Machine tool calibration: Measurement, modeling, and compensation of machine tool errors

Gao, Wei; Ibaraki, Soichi; Donmez, M A.; Kono, Daisuke; Mayer, Josef; Chen, Yuan-Liu; Szipka, Károly; Archenti, Andreas; Linares, Jean‐Marc; Suzuki, Norikazu

doi:10.1016/j.ijmachtools.2023.104017

Cited by 61 publications

(15 citation statements)

References 414 publications

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“…A lot of research has already been conducted on thermo-elastic TCP errors. An overview of recent research is presented by Gao et al [2]. The research can be clustered into approaches focussing on compensation and correction of the thermo-elastic error.…”

Section: Thermo-elastic Errormentioning

confidence: 99%

An Investigation of the Relationship Between Encoder Difference and Thermo-Elastic Machine Tool Deformation

Brecher¹,

Dehn²,

Neus³

2023

Journal of Machine Engineering

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New approaches, using machine learning to model the thermo-elastic machine tool error, often rely on machine internal data, like axis speed or axis position as input data, which have a delayed relation to the thermo-elastic error. Since there is no direct relation to the thermo-elastic error, this can lead to an increased computation inaccuracy of the model or the need for expensive sensor equipment for additional input data. The encoder difference is easy to obtain and has a direct relationship with the thermo-elastic error and therefore has a high potential to improve the accuracy thermo-elastic error models. This paper first investigates causes of the encoder difference and its relationship with the thermo-elastic error. Afterwards, the model is presented, which uses the encoder difference to compute the thermo-elastic error. Due to the complexity of the relationship, it is necessary, to use a machine learning approach for this. To conclude, the potential of the encoder difference as an input of the model is evaluated.

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Section: Thermo-elastic Errormentioning

confidence: 99%

An Investigation of the Relationship Between Encoder Difference and Thermo-Elastic Machine Tool Deformation

Brecher¹,

Dehn²,

Neus³

2023

Journal of Machine Engineering

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“…So the proposed machine simulator's practical use for accurate machining will be possible after all equipment errors have been controlled for, ensuring they have no impact on part reliability. Notably, a complex matter of mathematical and thermal error compensating is not addressed here but has garnered plenty of interest from other investigators [10,11]. Dynamical investigation comprises the evaluation of the force of cutting for determining the nervousness motion quality of the manufacturing equipment.…”

Section: Introductionmentioning

confidence: 99%

Improving CNC Turning Machine Precision through Vibration Analysis for Clamping Error Detection Employing Principal Component Analysis

Ullah,

Chan,

Xie

2024

Preprint

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The vibration caused by mechanical manufacturing will lead to unpredictable changes in product quality, which will increase the manufacturing cost. Plenty of research is imposed to establish a normal vibration coefficient or to develop an accurate and efficient production process. Therefore, various health diagnosis methods and feedback mechanisms are obtained, such as dynamic feature Detection, machine tool state Detection, cutting chatter analysis, health state feedback of specific parts in the machine tool, and so on. This study analyzes the lathe and establishes the vibration analysis and health diagnosis method used for NC lathe or traditional machine tools through the vibration signals generated by different clamping states. Before the spindle speed reaches 2000 rpm, 5 experiments at an interval of 250- rpm and three clamping states are executed. Moreover, the vibration signal is obtained using the intelligent prediction and diagnosis performance system, analyzed in the frequency domain, matched with the root mean square result, and checked for the accuracy of the vibration signal data and vibration eigenvalues. Then, digital tools are used to filter the signal according to the filtered outliers and the matching results of feature extraction. Principal component analysis (PCA) and the projection matrix are used to evaluate 37 features and reduce the dimension of the data, to obtain the vibration data distribution map under different rotating speeds of each clamping state. It can identify the distribution range and tightness of the distribution map under each clamping state. In the above experiment, the signal data of each 250-rpm interval and three clamping states were collected and compared. The results show that it is feasible to use the PCA method to determine the change of vibration value in the CNC lathe and establish a health state feedback data set based on the vibration change mechanism.

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“…While machine tools and metrology systems share a similar workflow for geometric error compensation, they exhibit distinct differences in the constituent elements of errors and in the objectives of compensation scheme. In machine tools, errors predominantly originate from geometric inaccuracies, thermal effects, and cutting-induced forces [39][40][41]. Conversely, non-contact scanning metrology systems, operating typically under temperature-controlled environment and reduced motion speeds, largely avoid thermal and forceinduced errors.…”

Section: Introductionmentioning

confidence: 99%

“…While research on error modeling and compensation in five-axis machine tools has been thoroughly explored, as discussed in [39,40,55], the focus on geometric error compensation within metrology systems remains largely confined to three-axes orthogonal metrology systems [56][57][58][59][60][61][62]. For fouraxes CMMs that are more complex, relevant research has been carried out by de Aquino Silva et al in [63].…”

Section: Introductionmentioning

confidence: 99%

Unified framework for geometric error compensation and shape-adaptive scanning in five-axis metrology systems

Zhang,

Yu,

Zhu

et al. 2024

Meas. Sci. Technol.

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In response to the escalating demand for precise shape metrology of complex optical surfaces, this study unveils a unified geometric error compensation and trajectory planning framework tailored for high-accuracy five-axis scanning metrology systems, which remains a notably underexplored field compared to error compensation in machine tools. Founded on a unified geometric model, the proposed framework seamlessly integrates a versatile shape-adaptive trajectory planning strategy, a thorough global error sensitivity analysis approach, and an exhaustive geometric error compensation scheme. Leveraging inverse kinematics, an innovative shape-adaptive scanning trajectory generation strategy is mathematically formulated, thereby facilitating adaptable measurement trajectory generation for diverse surface geometries. Employing forward kinematics, an exhaustive geometric error model is established to extensively address the 53 distinct geometric errors in the metrology system. This proposed error model fundamentally augments conventional geometric error models in machine tool by managing not only the geometric errors from the motion system, but also those from the probe and workpiece. To streamline the error compensation procedure, a novel global error sensitivity analysis approach is introduced, identifying both system-oriented and process-oriented sensitive geometric errors for targeted compensation. Experimental validation using a standard ball, which achieved an exceptional 89.35% reduction in the root mean square (RMS) of the measurement errors, further confirms the feasibility and effectiveness of the proposed framework. By offering an universal trajectory planning, sensitivity analysis and error compensation trinity for five-axis scanning metrology systems, this study sets the stage for precision advancements and design optimization across diverse configurations of metrology systems.

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Machine tool calibration: Measurement, modeling, and compensation of machine tool errors

Cited by 61 publications

References 414 publications

An Investigation of the Relationship Between Encoder Difference and Thermo-Elastic Machine Tool Deformation

An Investigation of the Relationship Between Encoder Difference and Thermo-Elastic Machine Tool Deformation

Improving CNC Turning Machine Precision through Vibration Analysis for Clamping Error Detection Employing Principal Component Analysis

Unified framework for geometric error compensation and shape-adaptive scanning in five-axis metrology systems

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