A dynamics-driven approach to precision machines design for micro-manufacturing and its implementation perspectives

Precision machines are essential elements in fabricating high quality micro products or micro features and directly affect the machining accuracy, repeatability and efficiency. There are a number of literatures on the design of industrial machine elements and a couple of precision machines commercially available. However, few researchers have systematically addressed the design of precision machines from the dynamics point of view. In this paper, the design issues of precision machines are presented with particular emphasis on the dynamics aspects as the major factors affecting the performance of the precision machines and machining processes. This paper begins with a brief review of the design principles of precision machines with emphasis on machining dynamics. Then design processes of precision machines are discussed, and followed by a practical modelling and simulation approaches. Two case studies are provided including the design and analysis of a fast tool servo system and a 5-axis bench-top micro-milling machine respectively. The design and analysis used in the two case studies are formulated based on the design methodology and guidelines

Virtual manufacturing: prediction of work piece geometric quality by considering machine and set-up

Lien vers la version éditeur: http://www.tandfonline.com/doi/full/10.1080/0951192X.2011.569952#.U4yZIHeqP3UIn the context of concurrent engineering, the design of the parts, the production planning and the manufacturing facility must be considered simultaneously. The design and development cycle can thus be reduced as manufacturing constraints are taken into account as early as possible. Thus, the design phase takes into account the manufacturing constraints as the customer requirements; more these constraints must not restrict the creativity of design. Also to facilitate the choice of the most suitable system for a specific process, Virtual Manufacturing is supplemented with developments of numerical computations (Altintas et al. 2005, Bianchi et al. 1996) in order to compare at low cost several solutions developed with several hypothesis without manufacturing of prototypes. In this context, the authors want to predict the work piece geometric more accurately by considering machine defects and work piece set-up, through the use of process simulation. A particular case study based on a 3 axis milling machine will be used here to illustrate the authors’ point of view. This study focuses on the following geometric defects: machine geometric errors, work piece positioning errors due to fixture system and part accuracy

Chip-controlled 3-D complex cutting tool insert design and virtual manufacturing simulation

Designing suitable tools for the turning operation is of vital interest to manufacturers. The tool inserts used nowadays adopt complex geometric shapes. A question facing many manufacturers is how to effectively design complex shaped tool inserts and how to prove the validity of such design. One of the important criteria for selecting inserts is the ability to control chip formation and chip breaking;The research work described in this dissertation attempted to bring innovation into the cutting tool insert design process by using feature-based modeling and by proposing a predictive chip model and integrating it into the design process. Such model integration makes the tool insert design a much more effective process and also enhances the decision-making required in insert design;A new 3-D kinematic chip model was developed to depict chip behavior in a complex groove insert. The model derived showed the analytical relationships between chip shape parameters and chip motion parameters. This dissertation explained how the kinematic model could be modified to take into account all possible 3-D complex groove shapes. A mathematical model was also developed from experimental data to serve the current need for cutting tool design;Other research work presented in this dissertation is the simulation of the machining process in a virtual environment. The virtual machining simulation can be of great benefit for researchers in manufacturing to use the platform as a testbed for product development and testing

Cylindrical Machining Workpiece Temperature and Bore Cylindricity

Cylindrical machining processes are widely used in industry to achieve better dimensional and geometrical tolerances and finer surface finish on cylindrical workpieces. Hard turning is utilized to machine hardened steels for large bearing rings and finish boring is used to machine cylinder bores during automotive engine block production. Workpiece temperature is critical for cylindrical machining processes. In hard turning, high machined surface temperature leads to the formation of white layer, reducing the workpiece fatigue life. In finish boring, thermal expansion due to workpiece temperature rise causes bore cylindricity errors, leading to engine performance issues. Besides thermal expansion, other factors like cutting force, spindle, and fixture/clamping also affect the bore cylindricity in finish boring. This dissertation studied the cylindrical machining workpiece temperature through both experiment and modelling and identified bore cylindricity error sources in finish boring. Firstly, two experimental methods were developed to measure machined surface temperatures in hard turning. The first method, based on a tool-foil thermocouple, estimated the machined surface temperature using a metal foil embedded in the workpiece to measure the tool tip temperature. The second method used a thermocouple embedded in the tool with its tip continuously sliding on the machined surface behind the cutting edge. The inverse heat transfer method was applied on a three-dimensional thermal model to find the machined surface temperature near the cutting edge. These two methods, although based on distinct approaches, gave correlated predictions in hard turning tests, indicating both to be feasible for the measurement of hard turning machined surface temperatures. Secondly, four finite element method (FEM) models, namely the advection model, surface heat model, heat carrier model and ring heat model, were studied to predict the workpiece temperature in finish boring. Cylinder boring experiments were conducted to measure the workpiece temperature and evaluate the capability of four models in terms of accuracy and efficiency. Results showed good correlations between model-predicted and experimentally- measured temperatures. Advantages and disadvantages of each model were discussed. For studying detailed cylinder boring workpiece temperature, it was suggested to use the ring heat model to estimate the moving heat flux and the heat carrier model for local workpiece temperature calculation. Thirdly, experimental and FEM analysis was combined to identify the bore cylindricity error sources in finish boring. Experiments were conducted to measure the workpiece temperature, cutting and clamping forces, spindle error, and bore shape. FEM analysis of the workpiece temperature, thermal expansion, and deformation due to cutting and clamping forces was performed. The coordinate measurement machine (CMM) measurements of the bore after finish boring showed the 5.6 micrometer cylindricity and a broad spectrum from 2nd to 10th harmonics. The FEM revealed effects of workpiece thermal expansion (1.7 micrometer cylindricity), deformation due to cutting force (0.8 micrometer cylindricity), and clamping force (1.9 micrometer cylindricity) on the finished bore and the dominance by the 1st to 3rd harmonics using the three-jaw fixture. The spindle synchronous radial error motion (3.2 micrometer cylindricity) was dominated by 4th and higher order harmonics and matched well with the high (above 4th) harmonics in CMM measurements (2.9 micrometer cylindricity). The spindle error was found to be the dominant error source for bore cylindricity in finish boring. The experimental methods, FEM models and approaches developed in this dissertation provide better understanding of cylindrical machining processes and are useful for optimization of the process parameters.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137076/1/leichan_1.pd

Process design for 5-axis ball end milling using a real-time capable dynamic material removal simulation

For repairing turbine blades or die and mold forms, additive manufacturing processes are commonly used to build-up new material to damaged sections. Afterwards, a subsequent re-contouring process such as 5-axis ball end milling is required to remove the excess material restoring the often complex original geometries. The process design of the re-contouring operation has to be done virtually, because the individuality of the repair cases prevents actual running-in processes. Hard-to-cut materials e.g. titanium or nickel alloys, parts prone to vibration and long tool holders complicate the repair even further. Thus, a fast and flexible material removal simulation is needed. The simulation has to predict suitable processes focusing shape deviations under consideration of process stability for arbitrary complex engagement conditions. In this paper, a dynamic multi-dexel based material removal simulation is presented, which is able to predict high-resolution surface topography and stable parameters for arbitrary processes such as 5-axis ball end milling. In contrast to other works, the simulation is able to simulate an unstable process using discrete cutting edges in real-time. © 2020, The Author(s)

Surface Location Error in Robotic Milling: Modeling and Experiments

Robotic milling offers new opportunities for discrete part manufacturing as an alternative to milling using large conventional machine tools. The advantage of industrial robots is their large work volume, configurability, and comparatively low cost. However, robots are significantly less stiff than conventional machine tools, which can lead to poor surface finish, low machining accuracy, and low material removal rates. The purpose of this research is to predict the geometric errors, or surface location errors, that occur in a robotic mulling tool path, validate these predictions with machining tests, and compensate these errors by tool path modification. Compared with conventional machine tools, robots possess low stiffness, low frequency vibration modes and the presence of these modes causes surface location errors that are nearly independent of spindle speed in the range typically used for machining. Additionally, the robot often exhibits errors relative to the commanded tool path. By developing an understanding of both the dynamics of the robot and its tool path accuracy, predictions were made of the surface location error for a machined part and a compensation algorithm was developed. The accuracy of the predictions and compensation algorithm were verified with a series of experiments. Through this research it was determined that robotic milling is prone to large surface location errors, but it is possible to reduce these through offline compensation

3D Finite Element Simulation of Micro End-Milling by Considering the Effect of Tool Run-Out

Understanding the micro milling phenomena involved in the process is critical and difficult through physical experiments. This study presents a 3D finite element modeling (3D FEM) approach for the micro end-milling process on Al6082-T6. The proposed model employs a Lagrangian explicit finite element formulation to perform coupled thermo-mechanical transient analyses. FE simulations were performed at different cutting conditions to obtain realistic numerical predictions of chip formation, temperature distribution, and cutting forces by considering the effect of tool run-out in the model. The radial run-out is a significant issue in micro milling processes and influences the cutting stability due to chip load and force variations. The Johnson-Cook (JC) material constitutive model was applied and its constants were determined by an inverse method based on the experimental cutting forces acquired during the micro end-milling tests. The FE model prediction capability was validated by comparing the numerical model results with experimental tests. The maximum tool temperature was predicted in a different angular position of the cutter which is difficult or impossible to obtain in experiments. The predicted results of the model, involving the run-out influence, showed a good correlation with experimental chip formation and the signal shape of cutting forces

Understanding the Mechanism of Abrasive-Based Finishing Processes Using Mathematical Modeling and Numerical Simulation

Recent advances in technology and refinement of available computational resources paved the way for the extensive use of computers to model and simulate complex real-world problems difficult to solve analytically. The appeal of simulations lies in the ability to predict the significance of a change to the system under study. The simulated results can be of great benefit in predicting various behaviors, such as the wind pattern in a particular region, the ability of a material to withstand a dynamic load, or even the behavior of a workpiece under a particular type of machining. This paper deals with the mathematical modeling and simulation techniques used in abrasive-based machining processes such as abrasive flow machining (AFM), magnetic-based finishing processes, i.e., magnetic abrasive finishing (MAF) process, magnetorheological finishing (MRF) process, and ball-end type magnetorheological finishing process (BEMRF). The paper also aims to highlight the advances and obstacles associated with these techniques and their applications in flow machining. This study contributes the better understanding by examining the available modeling and simulation techniques such as Molecular Dynamic Simulation (MDS), Computational Fluid Dynamics (CFD), Finite Element Method (FEM), Discrete Element Method (DEM), Multivariable Regression Analysis (MVRA), Artificial Neural Network (ANN), Response Surface Analysis (RSA), Stochastic Modeling and Simulation by Data Dependent System (DDS). Among these methods, CFD and FEM can be performed with the available commercial software, while DEM and MDS performed using the computer programming-based platform, i.e., "LAMMPS Molecular Dynamics Simulator," or C, C++, or Python programming, and these methods seem more promising techniques for modeling and simulation of loose abrasive-based machining processes. The other four methods (MVRA, ANN, RSA, and DDS) are experimental and based on statistical approaches that can be used for mathematical modeling of loose abrasive-based machining processes. Additionally, it suggests areas for further investigation and offers a priceless bibliography of earlier studies on the modeling and simulation techniques for abrasive-based machining processes. Researchers studying mathematical modeling of various micro- and nanofinishing techniques for different applications may find this review article to be of great help