On-machine Measurement System Research Articles

A novel pose calibration method for laser displacement sensor in the five-axis on-machine measurement system

The five-axis on-machine measurement system, equipped with a laser displacement sensor, offers an effective approach for conducting on-site inspections of freeform surface parts. It is crucial to address the calibration error pertaining to the sensor’s pose, encompassing both the beam direction and the zero position, as it directly impacts the measurement accuracy. This paper presents a new approach for the calibration of a laser displacement sensor’s pose, which is mounted on the spindle of a five-axis gantry machine tool. The proposed method utilizes measurements taken from multiple angles of a standard ball. Through the utilization of spherical constraints and coordinate translation transformation, the Levenberg-Marquardt iteration method is employed to derive the sensor’s beam direction, while the least square method is used to determine the sensor’s zero position. Applying this proposed method, the maximum error in the distance between the centers of the standard double ball is below 0.008 mm, which can meet the precision requirements of on-site inspection of freeform surface parts.

On-machine measurement and compensation of thin-walled surface

On-machine measurement technology is considered as a key technology for realizing closed-loop feedback control in intelligent manufacturing due to the reduction of the transfer process. However, the complexity of the machine tool process system introduces some uncertainty into the accuracy of on-machine measurement, which severely limits the application in the actual industrial field. To overcome the shortcomings of the existing uncertainty, an inspection framework for on-machine measurement of thin-walled surface is proposed. Firstly, a low-cost wireless on-machine measurement system based on potential signals is established and integrated into a manufacturing process line for automatic sampling. Then, the similarity of momentum conservation is introduced into sampling planning, and an adaptive sampling model based on momentum conservation and multi-objective particle swarm optimizer is proposed. Finally, a stacked deep learning model under the vertical inspection direction is proposed to improve the inspection accuracy by correcting the sampling data. Compared with existing sampling methods, the proposed model is similar to an attention mechanism that enables adaptive enhancement of profile features. The inspection performance by data correction is improved by about 16.14% in the mean inspection error. Simulations and experiments show that the proposed method has great advantages in terms of efficiency and robustness, which can provide a theoretical reference for adaptive toolpath correction for thin-walled surfaces.

An on-machine measurement technique with sub-micron accuracy on a low-precision grinding machine tool

The on-machine measurement system can effectively improve the machining efficiency and accuracy of the optics in the grinding stage, but the common grinding machine has large geometric errors and ambient temperature errors, which are the key factors restricting the accuracy of on-machine measurement. In this paper, a high-precision error separation technique including geometric error separation and temperature error separation is proposed to achieve sub-micron level measurement accuracy in the grinding stage. The on-machine measurement system is built based on the color confocal sensor. A sensitive error model is established based on Abbe's principle and multi-body dynamics, and the geometric error separation with zero Abbe's error is achieved by a high-precision reference mirror. Then the temperature error influence model is established based on the scanning path, and the temperature error separation method based on the auxiliary profile line is proposed according to the temperature error model. Finally, it is verified through experiments that after error separation, the measurement accuracy of the on-machine measurement system is improved from tens of micron to sub-micron, which exceeds the measurement accuracy of ordinary coordinate measurement machines (CMMs), and can effectively improve the machining accuracy and efficiency in the grinding stage.

Special Issue on On-Machine and In-Process Measurement for Smart and Precision Manufacturing

The Internet of Things is playing an important role, organizing all things that use data and connecting them to the Internet. It has been made possible by the rapid progress in smart and real-time measurement technologies, the miniaturization and speeding up of sensor technologies as well as intelligent data processors, and by the spread of cloud technology, which accumulates huge amounts of data. To establish smart and precision manufacturing, not only the improvement of conventional ultraprecision machining techniques but also the development of the novel, high-performance machining techniques has been made. On-machine and in-process measurement are gaining in importance for emerging machining technologies as well as conventional ones. Advanced techniques of machining and metrology as well as feedback for compensation manufacturing have been required for plasticity to on-machine and in-process conditions. This special issue focuses on metrology and manufacturing measurement and instrumentation for the progress of state-of-the-art on-machine and in-process measurement systems and sensor technologies. It consists of contributions related to, but not limited to, the following topics: - On-machine, in-process measurement and process monitoring - Practical application of on-machine, in-process measurement - Machine tool metrology - Intelligent micro- and nano-metrology - Multi-sensor fusion and multi-sensor cooperation - Form and dimensional measurement and instrumentation - 3D-surface texture and its micro-characteristics - Machine learning, AI aided measurement We would like to sincerely thank all the authors for their contributions, and we sincerely hope that the papers in this special issue further contribute to the development of our future society from a new horizon of metrology.

Online monitoring method of non-cylindrical wheel wear for gear grinding based on dynamic force model

Traditional monitoring methods of grinding wheel wear mainly take on-machine measurement systems or black-box algorithms. The first method has poor real-time performance for it can only be implemented after machining, making it difficult to adjust grinding processes in time. The second method has not revealed the mechanism of wear, resulting in poor model accuracy and flexibility. Besides, previous models are mainly for cylindrical wheels in surface grinding, while the properties of non-cylindrical wheel wear for gear grinding are different. To address this issue, a novel online monitoring method of non-cylindrical wheel wear for gear grinding is proposed. Firstly, a new parameter is defined based on grain height variation to describe the non-cylindrical wheel wear condition, avoiding the problem of underestimating the actual results due to a small measurement range. Then, a theoretical model for dynamic grinding forces is established considering more grain parameters and more complicated and realistic shape, so that on the basis of that model, the online monitoring method for wheel wear is proposed. Finally, experiments under different grinding conditions are conducted to verify the proposed models. The average calculation error of the grinding force model in different grinding parameters is 6.67%, and the maximum prediction error of the monitoring method under different wheel wear conditions is 8.2%.

Study on the Method of Tilt Error Compensation for a Laser On-machine Measurement System

This paper proposes a spindle vector compensation method based on laser triangulation for the inclination measurement error of a laser on-machine measurement system. By using the fixed relationship between the calibration vector and the spindle vector, the laser’s axis vector and the surface’s normal vector coincide in the actual measurement by adjusting the spindle vector. The tilt measurement and calculation errors are compensated simultaneously using this spindle vector compensation method.

Uncertainty evaluation of an on-machine chromatic confocal measurement system

On-machine optical measurement receives growing attention as a viable quality assurance technique to satisfy the increasingly critical requirements for dimensional accuracy and surface finish upon precision components. It preserves the temporal and spatial consistency between manufacturing and measurement activities, allowing for a substantial productivity improvement and a great opportunity for on-line quality control. However, additional uncertainty can be introduced under the harsh on-machine measuring environment degrading the measurement quality. The explicit research on the on-machine measurement uncertainty is therefore essential but rarely carried out to date. To fill this gap, this paper presents the uncertainty investigation of an on-machine areal measuring instrument based on the chromatic confocal scanning principle. The vibration transmitted from neighboring machine tools is found to strengthen the drive vibration and to cause an overestimation of the roughness in the static noise test. The motion-induced disturbance and subdivisional error are recognized as artefacts in the flatness map influencing the evaluation of the flatness deviation, though they can be attenuated by the notch filter. Based on further evaluation on the roughness parameters, the uncertainty contributions from the noise and the corrected flatness deviation are found to be 18nm and 50nm respectively in Sz for the rough surface (pulse energy=250μJ). An uncertainty budget concerning all these influencing factors enables a systematic uncertainty quantification for the on-machine measurement.

Chromatic confocal sensor-based on-machine measurement for microstructured optical surfaces featuring a self-aligned spiral center.

Chromatic confocal sensor-based on-machine measurement is effective for identifying and compensating for form errors of the ultra-precisely machined components. In this study, an on-machine measurement system was developed for an ultra-precision diamond turning machine to generate microstructured optical surfaces, for which the sensor probe adopts a uniform spiral scanning motion. To avoid the tedious spiral center alignment, a self-alignment method was proposed without additional equipment or artefact, which identified the deviation of the optical axis to the spindle axis by matching the measured surface points and the designed surface. The feasibility of the proposed method was demonstrated by numerical simulation with full consideration of noises and system dynamics. Practically, taking a typical microstructured surface as an example, the on-machine measured points were reconstructed after calibrating the alignment deviation, which was then verified by off-machine white light interferometry measurement. Avoiding tedious operations and special artefacts may significantly simplify the on-machine measurement process, thereby greatly improving the efficiency and flexibility for the measurement.

Contact on-machine measurement probe error correction method for optical aspheric surface ultraprecision machining

Optical aspheric ultraprecision machining requires nanometer-scale on-machine measurement (OMM) techniques, and small probe errors in the contact OMM process can seriously affect the OMM accuracy, thereby reducing machining accuracy. Thus, a master ball-based probe radius error and probe profile error correction method is proposed to analyze the effects of probe radius error and probe profile error on OMM results while ensuring accurate probe alignment to establish an identification and correction model for probe radius error and probe profile error. OMM probe error correction measurement and error compensation machining experiments were conducted to verify the effectiveness of the probe error correction method. After the probe profile error correction measurement, the probe measurement error was changed from 0.436 μm to 0.023 μm. Compared with the uncorrected probe error and the probe radius error correction compensation machining results, the accuracy of the compensation machining after the probe profile error correction compensation was improved by 43 % and 41 %, respectively. Results show that this OMM system probe error correction method is effective in improving OMM accuracy.

Integrated profile and thickness error compensation for curved part based on on-machine measurement

Curved parts are widely used in aerospace, automotive and energy industries. The profile and thickness accuracy are both critical to some curved parts such as hollow blades. Improving the profile accuracy while ignoring the wall thickness error will reduce the qualified rate of these curved parts, and vice versa. This paper proposes a comprehensive compensation method with constraints of both profile and thickness tolerances for the machining of curved parts. The actual geometry and wall thickness of the parts are obtained by on-machine measurement system after rough machining. Both touch-trigger probe and thickness gage are used to reconstruct the actual outer and inner surface of the workpiece. Then, the comprehensive constraint considering both profile and thickness constraints is established based on the reconstructed workpiece geometry. With the comprehensive constraint, a new target outer surface is constructed. The machining error is calculated from the target surface and compensated via toolpath adjustment. At last, machining experiments are conducted to verify the feasibility of the proposed method.

On-Machine Measurement System of Tool Topography Using Edge Reversal Principle

Worn tools would wreak havoc on the surface integrity of workpieces in precision machining. This paper develops a new system for on-machine measurements of tool topography with micron accuracy based on the edge reversal principle. An array of experiments has been carried out to verify the system performance amenable to measuring various tools. An initial database of tools has been established as well for rapidly calculating tool wear and recording the topography characteristics of the different stages of tool wear. The on-machine measurement system is capable of achieving an expanded measurement uncertainty of 0.6 μm for tools with corner radii from 200 μm to 800 μm. The work provides equipment and data basis for efficient on-machine measurement of tool topography, which is beneficial to the prediction and management of tool life intelligently.

Determination method of optimal measurement area of CNC machine tool on-machine measurement system

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On-Machine Measurement of Profile and Concentricity for Ultra-Precision Grinding of Hemispherical Shells.

The profile and concentricity of hemispherical shells affect the frequency split and quality factor of hemispherical resonators. To compensate for machining errors caused by tool wear and tool setting, an on-machine measurement (OMM) method for the profile and concentricity of hemispherical shells in ultra-precision grinding was developed without the removal of workpieces from the machine tool. The OMM utilizes an inductive lever probe to test the inner and outer surfaces of the shell. A standard sphere is utilized to calibrate the relative position of the inductive lever probe at the two different work positions. To enhance the test accuracy of the OMM, a zero-position trigger-sampling method for the inductive lever probe was developed. It was verified to achieve a stable repeatability accuracy of 0.04 μm when using the OMM to realize a single-point sampling. Hemispherical shells were tested using the proposed OMM method. The concentricity test’s accuracy was verified to achieve accuracy better than 1 μm using a coordinate measuring machine and a standard sphere. The accuracy was 0.26 μm for testing the profiles of the hemispherical shell. The proposed OMM system was integrated with an ultra-precision machine tool. It is hoped that this method can help realize the integration function of machining-measurement-compensation.

Development of an on-machine measurement system with chromatic confocal probe for measuring the profile error of off-axis biconical free-form optics in ultra-precision grinding

Ultra-precision grinding of large-scale free-form optics made of hard brittle material is faced with several thorny problems, such as the grinding process is complex, hard to estimate the wear of the grinding wheel and the on-machine measurement technique of profile error is immature, which seriously affects the rapid convergence of profile accuracy. The on-machine measurement of profile error can effectively avoid the re-installation error introduced into the compensation period, and then the effectiveness and machining efficiency of compensation grinding are enhanced. Therefore, we developed an on-machine measurement system with a chromatic confocal probe for measuring the profile error of off-axis biconical free-form optics in ultra-precision grinding. First, the on-machine measurement system was developed on a 4-axis ultra-precision machine tool, and the scanning principles and position calibration were studied. Then, the scanning strategy was systematically researched, which included the centering approach, scanning path planning, scanning parameter calculation, and the evaluation principle of profile error. Finally, the on-machine measurement experiments were carried out on the off-axis biconical free-form optics with a width of 220 mm and height of 100 mm. The sub-micron variation range of measurement results is achieved by measuring the full-aperture profile error under different sampling parameters. The developed on-machine measurement system and scanning strategy can significantly improve the profile accuracy and machining efficiency of the large-scale free-form optics made of hard brittle material, and reduce the production cost.

Precision Milling of Integrated Turbine Based on a Non-Contact On-Machine Measurement System

Precision Milling of Integrated Turbine Based on a Non-Contact On-Machine Measurement System

Uncertainty Propagation and Assessment of Five-Axis On-Machine Measurement Error

Abstract As an important technology of adaptive machining, on-machine measurement (OMM) is always used to measure the shape of the to-be-cut surface. Due to the multi-source errors in an OMM system, the confidence of the measurement accuracy becomes particularly important before planning the next cutting procedure. OMM is implemented by multi-components involving machine tools, fixture, and on-machine probe. Each component introduces uncertainty of error into the measurement result. The positioning error, alignment error, and eccentricity error are investigated in terms of the expectation, uncertainty, and probability density function. By the kinematics of the components participated in the measurement, these errors are accumulated to affect the measurement results. Thus, the uncertainty of the final measurement result is determined by the accumulation of uncertainty of error sources. In order to evaluate the uncertainty of measurement error, an uncertainty propagation model involving positioning error of five-axis machine tools, alignment error of workpiece, and eccentricity error of the stylus tip is established in terms of the kinematic chain of OMM. Then, the uncertainty of the measurement result in vector form is obtained. Finally, the simulation and the experiment about the impeller are employed to validate the effectiveness and repeatability of the uncertainty propagation model for five-axis OMM.

Accuracy improvement of linear stages using on-machine geometric error measurement system and error transformation model.

In order to improve the accuracy of linear stages, a compact, portable and easy installation of a six-degree-of-freedom (6DOF) geometric error measurement system, in which two mirrors with special position and orientation are innovatively regarded as the sensitive elements of the roll error, is proposed. A set of combined focus lenses is integrated into the 6DOF measurement system to improve the resolution of the roll error. The accuracy of a linear stage is evaluated by the positional errors at the functional point, which is located at the working volume of a linear stage. An error transformation model based on the Abbe principle and the Bryan principle is established to estimate the positional errors at the functional point according to those at the measurement point. A series of experiments are carried out to verify the capable of the designed system and the effectiveness of the established model.

A Fiducial-Aided Reconfigurable Artefact for the Estimation of Volumetric Errors of Multi-Axis Ultra-Precision Machine Tools

In this paper, a fiducial-aided reconfigurable artefact is presented for estimating volumetric errors of multi-axis machine tools. The artefact makes use of an adjustable number of standard balls as fiducials to build a 3D artefact which has been calibrated on a coordinate measuring machine (CMM). This 3D artefact demonstrates its reconfigurability in its number of fiducials and their locations according to the characteristics of workpieces and machine tools. The developed kinematics of the machine tool were employed to identify the volumetric errors occupied by the workpiece in the working space by comparing the information acquired by on-machine metrology with that acquired by the CMM. Experimental studies are conducted on a five-axis ultra-precision machine tool. A developed 3D artefact composed of five standard spheres is measured by the integrated on-machine measurement system. Factors including the gravity effect and measurement repeatability are also examined in order to optimize the geometry of the artefact. The results show that the developed 3D artefact is able to provide information about the working space occupied by the workpiece.

Development of an on-machine measurement system for ultra-precision machine tools using a chromatic confocal sensor

In ultra-precision machining, the accuracy of a workpiece can be generally improved by surface measurement and compensation machining. Since on-machine surface measurement can avoid the errors caused by repositioning workpieces and use the machine axes to extend the measuring range, there has been a trend from offline measurement to on-machine measurement in recent years. However, the workpiece surfaces inspected by on-machine measurement system in previous studies generally have small slopes and depths. In this paper, an on-machine measurement device based on a chromatic confocal sensor is designed, which can inspect workpiece surfaces with larger slopes and depths. The on-machine measurement system and measurement procedure are introduced first. A nonlinear least squares method is then used to further reduce the adverse influence of the alignment error between the axes of the sensor and the spindle of the machine tool. Finally, machining and measuring experiments of the spherical and free-form surfaces are performed using a Nanotech 650FG ultra-precision machine lathe to validate the proposed on-machine measurement method. The profile pattern and the form error obtained from the on-machine measurement device are compared with those obtained from a Taylor-Hobson 3D stylus profilometer. There is good agreement between the two results, which verifies the effectiveness of the proposed on-machine measuring method.

Flatness on-machine measurement system of chemical mechanical polishing process for large-caliber tin plates

In planar optics machining, surface flatness is a critical requirement for making high-quality optical devices. Chemical mechanical polishing (CMP) is an important process of smoothing surfaces for hard and brittle planar optics. Thus, there are growing interests in developing high-precision flatness on-machine measurement system for tin plate CMP process. However, the traditional evaluation measurement cannot meet the measurement accuracy requirement of approximate 2 μm. In this study, we propose an effective on-machine measuring system for the large-caliber optical tin plate, which consists of linear guideway, rotary table, and measuring sensor. In the system, the straightness error of the guideway and the axial runout error of the rotary table are compensated using a spiral method and the Keyence LK-G5000 measuring sensor. First, the spiral measuring path is formed by the movement of the line guideway and rotary table, which can prevent from multiple calibration. Then, the 3D flatness error of the dressing process is measured by linear movement of the LK-G5000 and the rotation of the tin plate. After the primary measurement process, the obtained 3D flatness error is compensated for straightness and axial runout error in sequence. To verify the accuracy of the flatness measurement, the tin plate is dressed by the natural diamond tool according to the measured 3D flatness error. After the dressing process, the peak-valley value of the remeasured flatness error can achieve 2.12 μm through a single-step dressing. The experimental results provide the accuracy and reliability of the high-precision on-machine flatness measurement system for the large-caliber tin plate.