Intelligent monitoring and identification of cutting states of chips and chatter on CNC turning machine

To realize an intelligent machine tool, which can autonomously determine the cutting states and can change them automatically as required due to changes in the environmental conditions, a method has been developed to monitor and identify the states of cutting for CNC turning based on a pattern recognition technique. The method proposed introduces three parameters to classify the cutting states of continuous chip formation, broken chip formation, and chatter. Among the states of cutting, the broken chip formation is required for the stable and reliable machining process. The three parameters are calculated and obtained by taking the ratio of the average variances of the dynamic components of three cutting forces. The algorithm was developed to calculate the values of three parameters during the process to obtain the reference feature spaces and determine the proper threshold values for classification of the cutting states. A tool dynamometer is developed, and implemented to the CNC turning machine to monitor the turning process.It is proved by a series of cutting experiments that the states of cutting are well identified by the method developed and proposed regardless of the cutting conditions. The algorithm is proposed to obtain the broken chips by changing the cutting conditions during the process.     

Machining assessment of nano-crystalline hydroxyapatite bio-ceramic

Hydroxyapatite (HAP) is a widely used bio-ceramic in the fields of orthopedics and dentistry. This study investigates the machinability of nano-crystalline HAP (nHAP) bio-ceramic in end milling operations, using uncoated carbide tool under dry cutting conditions. Efforts are focused on the effects of various machining conditions on surface integrity. A first order surface roughness model for the end milling of nHAP was developed using response surface methodology (RSM), relating surface roughness to the cutting parameters: cutting speed, feed, and depth of cut. Model analysis showed that all three cutting parameters have significant effect on surface roughness. However, the current model has limited statistical predictive power and a higher order model is desired. Furthermore, tool wear and chip morphology was studied. Machined surface analysis showed that the surface integrity was good, and material removal was caused by brittle fracture without plastic flow.     

Analytical process damping stability prediction

This paper describes an analytical solution for turning and milling stability that includes process damping effects. Comparisons between the new analytical solution, time-domain simulation, and experiment are provided. The velocity-dependent process damping model applied in the analysis relies on a single coefficient similar to the specific cutting force approach to modeling cutting force. The process damping coefficient is identified experimentally using a flexure-based machining setup for a selected tool-workpiece pair (carbide insert-AISI 1018 steel). The effects of tool wear and cutting edge relief angle are also evaluated. It is shown that a smaller relief angle or higher wear results in increased process damping and improved stability at low spindle speeds.     

Application of FEM simulation of chip formation to stability analysis in orthogonal cutting process

Models for chatter prediction in machining often use a mechanistic force model that calculate the force as the product of a material dependent cutting constant and chip area. However, in reality, the forces are the result of complex interaction between the tool and the chip, and are affected by many factors. The effects of these complex, and often nonlinear, factors on the machining dynamics may only be included in chatter prediction if the chip formation process is simulated concurrently with simulation of the machining dynamics. In this paper, finite element simulation of the chip formation process is combined with simulation of chatter dynamics and the inter-relationship between the chip formation process and the chatter phenomenon is investigated. Mesh adaptation technique is used to simulate the chip formation within an FEM elastoplastic analysis with dynamic effects and frictional contact. The combined modeling predicts the occurrence of process damping at low cutting speeds, which other models are generally unable to predict.     

An Approach to Theoretical Modeling and Simulation of Face Milling Forces

A new approach to theoretical modeling and simulation of face milling forces is presented. The present approach is based on a predictive machining theory in which machining characteristic factors in continuous cutting with a single-point cutting tool can be predicted from the workpiece material properties, tool geometry, and cutting conditions. The action of a milling cutter is considered as the simultaneous work of a number of single-point cutting tools, and the milling forces are predicted from input data of workpiece material properties, cutter parameters and tooth geometry, cutting condition, cutter and workpiece vibration structure parameters, and types of milling. A predictive force model for face milling is developed using this approach. In the model, the workpiece material properties are considered as functions of strain, strain rate, and temperature. The ratio of cutter tooth engagement over milling is taken into account for the determination of temperature in the cutting region. Cutter runout is included in the modeling for the chip load. The relative displacement between the cutter and workpiece due to the cutter and workpiece vibration is also included in the modeling to consider the effect on the undeformed chip thickness. A milling force simulation system has been developed using the model, and face milling experimental tests have been conducted to verify the simulation system. It is shown that the simulation results agree well with experimental results.     

Ball end milling mechanistic model based on a voxel-based geometric representation and a ray casting technique

Prediction of machining forces involved in complex geometry can be valuable information for machine shops. This paper presents a mechanistic cutting force simulation model for ball end milling processes, using ray casting and voxel representation methods used in 3D computer graphics field. Using this method, instantaneous uncut chip cross sectional areas can be extracted, which can be used in cutting pressure coefficient extraction and machining simulation including machining forces and geometry of the workpiece. The major advantage of the proposed scheme is that it can simulate milling processes with arbitrary cutting tool geometry on a workpiece with complex geometry, using an algorithm with constant time complexity. A series of cutting experiments were carried out to validate the model.     

Surface roughness prediction in milling based on tool displacements

In this paper, an experimental device using non-contact displacement sensors for the investigation of milling tool behaviour is presented. It enables the recording of high frequency tool vibrations during milling operations. The aim of this study is related to the surface topography prediction using tool displacements and based on tool center point methodology. From the recorded signals and the machining parameters, the tool deformation is modeled. Then, from the calculated deflection, the surface topography in 3D can be predicted. In recent studies, displacements in XY plane have been measured to predict the surface topography in flank milling. In this article, the angular deflection of the tool is also considered. This leads to the prediction of surfaces obtained in flank milling as well as in end milling operations. Validation tests were carried out: the predicted profiles were compared to the measured profile. The results show that the prediction corresponds well in shape and amplitude with the measurement.     

Spindle dynamics identification using particle swarm optimization

Optimal parameters to eliminate machining chatter may be identified using analytical stability models which require the dynamics of the tool-holder-spindle-machine assembly. Receptance coupling substructure analysis (RCSA) provides a useful analytical tool to couple measured spindle-machine dynamics with tool-holder models to predict the tool point frequency response function for the assembly. Previous research has demonstrated a procedure to determine all required spindle receptances from a single measurement, where each mode within the measurement bandwidth was modeled as a fixed-free Euler–Bernoulli beam and fit using a manual, iterative procedure. Here, a particle swarm optimization technique is described for fitting the spindle-machine measurement using a fixed-free Euler–Bernoulli beam model for each mode. The performance of the optimization process and RCSA in predicting the tool tip frequency response is evaluated and the results are presented.     

Parametric glass milling with simultaneous control

Parametric glass milling is presented to machine periodical circular channels on the glass plates for manufacturing micro testing devices. An end mill traverses in the linear motion during the workpiece rotation, which are synchronized by simultaneous control. The glass milling is controlled by 4 parameters in a mathematical model without NC program. Based on the principle of the parametric machining and the effect of the cutter axis inclination on the cutting process, a milling machine was developed to perform the parametric glass milling with an inclined ball end mill. The cutter axis inclination and the actual feed rate are associated with the critical feed rate, the maximum feed rate at which a crack-free surface is finished. As a machining example, a periodical circular channel was machined with a transparent surface by the simultaneous control.     

Process capability study of laser assisted micro milling of a hard-to-machine material

Laser assisted micro milling (LAMM) is capable of generating three-dimensional micro scale features in hard-to-machine materials. This paper compares the process capability of LAMM with conventional micro milling of a hardened tool steel. In particular, the potential advantages of LAMM over micro milling with respect to cutting forces, tool wear, material removal rate, burr formation and surface roughness are investigated when micro milling hardened A2 tool steel (62 HRC). The results show that LAMM has significant advantages over micro milling, especially in terms of cutting forces, material removal rate and tool wear. The average reduction in the resultant cutting force is found to be up to 69% with laser assist. In addition, tool wear is found to be substantially less with laser assist even when the material removal rates are increased by a factor of six over the tool manufacturer recommended cutting conditions.     

Measurement of tool internal temperatures in the tool–chip contact region by embedded micro thin film thermocouples

Sensors capable of providing fast and reliable feedback signals for monitoring and control of existing and emerging machining processes are an important research topic, that has quickly gained academic and industrial interest in recent years. Generally, high-precision machining processes are very sensitive to variation in local machining conditions at the tool–workpiece interface and lack a thorough understanding of fundamental thermomechanical phenomena. Existing sensors to monitor the machining conditions are not suitable for robust in-process control as they are either destructively embedded and/or do not possess the necessary spatial and temporal resolution to monitor local tool internal temperatures during machining at the cutting tip/edge effectively. This paper presents a novel approach for assessing transient tool internal temperature fields in the close vicinity of less than 300 μm of the tool cutting edge. A revised array layout of 10 micro thin film micro thermocouples, fabricated using adapted semiconductor microfabrication methods, has been embedded into polycrystalline cubic boron nitride (PCBN) cutting inserts by means of a modified diffusion bonding technique. Scanning electron microscopy was used to examine material interactions at the bonding interface and to determine optimal bonding parameters. Sensor performance was statically and dynamically characterized. They show good linearity, sensitivity and very fast response time. Initial machining tests on aluminum alloys are described herein. The tests have been performed to demonstrate the functionality and reliability of tool embedded thin film sensors, and are part of a feasibility study with the ultimate goal of applying the instrumented insert in hard machining operations. The microsensor array was used for the acquisition of tool internal temperature profiles very close to the cutting tip. The influence of varying cutting parameters on transient tool internal temperature profiles was measured and discussed. With further study, the described instrumented cutting inserts could provide more valuable insight into the process physics and could improve various aspects of machining processes, e.g. reliability, tool life, and workpiece quality.     

Spindle speed variation and adaptive force regulation to suppress regenerative chatter in the turning process

Chatter suppression in machining processes results in more material removal rate, high precision and surface quality. In this paper, two control strategies are developed to suppress chatter vibration in the turning process including a worn tool. In the first stage, a sinusoidal spindle speed variation around the mean speed is modulated to disturb the regenerative mechanism. The optimal amplitudes of the speed modulations are found based on a genetic algorithm such that the input energy to the turning process is minimized. In the second stage, to improve the response of the system which is associated with small ripples under the steady state condition, an adaptive controller is designed. In this stage, the provided external force (e.g., by a piezo-actuator) is the input variable. Results are provided for each control strategy. It is shown that if both control approaches are applied simultaneously, chatter vibration is suppressed in less time without any ripples at the steady state condition.     

AlCrSiN/AlCrN/AlCrON/AlCrN多层复合涂层的研究

目的 解决硬质合金刀具高速干切削难加工材料面临效率低、寿命短的难题,提升刀具涂层的耐热能力,在AlCrSiN涂层中周期性植入AlCrON热屏障层,并在其两侧沉积AlCrN层进行包夹,改善含氧层的韧性,既能保持涂层刀具较高的强度,又能改善其耐热能力.方法 采用全自动电弧离子镀膜机,研制具有不同调制周期的AlCrSiN/A...     

Analysis of machined surface quality in a single-pass of ball-end milling on Inconel 718

The ball-end milling process is widely used for generating three-dimensional sculptured surfaces with definite curvature. In such cases, variation of surface properties along the machined surface curvatures is not well understood. Therefore, this paper reports the effect of machining parameters on the quality of surface obtained in a single-pass of a ball-end milling cutter with varying chip cross-sectional area. This situation is analogous to generation of free form cavities, pockets, and round fillets on mould surfaces. The machined surfaces show formation of distinct bands as a function of instantaneous machining parameters along the periphery of cutting tool edge, chip compression and instantaneous shear angle. A distinct variation is also observed in the measured values of surface roughness and micro-hardness in these regions. The maximum surface roughness is observed near the tool tip region on the machined surface. The minimum surface roughness is obtained in the stable cutting zone and it increases towards the periphery of the cutter. Similar segmentation was observed on the deformed chips, which could be correlated with the width of bands on the machined surfaces. The sub-surface quality analysis in terms of micro-hardness helped define machining affected zone (MAZ). The parametric effects on the machining induced shear and residual stresses have also been evaluated.     

Micro dimple milling on cylinder surfaces

The paper presents a micro dimple machining on a cylinder surface with a two-flutes ball end mill. When the cutter axis is inclined and the depth of cut is less than the tool radius, non-cutting time, during which neither of the two cutting edges contacts the workpiece, appears in a rotation of the cutter. The rotation of the workpiece and the feed of the tool are controlled so that the cutting areas do not overlap each other. In order to incline the tool with respect to the tangential direction on the cylinder surface, the tool is located at a position oriented at 45° from the top of the cylinder. An analytical model is presented to control the shapes of the dimples with the cutting parameters. The presented machining is verified in cutting tests with measuring the shape and the profile of the dimples. Pre-machining operations are conducted to have a high cylindricity of the workpiece in longitudinal turning and polishing. The cutter runout of the tool is also eliminated by adjusting the orientation and the position of the tool in the collet chuck with measuring the cutting force. The micro dimples are machined accurately as they are simulated.     

Evaluating the use phase energy requirements of a machine tool system

This paper has an energy consumption reduction perspective by considering alternative machining strategies and system components interactions translated into variable and constant power flows with respect to various use phase regimes of a machine tool system. The methodology is able to estimate the mechanical energy requirements of the spindle and feed axes with respect to 2.5D machining strategies by taking into account steady-state and transient regimes. In addition, the specific amount of fixed energy drawn by a machine was determined based on a careful monitoring of the energy share amongst the auxiliary equipment that supports the accomplishment of the machining tasks. The numerical results were experimentally validated and the good agreement between them led to the conclusion that the proposed methodology can be used effectively for the calculation of the total energy required by a machine tool system for the milling of a part. This enables a straightforward comparison of different milling part programs with respect to their energy consumption levels.     

Basic Approach to a Prediction System for Burr Formation in Face Milling

Geometric parameters and material properties are the two major categories of factors affecting burr formation in the milling process. Geometric parameters such as tool geometry, workpiece geometry, or process condition influence workpiece edge quality at the tool-chip interface. This study identifies a unified criterion to analyze burr formation for different tool engagements. The criterion exploits the exit order of cutting edges of the tool along the workpiece edge, which essentially includes the 3-D nature of the process. The criterion correlates the cutting mechanism and burr formation using the exit order sequence (EOS) as an approximation of chip flow angle. The impact of different possible exit order sequences on burr formation is analyzed. Previously observed phenomena are explained based on the EOS. Also, experiments are done with three different materials (with different ductilities) to analyze the impact of material properties on burr formation for a given EOS. Although burr sizes are different quantitatively with different material, the ranking of burr size for different EOS remained the same. An algorithm for the prediction of burr formation in face milling based on EOS is developed and tested and validated on two different profiles of an automotive part.     

Application of Taguchi method to selection of optimal lubrication and cutting conditions in face milling of AlMg3

This paper outlines the Taguchi optimization methodology, which is applied to optimize the cutting parameters in face milling when machining AlMg₃ (EN AW 5754) with HSS (high speed steel) tool under semi-finishing conditions in order to get the best surface roughness and the minimum power consumption. Beside the conventional flood lubrication, the investigations include the minimal quantity lubrication and the dry milling. These environment-friendly cutting techniques are considered two practical ways to the cleaner manufacturing in the context of the sustainable production. The parameters evaluated are the cutting speed, the depth of cut, the feed rate and the cooling lubrication techniques (cutting fluid flow). The appropriate orthogonal array, signal to noise (S/N) ratio and Pareto analysis of variance (ANOVA) are employed to analyze the effect of the mentioned parameters on the good surface finish (surface roughness). This paper illustrates the application of the techniques for single performance characteristics optimization, which employs the weighting factors to each of the S/N ration of the responses to obtain a multi-response S/N ratio for each trial of the orthogonal array and, finally, a single optimal process parameters setting. Using Taguchi method for the design of experiments (DOE), it is investigated the significant influence and the parameters interaction effect with minimum number of trials as compared with a full factorial design.     

Cutting tool temperatures in interrupted cutting—The effect of feed-direction modulation

Transient tool temperatures in interrupted machining processes were investigated. The initial focus was feed-direction modulated turning. Here, the instantaneous uncut chip thickness (IUCT) was modeled including the regenerative effect introduced by the modulation. Treating the tool as a one-eighth semi-infinite body, for a rectangular heat patch governed by the IUCT at the corner, the tool heat conduction problem was solved. The Green’s function solution procedure included heat convection from exterior surfaces. The results indicated that modulation lowered the cutting temperature, more significantly at a higher modulation frequency. However, heat conduction into the tool dominated over convection to the ambient. The IUCT was found to lag the peak temperature, indicating that modulation can possibly alter the thermal softening of the cutting tool in continuous cutting without a concomitant decrease in material removal rate. The same tool temperature model applied to face-milling indicated that the peak temperature occurred only at cut exit. Carefully planned interrupted hard-facing experiments were performed varying the frequency and duration of interruption. Tool-life data confirmed the beneficial effects of lower cutting temperatures due to slight interruption.