Accuracy distribution and determination of the flexible three-coordinate measuring machine

Wang, Chunhua; Fei, Yetai; Hu, Penghao; Wang, Ping-ping; Chen, Wentao

doi:10.1117/12.716193

Cited by 5 publications

(6 citation statements)

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“…In 2010 K. Sivakumar, et al proposed a novel multi-objective optimization method to enhance the operations of the non-traditional algorithms and Multi-Objective Particle Swarm Optimization and systematically distribute the tolerances among various the components of mechanical assemblies [32]. From the above literature, the previous researches on tolerance allocation mainly focus on structural design taking manufacturing cost or manufacturing process into consideration, besides, there are many of accuracy allocation in the field of hull construction, robotics, military application, and instruments [35,24,37,42,34]. However, works on accuracy allocation of multi-axis machine tools are few.…”

Section: Accuracy Allocationmentioning

confidence: 99%

A geometric accuracy design method of multi-axis NC machine tool for improving machining accuracy reliability

Cai¹,

Zhang²,

Cheng³

et al. 2015

Eksploatacja i Niezawodnosc - Maintenance and Reliability

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Section: Accuracy Allocationmentioning

confidence: 99%

A geometric accuracy design method of multi-axis NC machine tool for improving machining accuracy reliability

Cai¹,

Zhang²,

Cheng³

et al. 2015

Eksploatacja i Niezawodnosc - Maintenance and Reliability

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“…The single-point repeatability accuracy of the AACMM calculated by (11) and (12) with the 70 groups of simulation data is 3×10 −6 mm.…”

Section: Numerical Simulationmentioning

confidence: 99%

“…The single-point repeatability accuracy of the AACMM calculated by (11) and (12) with the 70 groups of simulation data is 2×10 −6 mm. The deviation between the repeatability accuracies before and after scaling length parameters can be neglected with regard to the normal accuracy (5×10 −2 mm) of AACMMs.…”

Section: The Effects Of Scaling Factor On Repeatability Accuracymentioning

confidence: 99%

“…Wang et al [11] and Gao et al [12] used a cone hole, which can restrict the center of the probe in the same position, to collect multiple groups of joint angles by changing the poses AACMMs. Under the constraint of single-point cone hole, the coordinates calculated by different group of joint angles will be the same if the kinematic parameters have no errors.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Kinematic Parameters Identification Method for Articulated Arm Coordinate Measuring Machines Using Repeatability and Scaling Factor

Cheng

Wang

Weng

et al. 2018

Mathematical Problems in Engineering

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Kinematic parameters identification and compensation are effective ways to improve the accuracy of articulated arm coordinate measuring machines (AACMMs) and robotic arms without increasing the cost of hardware. Generally, kinematic parameters identification methods based on standard references are relatively high in accuracy but time-consuming and not suitable for industrial sites, while kinematic parameters identification methods based on repeatability are flexible and easy to implement but lack reliability in accuracy. A novel kinematic parameters identification method for AACMMs using repeatability and scaling factor is proposed in this paper, which combines the advantages of methods based on both standard references and repeatability. Through theoretical analysis and numerical simulations, we found that the commonly used single-point-repeatability-based identification method has problems in identifying the length parameters, which is due to that high repeatability cannot guarantee the accuracy of the kinematic parameters and the measurement accuracy of the AACMM. Further analysis showed that the error of the length parameters is determined by a scaling factor which can be used to remove the error of length parameters. Therefore, a two-step novel kinematic parameters identification method for the AACMMs using repeatability and scaling factor was proposed to get accurate parameters with convenient operation. Experimental studies showed the effectiveness of the proposed identification method, which indicated that 93% more error in spatial length can be decreased comparing to the traditional method of repeatability-based identification.

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“…In fact, this is actually a problem of structural optimization and its aim is to obtain the optimum solution under specified limitations and limited resources [6]. To date, there are many researchers focusing their attention on accuracy allocation of structural designs and some allocation models have been developed in the field of naval engineering, measuring machines, robotics, military weapons, and instrumentation [28,40,41,45,52]. However, the research on accuracy allocation of machine tools is primarily targeting at the parallel machine tool development [29,43,46], and a systemic approach for accuracy allocation of multi-axis machine tools has not been developed yet, with limited studies focusing on the field of machine tool design.…”

Section: Introductionmentioning

confidence: 99%

An approach of comprehensive error modeling and accuracy allocation for the improvement of reliability and optimization of cost of a multi-axis NC machine tool

Zhang

Liu

Cheng

et al. 2016

Int J Adv Manuf Technol

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Machining accuracy is critical for the quality and performance of a mechanical product, and the reliability of a multi-axis NC machine tool reflects the ability to reach and maintain the required machining accuracy. The objective of this study is to propose a general methodology that will simultaneously consider geometric errors and thermal-induced errors to allocate the geometric accuracy of components, for improving machining accuracy reliability under certain design requirements. The multi-body system (MBS) theory was applied to develop a comprehensive volumetric error model, showing the coupling relationship between the individual errors of the components of this machine tool and their volumetric accuracy. Additionally, a thermal error model was established based on the neural fuzzy control theory and was compared to the common thermal error modeling method called BP neural network. Based on the traditional cost model and the reliability analysis model, a geometric error-cost model and a geometric error-reliability model were established, taking the weighted function principle into consideration. Then, an allocation approach of the geometric errors, for optimizing total cost (manufacture and QLF) and reliability, subject to the geometrical and operational constraints of the machine tool, was proposed and formulated into a mathematical model, in order to perform the optimization process of accuracy allocation by using the advanced NSGA-II algorithm. A case study was also performed in a five-axis machine tool, and the traditional NSGA algorithm was used for comparison. The optimization results for the five-axis machining center showed that the proposed approach is effective and able to perform the optimization of geometric accuracy and improve the machining accuracy and the reliability of the machine tool.

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Accuracy distribution and determination of the flexible three-coordinate measuring machine

Cited by 5 publications

References 0 publications

A geometric accuracy design method of multi-axis NC machine tool for improving machining accuracy reliability

A geometric accuracy design method of multi-axis NC machine tool for improving machining accuracy reliability

A Novel Kinematic Parameters Identification Method for Articulated Arm Coordinate Measuring Machines Using Repeatability and Scaling Factor

An approach of comprehensive error modeling and accuracy allocation for the improvement of reliability and optimization of cost of a multi-axis NC machine tool

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