2,326 research outputs found
Experimental investigation of effect of tool path strategies and cutting parameters using acoustic signal in complex surface machining
High productive milling of complex sculptured surfaces is extremely important in many different industries. Determination of the appropriate tool path styles and milling parameters is crucial in ensuring precise surface machining, meeting the better surface integrities and lower tool deflection and forces using process monitoring methods. In this study, sound pressure as a monitoring method is presented for analyzing different tool path strategies and cutting parameters to assess their influence on surface errors, tool deflection, cutting forces, sound pressure level and instantaneous material removal rate on rough machining of complex surfaces with ball end mill. Design and analysis of experiments are performed using factorial design technique and variance analysis. Additionally, the significant parameters affecting the experimental results are introduced. B-rep based method with integrated CAM software is developed to calculate the cutter/workpiece engagement, effective cutting diameter and instantaneous material removal rate. Milling strategies employed include contour parallel, zigzag with two cut angle, and spiral. The milling conditions were feed rate and radial depth of cut. The conclusion is that 0° zigzag strategy provokes the lowest cutting forces, tool deflection, surface errors and sound pressure and spiral strategy signifies the worst surface errors and the highest cutting forces. With the increase of feed rate, instantaneous material removal rate increases parallel to rising of machining sound signal, milling forces, tool deflection and machining errors. It is observed that the step over value has less influence on the results. The sound pressure level which has a drastic reference to the material removal rate and removed volume values are detected and experimental results could be figured out with sound pressure
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Vibration assisted machining: Modelling, simulation, optimization, control and applications
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 30/11/2010.Increasing demand for precision components made of hard and brittle materials such as glasses, steel alloys and advanced ceramics, is such that conventional grinding and polishing techniques can no longer meet the requirements of today's precision manufacturing engineering. Particularly, in order to undertake micro-milling of optical glasses or other hard-machining materials, vibration assisted machining techniques have been adopted. However, it is essential and much needed to undertake such processes based on a scientific approach, i.e. the process to be quantitatively controlled and optimized rather than carried out with a trial-and-error manner.
In this research, theoretical modelling and instrumental implementation issues for vibration assisted micro-milling are presented and explored in depth. The modelling is focused on establishing the scientific relationship between the process variables such as vibration frequency, vibration amplitude, feedrate and spindle speed while taking into account machine dynamics effect and the outcomes such as surface roughness generated, tool wear and material removal rate in the process.
The machine dynamics has been investigated including a static analysis, machine tool-loop stiffness, modal analysis, frequency response function, etc, carried out for both the machine structure and the piezo-actuator device. The instrumentation implementation mainly includes the design of the desktop vibration assisted machining system and its control system. The machining system consists of a piezo-driven XY stage, air bearing spindle, jig, workpiece holder, PI slideway, manual slideway and solid metal table to improve the system stability. The control system is developed using LabVIEW 7.1 programming. The control algorithms are developed based on theoretical models developed by the author.
The process optimisation of vibration assisted micro-milling has been studied by using design and analysis of experiment (DOE) approach. Regression analysis, analysis of variance (ANOVA), Taguchi method and Response Surface Methodology (RSM) have been chosen to perform this study. The effects of cutting parameters are evaluated and the optimal cutting conditions are determined. The interaction of cutting parameters is established to illustrate the intrinsic relationship between cutting parameters and surface roughness, tool wear and material removal rate. The predicted results are confirmed by validation experimental cutting trials.
This research project has led to the following contribution to knowledge:
(1) Development of a prototype desktop vibration assisted micro-milling machine.
(2) Development of theoretical models that can predict the surface finish, tool wear and material removal rate quantitatively.
(3) Establishing in depth knowledge on the use of vibration assisted machining principles.
(4) Optimisation of cutting process parameters and conditions through simulations and machining trials for through investigation of vibration assisted machining.Financial support was obtained from Brunel University
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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
Use of Energy Consumption during Milling to Fill a Measurement Gap in Hybrid Additive Manufacturing
Coupling additive manufacturing (AM) with interlayer peening introduces bulk anisotropic properties within a build across several centimeters. Current methods to map high resolution anisotropy and heterogeneity are either destructive or have a limited penetration depth using a nondestructive method. An alternative pseudo-nondestructive method to map high-resolution anisotropy and heterogeneity is through energy consumption during milling. Previous research has shown energy consumption during milling correlates with surface integrity. Since surface milling of additively manufactured parts is often required for post-processing to improve dimensional accuracy, an opportunity is available to use surface milling as an alternative method to measure mechanical properties and build quality. The variation of energy consumption during the machining of additive parts, as well as hybrid AM parts, is poorly understood. In this study, the use of net cutting specific energy was proposed as a suitable metric for measuring mechanical properties after interlayer ultrasonic peening of 316 stainless steel. Energy consumption was mapped throughout half of a cuboidal build volume. Results indicated the variation of net cutting specific energy increased farther away from the surface and was higher for hybrid AM compared to as-printed and wrought. The average lateral and layer variation of the net cutting specific energy for printed samples was 81% higher than the control, which indicated a significantly higher degree of heterogeneity. Further, it was found that energy consumption was an effective process signature exhibiting strong correlations with microhardness. Anisotropy based on residual strains were measured using net cutting specific energy and validated by hole drilling. The proposed technique contributes to filling part of the measure gap in hybrid additive manufacturing and capitalizes on the preexisting need for machining of AM parts to achieve both goals of surface finish and quality assessment in one milling operation
A model-based sustainable productivity concept for the best decision-making in rough milling operations
[EN]There is a need in manufacturing as in machining of being more productive. However, at the same time, workshops are also urged for lesser energy waste in cutting operations. Specially, rough milling of impellers and bladed integrated disks of aircraft engines need an efficient use of energy due to the long cycle times. Indeed, to avoid dramatic tool failures and idle times, cutting conditions and operations tend to be very conservative. This is a multivariable problem, where process engineers need to handle several aspects such as milling operation type, toolpath strategies, cutting conditions, or clamping systems. There is no criterion embracing productivity and power consumption. In this sense, this work proposes a methodology that meets productivity and sustainability by using a specific cutting energy or sustainable productivity gain (SPG) factor. Three rough milling operations-slot, plunge nad trochoidal milling-were modelled and verified. A bottom-up approach based on data from developed mechanistic force models evaluated and compared different alternatives for making a slot, which is a common operation in that king of workpieces. Experimental data confirmed that serrated end milling with the highest SPG value of 1 is the best milling operation in terms of power consumption and mass removal rate (MRR). In the case of plunge milling technique achieve an SPG < 0.51 while trochoidal milling produces a very low SPG value.The authors acknowledge the support from the Spanish Government (JANO, CIEN Project, 2019.0760) and Basque Government (ELKARTEK19/46, KK-2019/00004).
This research was funded by Tecnologico de Monterrey through the Research Group of Nanotechnology for Devices Design, and by the Consejo Nacional de Ciencia y Tecnologia de Mexico (Conacyt), Project Number 296176, and National Lab in Additive Manufacturing, 3D Digitizing and Computed Tomography (MADiT) LN299129.
The authors also acknowledge the support from Garikoitz Goikoetxea and fruitful discussions with Mr. Jon Mendez (Guhring (c)) and Endika Monge (Hoffmann Group (c))
IN-SITU CHARACTERIZATION OF SURFACE QUALITY IN Îł-TiAl AEROSPACE ALLOY MACHINING
The functional performance of critical aerospace components such as low-pressure turbine blades is highly dependent on both the material property and machining induced surface integrity. Many resources have been invested in developing novel metallic, ceramic, and composite materials, such as gamma-titanium aluminide (Îł-TiAl), capable of improved product and process performance. However, while Îł-TiAl is known for its excellent performance in high-temperature operating environments, it lacks the manufacturing science necessary to process them efficiently under manufacturing-specific thermomechanical regimes. Current finish machining efforts have resulted in poor surface integrity of the machined component with defects such as surface cracks, deformed lamellae, and strain hardening.
This study adopted a novel in-situ high-speed characterization testbed to investigate the finish machining of titanium aluminide alloys under a dry cutting condition to address these challenges. The research findings provided insight into material response, good cutting parameter boundaries, process physics, crack initiation, and crack propagation mechanism. The workpiece sub-surface deformations were observed using a high-speed camera and optical microscope setup, providing insights into chip formation and surface morphology. Post-mortem analysis of the surface cracking modes and fracture depths estimation were recorded with the use of an upright microscope and scanning white light interferometry,
In addition, a non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN) was developed to achieve a real-time total volume crack monitoring capability. This approach showed good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, thereby establishing the significant potential for real-time quality monitoring in manufacturing processes.
The findings from this present study set the tone for creating a digital process twin (DPT) framework capable of obtaining more aggressive yet reliable manufacturing parameters and monitoring techniques for processing turbine alloys and improving industry manufacturing performance and energy efficiency
Manufacturing of high precision mechanical components
The main goal of the thesis is to analyze key aspects of Precision Manufacturing, aiming at optimizing critical manufacturing processes: innovative experimental methodologies and advanced modelling techniques will be applied to cases study of industrial interest which have been successfully optimized
Tool wear monitoring for milling by tracking cutting force model coefficients
This study establishes a way to monitor tool wear in end milling using a tangential force model coefficient method. An experimental investigation of the characteristics of tangential force model coefficients, KTC and KTE, under different cutting conditions is presented. Experimental results indicate that the coefficients are relatively insensitive to the cutting conditions and quite sensitive to tool wear. Several tool wear experiments were performed on AISI 1018 steel. The tool wear was examined using an optical measurement inspection system. The results indicate that KTE increases proportionally with tool flank wear while K TC stays relatively constant until close to the end of tool life. Other possible wear indicators were studied, specifically the radial coefficients (KRC & KRE) and vibration signals. It was found that KRC & KRE are proportional to KTC & KTE, and the vibration signal magnitude is related to flank wear
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