stiffness in the micro cutting system is focused on its effects on the micro cutting process and its control strategies. The burrs formation and machining accuracy are explored in relation with control of the dynamic stiffness. Furthermore, the control algorithm for dynamic stiffness is developed accordingly in order to minimise burrs formation and stabilize the micro cutting accuracy.The micro cutting force modelling is performed based on specific cutting force, i.e. modelling the cutting force at the unit cutting length or area as coined as the amplitude aspect of the proposed cutting force modelling. The cutting force against a dynamically varied cutting time interval is proposed as the spatial aspect of the cutting force formulation. The amplitude aspect can provide the insight into the micro cutting phenomena particularly in relation with the chip formation and size-effects. The spatial aspect, using a on the wavelet transform (WT) technique and standard deviation analysis can render the dynamic behaviour of the micro cutting force, particularly representing the dynamic effects of the cutting process and its correlation with tool wear.The micro cutting temperature is investigated to formulate the scientific understanding of cutting temperature, heat and their partitioned distribution particularly at the tool-workpiece-chip interface zone in ultraprecision and micro cutting using a diamond cutting tool. The contribution to knowledge at this aspect is to represent the partitioned cutting heat in the micro cutting process and their different behaviours compared to the conventional metal cutting. The scientific approach to modelling micro cutting application (MMCA), i.e. based on modelling-simulation combined with experimental validation, is further evaluated and validated to illustrate the overall benefits of this research investigation through micro cutting of single crystal silicon (for ultraprecision machining of large-sized infrared devices). This approach is established in light of combining all the three aspects of the above investigation on micro cutting mechanics. The research results show the approach can lead to industrial scale advantages for ultraprecision and micro cutting but driven by the scientific understanding of micro manufacturing technology. The systematic investigation on dynamic stiffness control, micro cutting force modelling, micro cutting heat and temperature and their integrated approach can contribute well to the future micro cutting applications

Reducing the uncertainty of thermal model calibration using on-machine probing and data fusion

Various sources of error hinder the possibility of achieving tight accuracy requirements for high-value manufacturing processes. These are often classified as: pseudo-static geometric errors; non-rigid body errors; thermal errors; and dynamic errors. It is comparatively complicated to obtain an accurate error map for the thermal errors because they are influenced by various factors with different materials, time constants, asymmetric heating sources and machining process, environmental effects, etc. Their transient nature and complex interaction mean that they are relatively difficult to compensate using pre-calibration methods. For error correction, the magnitude and sign of the error must first be measured or estimated. Pre-calibrated thermal compensation has been shown to be an effective means of improving accuracy. However, the time required to acquire the calibration data is prohibitive, reducing the uptake of this technology in industrial applications. Furthermore, changing conditions of the machine or factory environment are not adequately accommodated by pre-calibrated compensation, leading to degradation in performance. The supplementary use of on-machine probing, which is often installed for process control, can help to achieve better results. During the probing operation, the probe is carried by the machine tool axes. Therefore, the measurement data that it takes inevitably includes both the probing errors and those originating from the inaccuracies of a machine tool as well as any deviation in the part or artefact being measured. Each of these error sources must be understood and evaluated to be able to establish a measurement with a stated uncertainty. This is a vital preliminary step to ensure that the calibration parameters of the thermal model are not contaminated by other effects. This thesis investigates the various sources of measurement uncertainties for probing on a CNC machine tool and quantify their effects in the particular case where the on-machine probing is used to calibrate the thermal error model. Thermal errors constitute the largest uncertainty source for on-machine probing. The maximum observed thermal displacement error was approximately 220 μm for both X and Z-axis heating test at 100 % speed. To reduce the influence of this uncertainty source, sensor data fusion model using artificial neural network and principal component analysis was developed. The output of this model showed better than 90 % correlation to the measured thermal displacement. This data fusion model was developed for the temperature and FBG sensors. To facilitate the integration of the sensor and to ease the communication with machine tool controller, a modular machine tool structural monitoring system using LabVIEW environment was developed. Finally, to improve the performance of the data fusion model in order to reduce the thermal uncertainty, a novel photo-microsensor based sensing head for displacement measurement is presented and analysed in detail. This prototype sensor has measurement range of 20 μm and resolution of 21 nm

Design and analysis of the internally cooled smart cutting tools with the applications to adaptive machining

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Adaptive machining with internally cooled smart cutting tools is a smart solution for industrial applications, which have stringent manufacturing requirements such as contamination free machining (CFM), high material removal rate, low tool wear and better surface integrity. The absence of cutting fluid in CFM causes the cutting tool and the workpiece subject to great thermal loads owing to higher friction and adhesion, and as a result may increase the levels of tool wear drastically. The increase in cutting temperature may influence the chip morphology which in return producing metal chips in unfavourable ribbon or snarl forms. CFM is difficult to be realized as contaminants can be in various forms in the machining operation and to avoid them totally requires a very tight controlled condition. However, the ecological, economical and technological demands compel the manufacturing practitioners to implement environmentally clean machining process (ECMP). Machining with innovative cooling techniques such as heat pipe, single-phase microduct, cryogenic or minimum quantity lubrication (MQL) has been intensely researched in recent years in order to reduce the cutting temperature in ECMP, thus enabling the part quality, the tool life and the material removal rate achieved in ECMP at least equate or surpass those obtained in conventional machining. On the other hand, the reduction of cutting temperature by using these techniques is often superfluous and is adverse to the produced surface roughness as the work material tends to inherent brittle and hard property at low temperature. Open cooling system means the machining requires a constant cooling supply and it does not provide a solution for process condition feedback as well.This Ph.D. project aims to investigate the design and analysis of internally cooled cutting tools and their implementation and application perspectives for smart adaptive machining in particular. Circulating the water based cooling fluid in a closed loop circuit contributes to sustainable manufacturing. The advantage of reducing cutting temperature from localized heat at the tool tip of an internally cooled cutting tool is enhanced with the smart features of the tool, which is trained by real experimental data, to cognitively vary the coolant flow rate, cutting feed rate or/and cutting speed to control the critical machining temperature as well as optimum machining conditions. Environmental friendly internal micro-cooling can avoid contamination of generated swarf which can also reduce the cutting temperature and thus reduce tool wear, increase machining accuracy and optimize machining economics. Design of the smart cutting tool with internal micro-cooling not only takes into account of the environmental aspects but also justifies with its ability to reduce the machining cost. Reduction of production cost can be achieved with the lower consumption of cooling fluid and improved machining resources/ energy efficiency. The models of structural, heat transfer, computational fluid dynamics (CFD) and tool life provide useful insight of the performance of the internally cooled smart cutting tool. Experimental validation using the smart cutting tool to machine titanium, steel and aluminium, indicates that the application of internally cooled smart cutting tools in adaptive machining can improve machining performance such as cutting temperature, cutting forces and surface quality generated. The useful tool life span is also extended significantly with internally cooled smart cutting tools in comparison to the tool life in conventional machining. The internally cooled smart cutting tool has important implications in the application to ECMP particularly by overcoming the stigma of high uncontrollable cutting temperature with the absence of cooling fluid.Brunel Universit

力制御型スタイラスプローブによる機上形状計測

Tohoku University高偉課

The Application of ANN and ANFIS Prediction Models for Thermal Error Compensation on CNC Machine Tools

Thermal errors can have significant effects on Computer Numerical Control (CNC) machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon the accuracy and robustness of the thermal error model and its input measurements. This thesis first reviews different methods of designing thermal error models, before concentrating on employing Artificial Intelligence (AI) methods to design different thermal prediction models. In this research work the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used as the backbone for thermal error modelling. The choice of inputs to the thermal model is a non-trivial decision which is ultimately a compromise between the ability to obtain data that sufficiently correlates with the thermal distortion and the cost of implementation of the necessary feedback sensors. In this thesis, temperature measurement was supplemented by direct distortion measurement at accessible locations. The location of temperature measurement must also provide a representative measurement of the change in temperature that will affect the machine structure. The number of sensors and their locations are not always intuitive and the time required to identify the optimal locations is often prohibitive, resulting in compromise and poor results. In this thesis, a new intelligent system for reducing thermal errors of machine tools using data obtained from thermography data is introduced. Different groups of key temperature points on a machine can be identified from thermal images using a novel schema based on a Grey system theory and Fuzzy C-Means (FCM) clustering method. This novel method simplifies the modelling process, enhances the accuracy of the system and reduces the overall number of inputs to the model, since otherwise a much larger number of thermal sensors would be required to cover the entire structure. An Adaptive Neuro-Fuzzy Inference System with Fuzzy C-Means clustering (ANFIS-FCM) is then employed to design the thermal prediction model. In order to optimise the approach, a parametric study is carried out by changing the number of inputs and number of Membership Functions (MFs) to the ANFIS-FCM model, and comparing the relative robustness of the designs. The proposed approach has been validated on three different machine tools under different operation conditions. Thus the proposed system has been shown to be robust to different internal heat sources, ambient changes and is easily extensible to other CNC machine tools. Finally, the proposed method is shown to compare favourably against alternative approaches such as an Artificial Neural Network (ANN) model and different Grey models

Development of compliant mechanisms for real-time machine tool accuracy enhancement using dual-servo principle

Ph.DDOCTOR OF PHILOSOPH