5-axis Machine Tool Research Articles

A new method to identify the position-independent geometric errors in the rotary axes of five-axis machine tools

Position-independent geometric errors (PIGEs), caused by assembly imperfection, affect the machine tool's accuracy. Moreover, the rotary axes of five-axis machine tools introduce more PIGEs during parts machining, hence, the need to identify them to improve the accuracy. However, the identification of rotary axes centerlines and the use of extension bars, using double ball bar (DBB), introduce additional setup errors and uncertainties during error measurements and sometimes make the process tedious. This work proposes a new method to identify the eight (8) PIGEs in the rotary axes of a five-axis machine tool with a tilting table. The homogeneous transformation matrix (HTM) was used to construct the relative motion matrix to the established coordinate systems and then deduced the error model. Three different DBB installation setups were employed for the identification of the PIGEs for both rotary axes using the planar test, the recorded DBB length data was substituted into the model to obtain the PIGEs. The results show that the proposed PIGEs identification method is accurate and can improve the accuracy of the five-axis machine tool effectively, and this method has some advantages over some existing methods of identification in terms of simplicity which shows a good improvement in the manufacturing industry.

Intelligent feedrate optimization using a physics-based and data-driven digital twin

Intelligent manufacturing machines envisioned for the future must be able to autonomously select process parameters that maximize their speed while adhering to quality specifications. Accordingly, this paper proposes a framework and methodology for using a physics-based and data-driven digital twin of a feed drive to maximize feedrate while respecting kinematic and contour error limits. To correct for inaccuracies introduced by unmodeled dynamics and disturbances, the data-driven model is updated on-the-fly using sensor feedback. Experiments on a 3-axis CNC machine tool prototype are used to demonstrate up to 35% cycle time reduction without violating error tolerances compared to the status quo.

A novel surface residual stress monitoring method based on the power consumption of machine tool: A case study in 5-axis machining

The machining-induced residual stress significantly influences the service performance of machined parts and should be well monitored. However, the direct measurement method is time-consuming and only can be conducted after machining. Meanwhile, the existing prediction method rarely considers the effects of real-time factors on the machining parameters and cannot meet the requirement of online residual stress monitoring. Therefore, a novel surface residual stress monitoring method is proposed based on the easily measured online factor (power consumption of the 5-axis machine tool is used in the paper). Firstly, the power consumption of the machine tool (Pt) is used to model the mean effective cutting power (Pe¯). Secondly, the relationship between the surface residual stress in the feed direction (Rsx) and Pe¯ is established. Thirdly, Rsx is predicted based on Pt by combining these two models. Finally, a novel surface residual stress monitoring method based on Pt is proposed. The effectiveness of the proposed method is validated by various experiments, and the mean prediction error rate is only 9.5 %. From the case study, when the power consumption of machine power increases at a fixed spindle speed, Rsx changes from tensile stress to compressive stress. It provides a new method and platform for controlling the surface residual stress and greatly benefits the high-performance manufacturing of complex parts.

Rectilinear strain sensing framework for real time compensation of structural distortions in precision machinery

Precision machinery such as machine tools use heavy duty structural elements to provide high accuracy and repeatability. However, external forces and thermal effects can still cause significant errors. Machine builders put significant emphasis on good design for error avoidance and more recently, utilise software-based error compensation methods to further improve performance. For geometric errors which result from build tolerances, and which normally only vary slowly over time, most Numerical Control systems provide functionality for pre-calibrated error compensation. For compensation of thermal errors, temperature sensors are often used to provide data for a model which calculates the effect of the temperature field on the machine structure. Although this method is widely researched, there is often significant residual error due the time-variant non-linear relationship between temperature and the error between the tool and workpiece. This may be exacerbated by introducing multi-material structural elements to reduce weight. Direct measurement and combining temperature with direct measurement can enable more precise modelling but can add significant cost of additional sensors. In this research a direct measurement method is applied using a series of short-range, ultra-low-cost displacement sensors, exploiting a particular arrangement of compact slotted photo-microsensors. These are organised in a novel rectilinear framework to enable detection of the bending of a machine tool structure. The design provides high resolution measurement of strain over arbitrary lengths and cost-effective hardware for permanently embedding on a machine. The system was applied to the ram of a high precision 3-axis machine tool and used to compensate the thermal error caused by running the integrated high-speed spindle. The residual error was reduced from 10 to 4 µm, even reducing the magnitude of the effect of the chiller cycles.

THERMO-MECHANICAL ANALYSIS OF A MACHINE TOOL WITH HYDROSTATIC BEARINGS

Thermal behaviour is a key factor affecting the operatingstatus of high performance hydrostatic (HS) bearings of rotational axes of machine tools (MT). This paper introduces a novel model developed for transient thermo mechanical analysis of hydrostatic guideways with a surrounding MT structure. In contrast to common approaches to HS bearing design, which only consider the static load carrying capacity, the new model enables detailed prediction of the bearing thermal stability under various operating conditions. An analytical description of the HS bearing heat generation coupled with a MT finite element (FE) model enables calculation of heat transfer, conduction and especially thermal deformations of the entire MT structure affecting the working accuracy of the machine tool.

Shaping of the Fresnel lens array on roller molds by 6-axis diamond machining

The Fresnel lens arrays are rapidly developing with the increasing demand for better optical performances and capabilities. For the roll-to-roll embossing of optical films, direct diamond machining of the Fresnel lenses on roller molds has been realized by installing an additional goniometer on the 5-axis ultra-precision machine tool in the previous study. However, this method owns two shortcomings, i.e., the communication delay between the machine tool and the goniometer and the poor positioning accuracy of the goniometer. In this paper, a 6-axis diamond shaping method is proposed to fabricate the Fresnel lens array on the roller periphery by utilizing a commercial 6-axis ultra-precision machine tool. It is ensured that the side cutting edge of the diamond tool matches the Fresnel lenses profiles during shaping. Also, the tool rake face is always perpendicular to both the roller tangent plane at the cutter location point and the cutting velocity relative to the roller via the synchronized rotations of the A-, B- and C-axes to avoid the tool–workpiece interference. The process to calibrate installation errors is introduced and utilized. The tool path is generated according to the cutting tool geometry, the lens parameters and the machine tool configuration. Experiments are carried out by machining the designed Fresnel lens array on a roller mold, which consists of lenses with different feature heights. The surface qualities of the lens arrays are evaluated and the influence of the block time to run the CNC code are also analyzed. The experimental results verify that the proposed method is effective and flexible for machining of the Fresnel lens array on roller molds.

Spatial angle error equivalence principle and on-machine detection method for 5-axis machine tools

Spatial angle error equivalence principle and on-machine detection method for 5-axis machine tools

A positioning correction method for turbine blade film cooling holes

It is significant to improve the machining accuracy of film cooling holes on aero-engine turbine blades. This paper presents a method to correct the position of film cooling holes on turbine blades. In this method, the pre-positioning algorithm and the precise positioning algorithm are proposed. The pre-positioning algorithm introduces the blade structure information. In the precise positioning algorithm, 3D coordinate transformation, ∠B and ∠C of 5-axis machine tool updating, iteration points creating based on the normal vector are designed. The operation of the gas film cooling hole correcting by the method is given. Experiment shows that, after 7 iterations, the error is reduced to 0.0344mm, achieving high-precision positioning of turbine blades. Furthermore, the coordinates are corrected to realize the high-precision machining of the film cooling holes, which can improve the cooling performance of turbine blades.

Based on NXUG10 Research on automatic programming and simulation machining of integral split impeller

Taking the programming and simulation processing of integral split impeller in nxug10.0 software as an example, this paper introduces a method that can realize the automatic programming of parts and components to call out five axis machine tool for simulation processing in ug10.0 software. This paper introduces the whole process of ug10.0 impeller machining module from automatic programming parameter setting of integral split impeller to generating tool path files for machining integral split impeller parts and calling out five axis machine tool for simulation machining. The correctness of the automatic programming program is verified. The phenomenon of Tool Collision and interference in the machining process is avoided, and the machining efficiency of the impeller is greatly improved.

State identification of a 5-axis ultra-precision CNC machine tool using energy consumption data assisted by multi-output densely connected 1D-CNN model

State identification of a 5-axis ultra-precision CNC machine tool using energy consumption data assisted by multi-output densely connected 1D-CNN model

NEW DEVICE FOR RAPID MEASUREMENT OF MACHINE TOOL GEOMETRIC ERRORS

Control systems of modern machine tools are equipped with a number of functions for volumetric accuracy enhancement. These functions can compensate for all the geometric errors of the axes, which are characterized by 21 errors for a 3-axis machine tool. Compensation data are stored in compensation tables and the control system calculates actual compensation based on these tables and actual machine tool position. Geometric errors are measured within the machine tool maintenance plan and it presents a time-consuming process. Measurement is mainly based on interferometric devices, where the precise setup of laser source and detector is challenging. This article introduces an original system for automatic interferometer set up to speed up the measurement of geometric errors. The system is designed for the interferometer Renishaw XM-60, which simultaneously measures all 6 degrees of freedom. The developed control software identifies interferometer position and transforms the measured data into a machine coordinate system. Numerical simulation verified the proposed solution.

An action-oriented teaching approach for intelligent and energy efficient precision manufacturing

Thermal errors of machine tools are a major contributor to inaccuracies of produced workpieces. Especially, the reduction of thermal errors without increasing the energy consumption of the machine tool and the shop floor due to exact air conditioning has a great social, scientific, and industrial relevance. Therefore, the Institute of Machine Tools and Manufacturing (IWF) at ETH Zürich set up a series of three lab courses to increase the awareness of undergraduate students on this important topic. In the first lab course the students elaborate how the carbon footprint of machine tools can be minimized over the whole live cycle including the manufactured products. Specifically, the students measure the energy demand and analyze the energy efficiency of the most important components of a 5-axis machine tool in different operating conditions. The second lab course focuses on the thermal chain of causes, which describes the physical fundamentals leading to the thermal deformations of machine tools. Temperature and displacement measurements as well as finite-element simulations of a purpose-built test bench visualize the characteristics of the thermal chain of causes. The third lab course completes the topic by dealing with model-based thermal compensation strategies, which enables a shift from resource-based towards intelligence-based reduction strategies for thermal errors. The students evaluate the thermal behaviour of a 5-axis machine tool with an on-machine measurement cycle and learn how to create physical and data-based thermal error compensation models.

A four parallel laser-based simultaneous measurement method for 6-degrees-of-freedom errors of rigid body with translational motion.

The measurement of six-degrees-of-freedom (6-DOF) errors of rigid bodies can show the real and accurate spatial pose of those rigid bodies. It plays a major role in precision calibration, spacecraft docking, machining, assembly, etc. In this paper, a four parallel laser-based simultaneous measurement (FPL-SM) method is proposed for measuring 6-DOF errors of rigid bodies with translational motion. First, a FPL-SM device is introduced. Its four laser heads form a rectangle, which is perpendicular to the movement direction of the measured linear displacement. Second, identification formulas for all geometrical errors in rigid bodies with translational motion are presented based on the relative positions of the four lasers. Based on the readings of the four lasers, angular errors and corresponding straightness errors are calculated for the direction of motion around the other two linear motions. As the two parallel sides of the rectangle are in different planes, the straightness errors of the two planes are different. The rolling angular error in the direction is expressed as the difference between the straightness errors of the two planes divided by the distance between the two planes. Six fundamental errors for rigid bodies with translational motion are obtained by four lasers in a single setting of the device. For multiple rigid bodies with mutually perpendicular translational motion, the squareness error is calculated by fitting to the actual direction of motion. Finally, experiments were carried out on the SmartCNC_DRDT five-axis machine tool and 21 geometric errors were determined for three translational axes. Error compensation was carried out using the generated machine tool geometric error data to verify the effectiveness of the proposed FPL-SM method. In addition, geometric errors and thermal errors of the Z axis of the GTI-2740 machine tool are measured based on the FPL-SM method.

All position-independent and position-dependent geometric error measurement and identification of the precision of a horizontal boring machine tool

Geometric error is the main obstacle that affects the quasi-static accuracy of horizontal boring machine tools. To improve quasi-static performance, the error terms of all position-independent geometric errors (PIGEs) and position-dependent geometric errors (PDGEs) must be measured and identified precisely. This study proposes a novel method for measuring and identifying the above two types of geometric errors based on double ballbar for the rotary axis. The error terms of the linear axis are identified from the measurement model based on the exponential product method and a preset measure trajectory, and the measure coordinate system is combined with the reference coordinate to lower the uncertainty in the identification accuracy. Then, the elastic net method and improved weight function IGG3-LTS method are established to identify the PIGEs and PDGEs of the rotary and linear axes, respectively. This method has the advantage that measurement with the built-in sensor method synchronously does not interfere with the running state of the machine tool, and neither the inaccuracy of reference-frame misalignment nor installation error of the measuring instrument affects the geometric error identification results of the linear axis. Moreover, all PIGEs and PDGEs, particular to the rotary axis of the horizontal boring machine tool, are determined accurately. The measurement and identification strategy is demonstrated by experimental comparison on a four-axis precision horizontal boring machine tool. The minimum compensation rate of each precision index of the test specimen is 40.0%, the average compensation rate is 52.7%, and the maximum compensation rate is 62.5%.

Geometric error identification of five-axis machine tools using dual quaternion

A universal identification method for position independent geometric errors (PIGEs) of dual rotary axes of five-axis machine tools with arbitrary rotary axis position structures is proposed based on the unit dual quaternion (UDQ). The PIGEs of translational/rotary axes are redefined based on UDQ transformation, which effectively reduces the transformation parameters and avoids the unitization process of UDQ compared with the existing UDQ kinematics model. Based on the redefined PIGEs, a kinematic error model of a five-axis machine tool is established for error identification. Taking the cradle-type five-axis machine too with non-intersecting rotary axes as the research objective, a novel method for identifying PIGEs through the synchronous motion of dual rotary axes using a double ball bar (DBB) is proposed. Compared with BK1 and BK2 in ISO10791-6 and other existing methods, the advantage of the proposed method is that it can greatly reduce the complexity of the experiment and the operation steps by directly constructing the relative kinematic relationship between the tool and the workpiece based on the error model. Only one installation and one measurement trajectory are needed to simultaneously identify the eight PIGEs of the dual rotary axes. In addition, a trajectory equalization algorithm is proposed to effectively solve the asynchronous problem of motion and data sampling in DBB trajectory operation. By combining the simplified error model with the sampling data of DBB, the pseudo-inverse matrix is used for decoupling. The effectiveness of the proposed method is verified by DBB compensation comparison experiment. The proposed error identification method can be applied to other types of five-axis machine tools with a few changes in the configural parameters, which is ideal for periodic checks and calibration to ensure the machining accuracy.

Posture Evaluation Based on Forward Kinematics and Inverse Kinematics of Parallel Link Type Machine Tool

Parallel mechanisms with multiple links have been expected to be used in machining because they are higher in rigidity, accuracy, and output power than series mechanisms, such as industrial robots. However, unlike conventional machine tools, which consist of linear and rotary axes, parallel mechanisms have a large number of error factors. In the parallel link mechanism, there is no guide surface that physically guarantees linearity, and all accuracy is determined by the operating performance of the composite axes. This makes it difficult to identify any error factors. Therefore, a kinematics model is devised, and the behavior of the tool tip is checked by inputting the encoder information during the actual operation of a specific axis. Based on the results, we evaluate the machining characteristics of the target machine tool. The target machine tool in this study is a 5-axis machine tool that combines a 3-DOF parallel mechanism consisting of three linear motion axes and a 2-DOF serial mechanism consisting of two rotary axes. In our previous research, we tried to build a forward kinematics model. Although its prediction accuracy was insufficient, it was possible to actually identify the cause of the defect in the quality of the machined surface using the servo position information of the kinematics machine. However, we have not been able to construct an inverse kinematics model that is suitable for calculating the correction position command value to improve the quality of the machined surface. In this study, based on the shape creation theory, we devise and evaluate the kinematics model of a robotic machine tool that has a parallel mechanism. As a result of comparing the kinematics model with the 3D-CAD model in order to evaluate the accuracy of the former, it was confirmed that the proposed method has high simulation accuracy. Then, machining tests were carried out to evaluate the machining accuracy by measuring, based on proposed kinematics model, the machined surfaces in order to identify the mechanism that affects the texture of the machined surface. In addition, we performed a circle interpolation to confirm the effects of reversing the motion of each drive axis on the behavior of the tool tip. As a result, it is considered that the linear motion axis has a large effect on the behavior of the tool tip on the quadrant glitch of each drive axis. It was also found that the effects of the 1st- and 3rd-axes on the behavior of the tool tip are different from those of the 2nd-axis.

A novel contour error evaluation index of the five-axis machine tools

The accuracy of high speed five-axis machine tool is mainly determined by the contour accuracy of machine tools. The contour accuracy evaluation and improvement of 5-axis machine tools have always been concerned. In order to simplify the calculation of five-axis contour error considering the synchronization between tool tip position and tool orientation, a novel five-axis contour evaluation index TCCE(Two-point Cutter location Contour Error) is proposed in this paper, which is based on the tool axis trajectory surface. The calculating method of the proposed index by NC servo encoder input from 5-axis machine tools is introduced. Finally, the experiment is performed to evaluate the trajectory accuracy and servo matching performance of the machine tool with the proposed contour error evaluation index and the calculating method.

Intelligent Operation Monitoring of an Ultra-Precision CNC Machine Tool Using Energy Data

Ultra-precision CNC machine tools play a significant role in the machining of precision dies and molds, optics, consumer electronics, etc., Due to the nature of ultra-precision machining, a subtle change in process condition, machine anomalies, etc. may significantly influence the machining outcome. Hence, continuous monitoring of the equipment’s operation is required to better understand the variations associated with the process and the machine. The conventional monitoring platform requires comprehensive data analysis using multiple sensors, and controller data to detect, diagnose, and prognose machine and process conditions. This increases the cost and complexity of installing a monitoring platform. The energy consumption data contains valuable information that could be potentially used to identify machine and process variations. The information can also be used to develop potential energy-saving strategies in an effort towards Green Manufacturing. This paper proposes an intelligent energy monitoring method using a 1-dimensional convolutional neural network (1D-CNN) to effortlessly and accurately obtain the working status information of the machine with minimal retrofitting. The 1D-CNN uses the energy consumption data to determine the equipment’s operation status by identifying the working components and the feed rate of the moving axis. The hyper-parameters of the developed model were optimized to improve the prediction accuracy. The paper also compares different Deep Learning and Machine Learning algorithms to gauge their effective performance in this application. Finally, the model with the highest accuracy was validated on a 5-axis ultra-precision CNC machine tool. Results show that 1D-CNN performs better than multi-layer neural networks and machine learning algorithms in processing time-series datasets. The classification accuracy of 1D-CNN on the detection of operation status and feed rate of each axis can reach 95.7 and 91.4%, respectively. Further studies are currently in progress to improve prediction accuracy of the model, and to detect subtle changes in energy consumption which would enable identification of the machine and process anomalies.

Machining cycle time prediction: Data-driven modelling of machine tool feedrate behavior with neural networks

Accurate prediction of machining cycle times is important in the manufacturing industry. Usually, Computer-Aided Manufacturing (CAM) software estimates the machining times using the commanded feedrate from the toolpath file using basic kinematic settings. Typically, the methods do not account for toolpath geometry or toolpath tolerance and therefore underestimate the machining cycle times considerably. Removing the need for machine-specific knowledge, this paper presents a data-driven feedrate and machining cycle time prediction method by building a neural network model for each machine tool axis. In this study, datasets composed of the commanded feedrate, nominal acceleration, toolpath geometry and the measured feedrate were used to train a neural network model. Validation trials using a representative industrial thin-wall structure component on a commercial machining center showed that this method estimated the machining time with more than 90% accuracy. This method showed that neural network models have the capability to learn the behavior of a complex machine tool system and predict cycle times. Further integration of the methods will be critical in the implantation of digital twins in Industry 4.0.

Prediction of the Comprehensive Error Field in the Machining Space of the Five-Axis Machine Tool Based on the “S”-Shaped Specimen Family

In order to quickly and accurately predict the spatial geometric error field of the five-axis machine tool processing, a method for predicting the comprehensive error field of the five-axis machine tool processing space based on the “S”-shaped specimen family is studied. Firstly, for the five-axis CNC machine tool in the form of A-C dual turntable, the geometric error model of the rotating axis is established based on the multi-body dynamics theory; the error mapping relationship between the processing technology system and the workpiece is analyzed based on the “S”-shaped specimen family, and the identification of 12 geometric errors of the two rotating shafts. Then, the error value of the sampling point is measured based on the “S”-shaped test piece in machine contact, and the double-circle center coordinate value is determined according to the curvature of the measured wire of the test piece, in order to identify the geometric errors of the two rotation axes of the five-axis machine tool. Finally, based on the prediction method, the comprehensive error field of the five-axis CNC machine tool processing space is analyzed. Compared with other geometric error identification methods, the measurement accuracy of this method meets the processing requirements and can further evaluate the comprehensive performance of the machine tool.