Cutter-workpiece Engagement Research Articles

Generic Cutting Force Modeling with Comprehensively Considering Tool Edge Radius, Tool Flank Wear and Tool Runout in Micro-End Milling.

Accurate cutting force prediction is crucial in improving machining precision and surface quality in the micro-milling process, in which tool wear and runout are essential factors. A generic analytic cutting force model considering the effect of tool edge radius on tool flank wear and tool runout in the micro-end milling process is proposed. Based on the analytic modeling of the cutting part of the cutting edge in the end face of the micro-end mill bottom, the actual radius model of the worn tool is established, considering the tool edge radius and tool flank wear. The tool edge radius, tool wear, tool runout, trochoidal trajectories of the current cutting edge, and all cutting edges in the previous cycle are comprehensively considered in the instantaneous uncut chip thickness calculation and the cutter-workpiece engagement determination. The cutting force coefficient model including tool wear is established. A series of milling experiments are performed to verify the accuracy and effectiveness of the proposed cutting force model. The results show that the predicted cutting forces are in good agreement with the experimental cutting forces, and it is necessary to consider tool wear in the micro-milling force modeling. The results indicate that tool wear has a significant influence on the cutting forces and cutting force coefficients in the three directions, and the influences of tool wear on the axial cutting force and axial force coefficient are the largest, respectively. The proposed cutting force model can contribute to real-time machining process monitoring, cutting parameters optimization and ensuring machining quality.

Efficient 5-axis CNC trochoidal flank milling of 3D cavities using custom-shaped cutting tools

A novel method for trochoidal flank milling of 3D cavities bounded by free-form surfaces is proposed. Existing 3D trochoidal milling methods use on-market milling tools whose shape is typically cylindrical or conical, and is therefore not well-suited for meeting fine milling tolerances required for finishing of benchmark free-form surfaces like blades or blisks. In contrast, our variational framework incorporates the shape of the tool into the optimization cycle and looks not only for the trochoidal milling paths, but also for the shape of the tool itself. High precision quality is ensured by firstly designing flank milling paths for the side surfaces that delimit the motion space, in which the trochoidal milling paths are further computed. Additionally, the material removal rate is maximized with the cutter–workpiece engagement being constrained under a given tolerance. Our framework also supports multi-layer approach that is necessary to handle deep cavities. The ability and efficacy of the proposed method are demonstrated by several industrial benchmarks, showing that our approach meets fine machining tolerances using only a few trochoidal paths.

Cross-scale identification for friction and wear boundaries of tooth flank of high-feed milling cutter

In the milling process, under the high-efficiency and intermittent cutting loads, the instantaneous posture of the milling cutter and the instantaneous cutter-workpiece engagement are in an unstable state. It is difficult to accurately identify the friction and wear boundary of the cutter tooth flank. It has become an urgent problem to be solved in the life evaluation of milling cutters. The characteristics of the instantaneous posture variation of the milling cutter and the distribution of the thermal-stress mechanical coupling field of the flank of cutter tooth under the vibration were studied. Using the cross-scale load transfer method, the cross-scale relationship between the macro and micro friction loads on the cutter tooth flank was realized. The number of broken valence bonds, the sudden change of potential energy and the attenuation of elastic modulus of the super-cell on the flank of cutter tooth were studied. The mesoscopic scale identification method of the friction and wear boundary feature points of the tooth flank was proposed. The instantaneous and cumulative boundary distribution of friction and wear on the flank of cutter tooth were obtained, and verified by experiments.

Investigation of robotic milling chatter stability prediction under different cutter orientations by an updated full-discretization method

Chatter can easily occur during robotic milling owing to the low rigidity of serial robots. Chatter affects the quality of the workpiece surface and damages the robot equipment, which is a bottleneck that hinders the application of robotic milling. An effective way to ensure milling stability is to rationally select the cutting parameters using high-precision stability lobe diagrams (SLDs). In this study, an updated full-discretization chatter stability prediction method based on the fourth-order Hermite and third-order Newton interpolation polynomial was proposed. A dynamical model of robotic milling was established by considering the regenerative effect, cutter structure modal coupling effect, and the influence of cutter orientations. Based on the established robotic milling dynamic model and the proposed full-discretization method, SLDs related to the axial depth of cut, spindle speed, lead angle, and tilt angle were generated. The dominant influencing factors of the robotic milling chatter stability under different robot postures and cutter orientations were analysed. The robotic milling experiment results show that the dynamic characteristics of the robot are different in each direction. When the milling cutter feeding direction is parallel to the x-axis direction of the global coordinate system, the regenerative effect is dominant. When the feed direction of the milling cutter is parallel to the y-axis of the global coordinate system, the cutter structure modal coupling effect is more obvious. This is possibly because the dynamic characteristics of the tool tip change during the milling process under different robot postures. However, the milling process becomes more stable with an increase in the lead or tilt angle. This is mainly because when the cutting depth is constant, the cutter–workpiece engagement area gradually decreases with an increase in the tool angle.

Technology for programming contour milling on a CNC machine

This paper reports a new technology for designing control programs for contour milling on CNC machines. The technology enables stabilization of the cutting process along the entire contour at the optimal level by controlling the feed, which ensures an increase in productivity when meeting the requirements for restrictions. Moreover, the effectiveness of using the technology improves with an increase in the complexity of the contour by changing the curvature of the surface. A mathematical model has been built for the interaction between the cutter and workpiece in the cutting zone when machining contours with variable curvature, which makes it possible to determine the main characteristic of the cutting process – the rate of cutting the allowance. The technology involves the use of a control program in G codes designed in any CAM system. At the first stage, a shape-formation trajectory in the form of a two-dimensional digital array is derived from the program. At the second stage, the cutter workpiece engagement in the cutting area is modeled simulated while determining the main characteristic of the cutting process – an analog of the material removal rate. And at the final stage, the simulation results are used to design a new control program, also in G-codes, with a new recorded law to control the feed, which enables the stabilization of the cutting process along the entire milling path. The software for the new technology has been developed, which automatically converts the preset control program in G-codes into a two-dimensional digital array, simulates the milling process, and designs a new control program in G-codes based on its results. The results of the experimental study into the milling of the preset contour using the developed simulation program showed an increase in productivity by 1.7 times compared to the original control program, designed in a conventional CAM system

An Explicit Coupling Model for Accurate Prediction of Force-Induced Deflection in Thin-Walled Workpiece Milling

Abstract Cutting force-induced vibrations in thin-walled parts milling may cause violation of dimensional tolerance while accurate modeling of the milling error distribution is still a challenging work because of the coupling effect between the dynamic cutting forces and the resulting steady-state vibrations. It greatly increases the computational complexity to capture the true cutter–workpiece engagement with classic time domain or iteration method. This paper proposes a novel explicit model to predict the error distribution considering this coupling relationship without iterative calculation. A new cutting force model with variable coefficients with respect to the deflections is developed to describe the dynamic cutting forces. The effectiveness of the force model is verified by a group of calibration experiments. The analytical solution of the dynamic model is discussed and a semi-analytical method is constructed to predict the error distribution directly. Machined surface as well as the deformation errors are derived and thin-walled workpiece milling experiments for verification are conducted. Comparisons between simulations and experiments show that the proposed method is accurate and efficient.

Evolution of hole surface integrity in successive processing using sequential milling and laser shock peening

Part's surfaces are usually produced by successive/integration machining process and the performance of the part is directly tied to the generated surface integrity. Holes are commonly used in many critical engineering structures to connect parts, whose surface primarily characterizes a high risk of fretting or contact fatigue failure. In this paper, the evolution of metallurgical and mechanical surface integrity of Ti-6Al-4V alloy hole surface which machined using multi-step milling and successive laser shock peening (LSP) treatment was investigated. Firstly, a special workpiece with various hole surface pieces was designed and four different sequential milling processes were set to conduct the milling experiments. A comprehensive analysis of the evolution of surface roughness, microstructure, microhardness, and residual stress along the sequential processing steps was carried out. The results showed that the forms of surface integrity evolution could be classified into mono-evolution and coupling evolution, which were correlated to the combined effect of the milling parameters, cutter-workpiece engagement nature, milling sequence, milling mode, and the coolant/lubricant applied strategy. Mono-evolution was predominated in material removal sequences (milling sequences), while the coupling evolution was dependent on the radial depth of cut (DoC, ~50 μm). By comparison, coupling evolution was prominent in non-material removal related sequences (LSP treatment). Due to the conformal contact nature of tool-workpiece engagement and the flood cooling strategy, the microhardness in the subsurface layer was not significantly altered in milling sequences, except that the up-milling normally produced a surface with lower hardness and the down-milling produced almost unchanged surface hardness compared with bulk material. The residual stress was a result of the coupling effect of the residual stress field introduced in the previous and current machining sequences, whose in-depth distribution could be represented as an exponential decay function. The degree of influence of the machining sequences and their interactions on the final residual stresses could be evaluated by utilizing a set of weighting coefficients. This research indicated that understanding the effect of successive processing on the surface integrity evolution could help in planning of appropriate processes to achieve desirable surface integrity.

Analytical Method for Screw Rotor Cutting according to the Cutter Workpiece Engagement Model

Abstract: The proper screw rotor cutting process is essential to obtain a precise rotor profile; however, it is a costly and high hazard if studied in a practical method. This study introduces an analytical screw cutting method to ensure the cutting process is running well and acquire the expected rotor profile. Two distinct cutter types, a cutter with a single curve and multiple inserts cutting edge, were applied. The analytical screw cutting method was developed according to the cutter-workpiece engagement model. The result reveals that the analytical screw cutting model using various cutters can generate identical simulated profiles and close to the original rotor profile. In addition, the virtual machining verification using VERICUT software was conducted to evaluate the proposed method. Conclusively, the analytical screw cutting method is reliable and realistic to be applied in screw rotor milling.

Study on the Formation Mechanism of Surface Adhered Damage in Ball-End Milling Ti6Al4V.

Ball-end cutters are widely used for machining the parts of Ti-6Al-4V, which have the problem of poor machined surface quality due to the low cutting speed near the tool tip. In this paper, through the experiments of inclined surface machining in different feed directions, it is found that the surface adhered damages will form on the machined surface under certain tool postures. It is determined that the formation of surface adhered damage is related to the material adhesion near the cutting edge and the cutting-into/out position within the tool per-rotation cycle. In order to analyze the cutting-into/out process more clearly under different tool postures, the projection models of the cutting edge and the cutter workpiece engagement on the contact plane are established; thus, the complex geometry problem of space is transformed into that of plane. Combined with the case of cutting-into/out, chip morphology, and surface morphology, the formation mechanism of surface adhered damage is analyzed. The analysis results show that the adhered damage can increase the height parameters Sku, Sz, Sp, and Sv of surface topographies. Sz, Sp, and Sv of the normal machined surface without damage (Sku ≈ 3) are about 4–6, 2–3, and 2–3 μm, while Sz, Sp, and Sv with adhered damage (Sku > 3) can reach about 8–20, 4–14, and 3–6 μm in down-milling and 10–25, 7–18, and 3–7 μm in up-milling. The feed direction should be selected along the upper left (Q2: β ∈ [0°, 90°]) or lower left (Q3: β ∈ [90°, 180°]) to avoid surface adhered damage in the down-milling process. For up-milling, the feed direction should be selected along the upper right (Q1: β ∈ (−90°, 0°]) or upper left (Q2: β ∈ [0°, 90°)).

FRAMEWORK FOR COUPLED DIGITAL TWINS IN DIGITAL MACHINING

This paper presents a further elaboration of the use of the digital twin concept in digital machining. The main goal of the research is an attempt to combine digital representations of different objects involved in the machining process in a holistic manner. Digital twins of the in-process workpiece, cutting tool, clamping, and machine tool along with the process twin are connected in a framework in which all these elements can influence each other. The framework shows different levels of integration of different digital twins and practical recommendation on the implementation. Besides, the framework supports a simulation layer that provides data for the intensity of the interaction. Such interactions can result in, for instance, cascading calculations of cutter workpiece engagement, cutting forces, tool wear, tool deflection, chatter, and so on. Eventually, a design for a software mockup was elaborated to present the developed framework. The entire workflow to simulate part machining in such a digital representation can be used as an ultimate tool for CAM simulation and NC verification within the Zero Defect Manufacturing paradigm.

INSTANTANEOUS PARAMETER IDENTIFICATION FOR MILLING FORCE MODELS USING BAYESIAN OPTIMIZATION

The comparison between measured and simulated machining forces enables the evaluation of workpiece quality, process stability, and tool wear condition. To compute the machining forces that occur, mechanistic cutting force models are typically used. The cutting force coefficients (CFCs) of mechanistic force models are directly linked to the mechanics of chip formation and, thus, depend on the tool-workpiece combination and on the prevailing cutting conditions. CFCs are usually identified via the average cutting force identification method, which requires the execution of cutting tests under defined test conditions. Hence, determining CFCs for different cutting conditions is time-consuming and expensive. In this paper, the performance of an instantaneous CFC identification approach based on Bayesian Optimization during the machining of arbitrary workpiece geometries is studied. Bayesian Optimization is well suited for global optimization problems with computationally expensive cost functions. The simulated cutting forces are calculated using a dexel-based cutter workpiece engagement simulation and the actual cutting forces are measured during the machining process using a dynamometer. Thus, an efficient identification of CFCs could be achieved.

Surface contour error model of five-axis machining considering multifactor coupling effects

During five-axis flank milling procedure, the static deflection of workpiece and cutter creates surface errors that lead to defects in projects with strict requirements, especially in thin-walled parts industry. Focusing on the mentioned issues, the surface contour error is predicted in this paper considering the coupling between the deflection and cutting force. First, an efficient calculation method of the cutting force is presented in five-axis flank milling. This method accounts for the impact of cutter runout on cutter/workpiece engagement (CWE) and the instantaneous undeformed chip thickness (IUCT). Then, a cutter is modelled as a cantilever structure and thus an analytical solution for the deflection of the end mill can be obtained. Next, the flexible cutting force is distributed on a finite element (FE) model of workpiece, while the workpiece stiffness keeps varying with the material removal. Subsequently, a flexible iterative calculation method for achieving deflection prediction is established. Finally, the prediction model is proven by machining tests of an S-shaped specimen in which predicted values of the surface error match with the experimental results.

Machining Digital Twin using real-time model-based simulations and lookahead function for closed loop machining control

The future of machining lies in the fully autonomous machine tool. New technologies must be developed that predict, sense and action intelligent decisions autonomously. Digital twins are one component on this journey and are already having significant impact in the manufacturing industries. Despite this, the implementation of machining Digital Twins has been slow due to the computational burden of simulating cutting forces online resulting in no commercially available Digital Twin that can automatically control the machining process in real time. Addressing this problem, this research presents a machining Digital Twin capable of real-time adaptive control of intelligent machining operations. The computational bottleneck of calculating cutter workpiece engagements online has been overcome using a novel method which combines a priori calculation with real-time tool centre point position data. For the first time, a novel online machine-induced residual stress control system is presented which integrates real-time model-based simulations with online feedback for closed loop residual stress control. Autonomous Digital Twin technologies presented also include chatter prediction and control and adaptive feed rate control. The proposed machining Digital Twin system has been implemented on a large-scale CNC machine tool designed for high-speed machining of aerostructure parts. Validation case studies have been conducted and are presented for each of the machining Digital Twin applications.

ForceNet: An offline cutting force prediction model based on neuro-physical learning approach

Accurate cutting force prediction serves as an important reference to the optimization of numerically controlled machining process. Traditional cutting force modeling via theoretical cutting mechanism hampers accurate prediction for actual machining process due to its highly suppressed modeling flexibility. On the other hand, machine learning based modeling approaches demand large amount of diversified labeled samples to achieve comparable prediction results, while collecting these samples can be tedious and costly because the cutter workpiece engagement (CWE) keeps changing during actual process. This paper presents a cutting force prediction model, named ForceNet, which incorporates elementary physical priori into structured neural networks to predict cutting force for end-milling process of complex CWE. The main idea is to use grayscale images to represent CWE geometry, providing a universal input to the ForceNet. Unlike traditional deep neural networks served as an unexplainable black box, the core of the ForceNet is constructed by the vector summation of directional primitive cutting force elements, which are approximated using elementary neural networks. Preliminary results indicate that ForceNet outperformed existing methods not only with greater prediction accuracy in unseen cutting situations, but also with less training data needed thanks to its inherent neuro-physical structure.

High Definition Metrology-Based Quality Improvement of Surface Texture in Face Milling of Workpieces With Discontinuous Surfaces

AbstractIn face milling process, the quality of surface texture is vital for mechanical performance of workpieces. The quality of surface texture, especially for waviness, is directly affected by tool marks, a commonly observed phenomenon in face milling. However, appropriate approaches for evaluation and modeling of tool marks are absent to date. Limited to the resolution as well as the efficiency of conventional measurement instruments, the height data of tool marks is hard to be entirely obtained, leading to valuable information omission. Besides, most existing models of tool marks are established for general workpieces with regular geometry and continuous surfaces. Since the cutter-workpiece engagement mode has a significant impact on the generation of tool marks, current models could be inaccurate or invalid when dealing with workpieces with discontinuous surfaces. To overcome this shortage, a novel approach is proposed in this research, aimed at quality improvement of surface texture in face milling of workpieces with discontinuous surfaces. First, the evaluation indexes for tool marks are defined based on the recently developed high definition metrology (HDM). Second, the physical modeling of tool marks is presented, taking the face milling mechanism into account. Third, the physical-informed optimization model is developed to search for the optimal processing parameters for surface quality improvement. At last, the effectiveness of the proposed approach is verified by a face milling experiment on the engine blocks.

High efficiency calculation of cutter-workpiece engagement in five-axis milling using distance fields and envelope theory

Cutter-workpiece engagement (CWE) is fundamental to the process mechanics and dynamics modeling. Due to the variation of the feed directions in five-axis milling of freeform surfaces, the instantaneous CWE is complex and time-varying. Therefore, for the industrial part milling process which contains tremendous cutter locations, how to calculate the CWE efficiently and accurately remains a challenge. In this paper, a high efficiency method for CWE calculation in five-axis milling based on the distance field and envelope theory is proposed. In the geometry modeling and milling simulation, workpiece surfaces are modeled using sampled distance fields stored in a well-designed octree data structure for efficient memory usage. The inverted trajectory method is used to calculate the tool swept volume, which is subtracted from the in-process workpiece by performing three-stage intersection detection and accelerated Boolean operation. As for the CWE extraction at a specific cutter location, the feasible contact arcs derived from the cutter surfaces based on the envelop theory are used as geometry primitives to intersect the in-process workpiece. A new segment-evaluation algorithm is offered to find the intersection points of each feasible contact arc with the workpiece surfaces. Finally, the CWE diagram is obtained by combining the entry and exit immersion angles of the engagement arcs at each axis height. The feasibility of the proposed method for industrial applications is evidenced by two case studies conducted on a developed virtual machining simulator. The results of the comparison with the B-rep based method indicate that the proposed method is more efficient while providing good accuracy.

Modified cutting force prediction model considering the true trajectory of cutting edge and in-process workpiece geometry in ball-end milling operation

Cutting force prediction is very important for optimizing machining parameters ahead of the costly physical test. Ball-end milling operation is widely used for machining sculptured surface. Mechanistic approach can precisely predict elemental cutting force at each cutting element and integrate them into the cutter tooth with high fidelity to predict the cutting force for ball-end milling operation. However, the intersection between the cutting tool and workpiece could be complicated due to the trochoid motion trajectory of cutting edge and constantly changing workpiece geometry, making it difficult to determine the cutter-workpiece engagement (CWE) and undeformed chip thickness (UCT). In this present research, a modified cutting force prediction model was developed with considering the true trajectory of cutting edge and in-process workpiece geometry in ball-end milling operation. First, a triangular mesh model of the in-process workpiece surface was developed, and its mesh points were continuously updated by the intersection between the vertical reference line of the selected mesh point and the motion trajectory of cutting edge. Secondly, the UCT was calculated directly using the linear distance between a selected point on the cutting edge and the intersection between the radial reference line of the selected point and the triangular mesh of the in-process workpiece surface. Meanwhile, the CWE was expressed as a step function of UCT. Thirdly, a modified mechanistic approach was established by incorporation into the developed UCT and CWE models. The cutting force of ball-end milling operation was predicted with mechanistic approaches. Finally, ball-end milling experiments of AISI P20 steel were carried out for calibrating cutting force coefficients and validating cutting force model. The relative error between the predicted and measured cutting force is less than 15%, which indicates the predicted cutting force is in good agreement with measured cutting force. The works presented in this paper are one important step for optimizing machining parameters and compensating cutting force induced form error, which could improve the surface accuracy and machining efficiency.

State dependent regenerative stability and surface location error in peripheral milling of thin-walled parts

Chatter avoidance and error control are the core issues accompanying milling processes of thin-walled parts. Owing to the high flexibility of workpiece, the cutting vibrations can easily reach dozens of micrometers and become comparable to the nominal chip thickness. However, the classic dynamic models usually neglect the influence of system state on regenerative stability and surface location error (SLE), which consequently reduces the prediction accuracy. In this paper, the coupling relationships between cutter-workpiece engagement, time delay and system state are modeled by means of analyzing the true teeth trajectories that are composed of tool rotation, feed movement and cutting vibrations. The resultant dynamic model is a state dependent delay differential equation, which is capable of accounting for the fly-over and multi-regeneration nonlinear phenomena too. Afterwards, an efficient numerical algorithm is proposed to accurately compute the dynamic responses. By contrast to classic time domain simulation techniques, the proposed algorithm uses discrete root finding scheme to determine the state dependent time delay and the state dependent cutter-workpiece engagement, which ensures its high computational efficiency. Based on the proposed dynamic model and numerical algorithm, the stability limits and SLE are finally obtained, and experimentally validated on two thin-walled plates using two variable pitch tools. Theoretical comparison and experimental results reveal that the proposed state dependent dynamic model successfully predicts the milling stability and SLE while the classic model fails. The state dependency of regenerative stability and SLE is further investigated and explained in detail.

Chip geometry and cutting force prediction in gear hobbing

This paper presents a tri-dexel geometric engine integrated simulation model for the gear hobbing operation. The process kinematics are modeled and validated using CNC signals from a Liebherr LC500 hobbing machine. Workpiece geometry updating and cutter-workpiece engagement (CWE) calculations are efficiently realized in the tri-dexel engine. 3D force contributions at discretized nodes along the hob's cutting edges are computed considering the localized principal cutting directions, and rake and inclination angles. To measure cutting forces, a rotary dynamometer is successfully adapted and used alongside a Kalman filter to compensate for structural dynamics. The predicted forces agree well with their experimental counterparts.

Nonlinear process damping identification using finite amplitude stability and the influence analysis on five-axis milling stability

Complex aerospace parts with difficult-to-cut materials AerMet100 etc. should be processed by five-axis milling at low spindle speed, in which the process damping cannot be ignored in stability analysis. Based on the established nonlinear process damping and relevant equivalent process damping coefficient model, a 3D stability lobe diagram (SLD) considering the finite amplitude stability is proposed. A novel indentation coefficient identification method of the nonlinear process damping is proposed by using the finite amplitude stability region, which avoiding the experiment identification of accurate critical cutting depth in inverse stability solution method, and a turning experiment is designed to identify the indentation coefficient of AerMet100 materials. Due to the distribution of process damping force is varied with the cutter-workpiece engagement (CWE) which can be changed by tool orientation, thus the critical cutting depth with considering or not the process damping under different tool orientation are compared and analyzed. The results indicate that critical cutting depth magnitude distribution can be affected by the process damping, and the percentage increase in cutting depth has significant relationship with tool orientation and the frequency response function (FRF). Finally, the influence rule of tool orientation on stability boundary is concluded and the optimization criteria is given.