Dynamic analysis of runout correction in milling

Tool runout and its effects is an important area of research within modelling, simulation, and control of milling forces. Tool runout causes tool cutting edges to experience uneven forces during milling. This fact also affects tool life and deteriorates workpiece surface quality. In this article a procedure, in order to diminish the effects of tool runout, is presented. The procedure is based on chip thickness modification by means of the fast correction of the tool feed rate. Dynamic feed rate modification is provided by superposing our own design of a fast feed system driven by a piezoelectric actuator to the conventional feed drive of the CNC machine tool. Previously, a model of the dynamic behaviour of the system was developed to analyze the influence of fast feed rate modification on cutting forces. The model incorporates the piezoelectric actuator response as well as the structural dynamics of the tool and the designed Fast Feed Drive System (FFDS). Simulated and experimental results presented in this paper show the effectiveness and benefits of this new tool runout correction procedure

Effect of state-dependent time delay on dynamics of trimming of thin walled structures

Acknowledgments This work was supported by the National Key R&D Program of China (2020YFA0714900), National Natural Science Foundation of China (52075205, 92160207, 52090054, 52188102).Peer reviewedPostprin

Smart machining system platform for CNC milling with the integration of a power sensor and cutting model

Novel techniques and strategies are investigated for dynamically measuring the process capability of machine tools and using this information for Smart Machine System (SMS) research. Several aspects of the system are explored including system integration, data acquisition, force and power model calibration, feedrate scheduling and tool condition monitoring. A key aspect of a SMS is its ability to provide synchronization between process measurements and model estimates. It permits real time feedback regarding the current machine tool process. This information can be used to accurately determine and keep track of model coefficients for the actual tooling and materials in use, providing both a continued improvement in model accuracy as well as a way to monitor the health of the machine and the machining process. A cutting power model is applied based on a linear tangential force model with edge effect. The robustness of the model is verified through experiments with a wide variety of cutting conditions. Results show good agreement between measured and estimated power. A test platform has been implemented for performing research on Smart Machine Systems. It uses a commercially available OAC from MDSI, geometric modeling software from Predator along with a number of modules developed at UNH. Test cases illustrate how models and sensors can be combined to select machining conditions that will produce a good part on the first try. On-line calibration allows the SMS to fine tune model coefficients, which can then be used to improve production efficiency as the machine learns its own capabilities. With force measurements, the force model can be calibrated and resultant force predictions can be performed. A feedrate selection planner has been created to choose the fastest possible feedrates subject to constraints which are related to part quality, tool health and machine tool capabilities. Monitoring tangential model coefficients is shown to be more useful than monitoring power ratio for tool condition monitoring. As the model coefficients are independent of the cutting geometry, their changes are more promising, in that KTC will increase with edge chipping and breakage, while KTE will increase as the flank wearland expands

The comprehensive analysis of milling stability and surface location error with considering the dynamics of workpiece

Cutting movement is still one of the main means to obtain the desired machined surface. As the most representative cutting method in subtractive manufacturing, milling is widely used in industrial production. However, the chatter induced by the dynamic interaction between machine tool and process not only reduces the accuracy of the machined workpiece, but also increases the tool wear and affects the rotary accuracy of the spindle. The stability lobe diagram can provide stable machining parameters for the technicians, and it is currently an effective way to avoid chatter. In fact, the dynamic interaction between the machine tool and process is very complicated, which involves the machine tool, milling tool, workpiece and fixture. The induced mechanism of chatter depends on different machining scenarios and is not entirely dependent on the vibration modes of milling tool. Therefore, it is important to obtain stable machining parameters and to know the dynamic surface location error distribution, which can ensure machining quality and improve machining efficiency. In this dissertation, two methods for constructing stability lobe diagram are first introduced, and then two machining scales, macro milling and micro milling, are studied. For the macro-milling scale, the dynamic response of the in-process workpiece with time-varying modal parameters during the material removal process is analyzed. The stability lobe diagrams for thin-walled workpiece and general workpiece with continuous radial immersion milling are established respectively. Besides, the cumulative surface location error distribution is also studied and verified for the general workpiece. For the micro-milling scale, the dynamics at the micro-milling tool point is obtained by means of the receptance coupling substructure analysis method. The stability lobe diagram and surface location error distribution are analyzed under different restricted/free tool overhang lengths. The relationship between measurement results and burrs is further explained by cutting experiments, and the difference between the two milling scales is compared in the end

Surface profile and acoustic emission as diagnostics of tool wear in face milling

This thesis examines the relationship between progressive wear of cutting inserts during a face milling operation and the acoustic emission and surface profile generated by that process. Milling experiments were performed on a range of workpiece materials using both eight point and single point inseý arrangements contained in two cutters of different geometries. Surface profile measurements were made using a stylus profilometer at intervals during the experiments. Correlations between the wear state as measured by the length of the flank wear land (Vb) and the spatial frequency content of the surface profiles were established. Investigations into the variation of fractal dimension of a milled surface with Vb demonstrated that no correlation was observable between these quantities. Acoustic emission (AE) measurements were made using a non-contacting fibre-optic interferometer which allowed the rms of the AE signal and its mean frequency to be determined. Correlations between these parameters and Vb were established for a range of workpiece materials and cutter geometries. It was shown that neither AE measurements nor surface profile measurements in isolation could predict tool wear state in all situations. The advantages of fusing data from surface profile and AE sources via an artificial neural network in tool wear monitoring were demonstrate

FAILURE PREDICTION AND STRESS ANALYSIS OF MICROCUTTING TOOLS

Miniaturized devices are the key producing next-generation microelectro-mechanical products. The applications extend to many fields that demand high-level tolerances from microproducts and component functional and structural integrity. Silicon-based products are limited because silicon is brittle. Products can be made from other engineering materials and need to be machined in microscale. This research deals with predicting microtool failure by studying spindle runout and tool deflection effects on the tool, and by measuring the cutting force that would fail the tool during microend-milling. End-milling was performed using a tungsten carbide (Ø1.016 mm dia., 2 flute) tool on SS-316L material. Tool runout measured using a laser was found to be less than 1 µm and tool deflection at 25000 rpm was 20 µm. Finite element analysis (FEA) predicts tool failure due to static bending for a deflection greater than 99% of tool diameter. Threshold values of chipload and cutting force resulting in tool failure were found using workdone by tool. Threshold values to predict tool failure were suggested for axial depth of cut in between 17.25% - 34.5% of cutter length. For a chipload greater than 20% of cutter diameter, the microtool fails instantly for any radial depth of cut

The assessment of surface quality in planed and spindle moulded products

Includes bibliographical referencesSIGLEAvailable from British Library Document Supply Centre- DSC:DX218434 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Displacement-based dynamometer for milling force measurement

This project will study the design and testing of a low-cost dynamometer for milling dynamic force measurement. The monolithic design is based on constrained-motion/flexure-based kinematics, where force is inferred from displacement measured using a low-cost optical interrupter (i.e., a knife edge that partially interrupts the light beam in an emitter-detector pair). The time-dependent displacement of the dynamometer’s moving platform caused by the milling force is converted to the frequency domain, multiplied by the inverse of the dynamometer’s ideally single degree of freedom (SDOF) frequency response function (FRF), and converted back into the time-domain to obtain the time-dependent cutting force. The basic science to be examined is the process dynamics and vibration behavior of the innovative dynamometer design and the ability to measure dynamic cutting forces by applying a structural deconvolution technique. A vibration transducer with high resolution, signal-to-noise ratio, and linearity is therefore able to accurately deconvolve dynamic forces from the measured displacement using the dynamometer’s FRF. This dynamometer will enable accurate and repeatable static and dynamic force measurement for milling operations; however, this approach can be extended to turning, grinding, and drilling as well. A SDOF constrained-motion dynamometer will be designed, manufactured, and evaluated against a commercially available, piezoelectric dynamometer system to validate the displacement-based cutting force approach. A milling process model will be implemented through the solution of second-order, time-delay differential equations of motion that describe the milling behavior [1]. Experiments will be performed to identify the critical stability limit for the various dynamometer systems and mechanistic cutting force coefficients The sensor selection, monolithic constrained-motion design, and companion structural deconvolution technique will provide an innovative, low-cost, high fidelity cutting force dynamometer for use in both production and research environments This approach offers the potential for reduced uncertainty cutting force measurement and significant advancement of metrology for machining operations including the in-process assessment of tool wear and the corresponding machining process health

Precision Machining

The work included in this book focuses on precision machining and grinding processes, including milling, laser machining and polishing on various materials for high-end applications. These processes are in the forefront of contemporary technology, with significant industrial applications. Their importance is also made clear by the important works that are included in the research that is presented in the book. Some important aspects of these processes are investigated, and process parameters are optimized. This is performed in the presented works with significant experimental and modelling work, incorporating modern tools of analysis and measurements

Experimental Study of Built-up-edge Formation in Micro Milling

Micromachining relies on precise tool geometry for effective material removal and acceptable surface finish. The detrimental built-up-edges (BUEs) not only degrade the surface finish of machined features, but also pose a concern for critical applications when BUE can be eventually detached from machined surface. This work presents experimental study on conditions for BUE formation and its effects in micro milling of biocompatible 316L stainless steel. Surface finish and BUE density on a micro milled surface are used to quantify the presence of BUE. A new micro tool is used for each milling condition. A BUE, embedded onto a milled surface, is identified by scanning electron microscopy and energy dispersive X-ray analysis. Optical microscopy is used to quantify BUE density at different locations and milling parameters. Surface finish data from meso-scale milling agree with predicted surface finish, but the model fails to predict the surface finish in micro-scale milling. Micro milling resulted in rough surface finish at low cutting speeds and chip loads due to formation and detachment of BUE from tool surface to machined surface. Hence a new surface finish model including the effect of BUE and tool wear was developed