New Orleans, Louisiana Paper Number: IMECE2002-MED-PPO-03 ADAPTIVE FEEDRATE SCHEDULING AND MATERIAL ENGAGEMENT ANALYSIS FOR HIGH PERFORMANCE MACHINING

ABSTRACT This paper presents a technique of feedrate scheduling by analyzing the material removal volume when a tool moves in linear, circular, or parametric curved motions. Tool motions of different types of endmilling cutters are considered in this study. By studying the relationship between the cutter geometry and the tool motion, the material removal rates of different cutters are analyzed. The adaptive feedrate scheduling can be determined to maintain a constant cutting load. The technique developed in this research can be used for tool path generation in CAD/CAM systems for 2.5D NC machining

Process planning methodology and evaluation of tool life for micromilling with an application to the fabrication of thin wall structure

Ph. D. Thesis.The scaling down effect on feature geometries and tools used in micromilling results in low feature stiffness and excessive tool wear. To achieve the required costs and tolerances, optimisation of the machining processes and their associated parameters are necessary which requires a thorough understanding of machining characteristics. Furthermore, the compensation must be sought for downscaling issues that arise at the process planning stage. Hence, the effect of the characteristics of the cutting tool, workpiece material and machining parameters are investigated in this research through a critical review of the literature followed by a numerical and experimental study of the impact of process variables. The research findings are used in the development of a process planning methodology for micromilling of components with application to high aspect ratio structures, to assist machine operators and to fill the gap between industrial and academic machining knowledge. From the investigation of machining sequences, the study of machining layer strategy considering the sequence of removal of excess material using numerical simulation, strategic planning of machining layers in relation to feature stiffness is required, in particular to the machining of high aspect ratio features. The results from numerical simulation recommend an improved layer strategy for micromilling of thin wall structures, which were then experimentally validated in relation to machining time and geometrical and surface accuracy. The importance of planning tool entry and exit position in relation to feature rigidity was highlighted. The increase in depth of cut shows to improve the tool engagement reducing the thin wall deflection by 168 μm and appearance of the burr along the wall edge indicated by up to 200% drop in burr width. The investigation of tool paths showed the suitability of strategies for machining of circular and linear geometries. Also, the experimental findings emphasise on considering the feature geometry type in the selection of tool paths to achieve a balance between high-performance machining and improved productivity. This study also investigates tool life, associated with flank wear rate, surface roughness, volumetric tool loss and the degradation of the cutting edge radius for micro endmills where a direct correlation between cutting speed and tool wear rate has been found. The new procedure for tool life prediction in conjunction with clear tool rejection criteria for the micro end mill is recommended. Along with standard procedure for the evaluation of tool change intervals to avoid tool failure and consequential defects in parts produced. In addition to the findings in the literature on machine process planning and findings from the study of machining sequence on the thin wall structure and tool life investigation conducted, a new process planning methodology for micromilling has been proposed. The process planning methodology includes four distinct modules i.e. feature recognition, tool selection, machining parameter selection and machining sequence planning. The feature recognition module proposes a new approach to identify key feature faces and their corresponding machining attributes required for tasks in process planning. In the tool selection module, a new methodology for the evaluation of the machinability index and the tool replacement strategy for micro endmills are proposed to guide the operator in the task of tool selection and estimating tool replacement intervals. The machining parameter module provides a systematic approach for the selection spindle speed, feedrate and depth of cut. The machine sequence planning module assists the operator in selecting a suitable tool path and tool layer strategy along with a compensate technique for tool path errors. An artefact with thin wall features has been fabricated using the methodology proposed and the conventional process planning method. The results show the part processed using the proposed methodology achieved better geometrical tolerance, and improved repeatability. It also show a 17% improvement in mean surface roughness, which demonstrates the effectiveness of the proposed methodology

Chip Production Rate and Tool Wear Estimation in Micro-EndMilling

abstract: In this research, a new cutting edge wear estimator for micro-endmilling is developed and the reliabillity of the estimator is evaluated. The main concept of this estimator is the minimum chip thickness effect. This estimator predicts the cutting edge radius by detecting the drop in the chip production rate as the cutting edge of a micro- endmill slips over the workpiece when the minimum chip thickness becomes larger than the uncut chip thickness, thus transitioning from the shearing to the ploughing dominant regime. The chip production rate is investigated through simulation and experiment. The simulation and the experiment show that the chip production rate decreases when the minimum chip thickness becomes larger than the uncut chip thickness. Also, the reliability of this estimator is evaluated. The probability of correct estimation of the cutting edge radius is more than 80%. This cutting edge wear estimator could be applied to an online tool wear estimation system. Then, a large number of cutting edge wear data could be obtained. From the data, a cutting edge wear model could be developed in terms of the machine control parameters so that the optimum control parameters could be applied to increase the tool life and the machining quality as well by minimizing the cutting edge wear rate. In addition, in order to find the stable condition of the machining, the stabillity lobe of the system is created by measuring the dynamic parameters. This process is needed prior to the cutting edge wear estimation since the chatter would affect the cutting edge wear and the chip production rate. In this research, a new experimental set-up for measuring the dynamic parameters is developed by using a high speed camera with microscope lens and a loadcell. The loadcell is used to measure the stiffness of the tool-holder assembly of the machine and the high speed camera is used to measure the natural frequency and the damping ratio. From the measured data, a stability lobe is created. Even though this new method needs further research, it could be more cost-effective than the conventional methods in the future.Dissertation/ThesisDoctoral Dissertation Mechanical Engineering 201

Investigation into micro machinability of Mg based metal matrix compostites (MMCs) reinforced with nanoparticles

PhD ThesisAs composite materials with combination of low weight and high engineering strength, traditional metal matrix composites (MMCs) with micro-sized reinforcement (micro-MMCs) have been utilized in numerous area such as aerospace, automobile, medical and advanced weapon systems in the past two decades. With the development of composite materials, metal matrix composites reinforced with small volume fraction of nano-sized reinforcements (nanoMMCs) exhibits an equivalent and even better properties than that reinforced with large volume of micro-sized reinforcement and thus receive increasing attention from academia and industries. MMCs components are typically fabricated in near net shape process such as casting. But micro machining processes are indispensable in order to meet the increasing demands on the component with high dimensional accuracy and complex shapes. However, the enhanced mechanical properties of MMCs and tool-like hardness of reinforced particles bring challenges to machining process. The deteriorative machined surface finish and excessive tool wear have been recognised as the main obstacles during machining of MMCs due to their heterogeneous and abrasive nature. In this research, the detailed material removal mechanism of nano-MMCs in terms of micro machinability, micro tool wear and simulated material removal process with finite element analysis (FEA) is investigated. The systematic experimental studies on micro machining mechanism of magnesium-based MMCs reinforced with nanoparticles (Ti, TiB2, BN, ZnO) are conducted. The cutting force, burr formation, surface roughness and morphology are characterised to investigate the micro machinability under the effect of various machining parameters, particle volume fraction and matrix/reinforcement materials using design of experiment (DoE) and analysis of variance (ANVOA) methods. The micro structure changes of Mg-MMCs by addition of nanoparticles were taken into account. In addition, surface morphology and the minimum chip thickness is obtained and characterised with the aim of examining the specific cutting energy. A comprehensive investigation of tool wear mechanisms in the micro milling of Mg-MMCs is conducted. The tool wear is characterised both quantitatively and qualitatively by observing tool wear patterns and analysing the effect of cutting parameters and tool coating on average flank wear, reduction in tool diameter, cutting forces, surface roughness, and burr formation. The main wear mechanisms at different machining conditions are determined. Finally, the tool wear phenomenon observed from experiments is explained by simulating the tool-particles interaction using finite element modelling, and hence new wear mechanisms are proposed for machining nano-MMCs. iv The two dimensional micromechanical finite element (FE) models are established to study the material removal mechanism of MMCs reinforced with micro-sized and nanoparticles in micro machining process with consideration of size effect. Two phases, namely particle and matrix are modelled in FE cutting models. Particle fracture properties are involved in micro-sized particles to study the fracture behaviours. The cutting force, tool-particles interaction, particle fracture behaviours, stress/strain distribution, chip formation process and surface morphology are investigated in the FE models. The surface defect generation mechanism is studied in details by developing the additional three dimensional (3D) FE models in machining micro-MMCs. Moreover, the cutting mechanism comparison between machining nano-MMCs and microMMCs is conducted to investigate the effect of significant particle size reduction from micro to nano-scale. The model validation is carried out by studying the chip morphology, cutting force, surface morphology obtained from machining experiments and good agreements are found with the simulation results

Making CNC Machines Smarter

CNC machines are a commonly used manufacturing tool. Over the years, they have become increasingly sophisticated. While there is a lot of research into making the machines more sophisticated, there is little research into making the machines smarter. CNC machines lack any intelligence to make decisions. Making a system fully intelligent is extremely difficult to do in one step. This thesis will focus on small steps that will hopefully lead to an intelligent CNC machine. The thesis first explores using audio data for perceiving the cutting state of the machine. Experienced machinist can listen to the machine and determine how it is cutting and can assess changes for improving the cutting rate or surface finish. Ideally, the machine should be able to determine how it is cutting and use that information to adjust machine parameter for a cutting goal. In this project, a neural network was trained to detect the presence of chatter. Unlike conventional methods, this project involved only doing a Fourier transform of the audio data. The neural network had success in identifying chatter in the audio data in all the cases that were tested. Next the thesis explores incorporating a model of the cutting process and using it to generate its own toolpaths. This method involves using a cutting model that uses 2D pixels for determining the cut and uncut area. Using this model, a tool path is generated by optimizing each step to achieve an optimal cutting goal. Further, constraints are added to the optimization, which improve the toolpath by limiting the turning radius, which makes the path smoother. The result is a toolpath that maintains a consistent cutting force, and smooth turning. The previous project relied on a simplified model of the cutting process. As CNC machines become smarter, they will need to have more accurate models of the process. Part of this would be to have accurate dynamic models of the machine. The last project focuses on building an automated device for capturing such models. This device uses a novel approach compared to traditional tap testing. The devices uses a voice coil for actuation, a load cell for force measurement, and a laser displacement for measuring the vibrations. This allows the tap tester to be able to measure many different tools without manually attaching accelerometers to each tool manually

Machining Chatter in Flank Milling and Investigation of Process Damping in Surface Generation

Although a considerable amount of research exists on geometrical aspects of 5-axis flank milling, the dynamics of this efficient milling operation have not yet been given proper attention. In particular, investigating machining chatter in 5-axis flank milling remains as an open problem in the literature. The axial depth of cut in this operation is typically quite large, which makes it prone to machining chatter. In this thesis, chatter in 5-axis flank milling is studied by developing analytical methods of examining vibration stability, generating numerical simulations of the process, and conducting experimental investigations. The typical application of 5-axis milling includes the machining of thermal resistant steel alloys at low cutting speeds, where the process damping dominates the machining vibration. The results of experimental study in this thesis showed that the effect of process damping is even stronger in flank milling due to the long axial engagement. Accordingly, the first part of the thesis is devoted to studying process damping, and in the second part, the modeling of chatter in flank milling is presented. Linear and nonlinear models have been reported in the literature that account for process damping. Although linear models are easier to implement in predicting stability limits, they could lead to misinterpretation of the actual status of the cut. On the other hand, nonlinear damping models are difficult to implement for stability estimation analytically, yet they allow the prediction of “finite amplitude stability” from time domain simulations. This phenomenon of “finite amplitude stability” has been demonstrated in the literature using numerical simulations. In this thesis, that phenomenon is investigated experimentally. The experimental work focuses on uninterrupted cutting, in particular plunge turning, to avoid unduly complications associated with transient vibration. The experiments confirm that, because of the nonlinearity of the process damping, the transition from fully stable to fully unstable cutting occurs gradually over a range of width of cut. The experimental investigation is followed by developing a new formulation for process damping based on the indentation force model. Then, the presented formulation is used to compute the stability lobes in plunge turning, taking into account the effect of nonlinear process damping. The developed lobes could be established for different amplitudes of vibration. This is a departure from the traditional notion that the stability lobes represent a single boundary between fully stable and fully unstable cutting conditions. Moreover, the process damping model is integrated into the Multi-Frequency Solution and the Semi Discretization Method to establish the stability lobes in milling. The basic formulations are presented along with comparisons between the two approaches, using examples from the literature. A non-shallow cut is employed in the comparisons. Assessing the performance of the two methods is conducted using time domain simulations. It is shown that the Semi Discretization Method provides accurate results over the whole tested range of cutting speed, whereas higher harmonics are required to achieve the same accuracy when applying the Multi Frequency Solution at low speeds. Semi Discretization method is modified further to calculate the stability lobes in flank milling with tools with helical teeth. In addition to the tool helix angle and long axial immersion, the effect of instantaneous chip thickness on the cutting force coefficients is considered in the modified formulation of Semi Discretization as well. Considering the effect of chip thickness variation on the cutting force coefficients is even more important in the modeling of 5-axis flank milling, where the feedrate, and consequently the chip thickness, varies at each cutter location. It also varies along the tool axis due to the additional rotary and tilt axis. In addition to the feedrate, the tool and workpiece engagement geometry varies at each cutter location as well. The actual feedrate at each cutter location is calculated by the dynamic processing of the toolpath. The tool and workpiece engagement geometry is calculated analytically using the parametric formulation of grazing surface at the previous and current passes. After calculating the instantaneous chip thickness and tool/workpiece engagement geometry, they are integrated into the Semi Discretization Method in 5-axis flank milling to examine the stability of vibration at each cutter location. While the presented chatter analysis results in establishing stability lobes in 3-axis flank milling, it results in developing a novel approach in presenting the stability of the cut in 5-axis flank milling. The new approach, namely “stability maps”, determines the unstable cutter locations of the toolpath at each spindle speed. The accuracy of established 3-axis flank milling stability lobes and 5-axis stability maps is verified by conducting a set of cutting experiments and numerical simulations

An Inexpensive Autonomous Colony Separator With Sub-Micrometer Repeability

M.S. Thesis. University of Hawaiʻi at Mānoa 2018

Proceedings of the 4th International Conference on Innovations in Automation and Mechatronics Engineering (ICIAME2018)

The Mechatronics Department (Accredited by National Board of Accreditation, New Delhi, India) of the G H Patel College of Engineering and Technology, Gujarat, India arranged the 4th International Conference on Innovations in Automation and Mechatronics Engineering 2018, (ICIAME 2018) on 2-3 February 2018. The papers presented during the conference were based on Automation, Optimization, Computer Aided Design and Manufacturing, Nanotechnology, Solar Energy etc and are featured in this book

A Micro-milling cutting force and chip formation modeling approach for optimal process parameters selection

Las últimas décadas evidencian una demanda creciente por componentes miniaturizados con dimensiones reducidas y tolerancias estrechas, lo cual ha conllevado al desarrollo de la micro y nanotecnología. El micro-fresado, dentro de los procesos de micro-mecanizado, tiene el potencial de ser uno de los procesos de remoción de material más costo-efectivos y eficientes debido a su facilidad de aplicación, variedad de materiales de trabajo y flexibilidad geométrica. Se enfrenta a unos retos complejos debido al efecto de tamaño, vibraciones y otros factores incontrolables. Este estudio analiza dicho proceso orientado hacia desarrollar una mejor comprensión de la mecánica del micro-corte para ser aplicada en la optimización de parámetros de proceso. Se propone un acercamiento al modelado híbrido en forma novedosa, que permite una evaluación numérica a priori para evaluación de fuerzas y esfuerzos, combinado con experimentación para evaluar parámetros relevantes a la industria (formación de rebabas, desgaste de herramientas, entre otros).DoctoradoDoctor en Ingeniería Mecánic

Cold Micro Metal Forming

This open access book contains the research report of the Collaborative Research Center “Micro Cold Forming” (SFB 747) of the University of Bremen, Germany. The topical research focus lies on new methods and processes for a mastered mass production of micro parts which are smaller than 1mm (by forming in batch size higher than one million). The target audience primarily comprises research experts and practitioners in production engineering, but the book may also be of interest to graduate students alike