Modeling and prediction of surface topography and surface roughness in dual-axis wheel polishing of optical glass

Lu, Ange; Jin, Tan; Liu, Qifeng; Guo, Zhimou; Qu, Meina; Luo, Hu; Han, Mei

doi:10.1016/j.ijmachtools.2018.10.001

Cited by 56 publications

(21 citation statements)

References 38 publications

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“…Conventional mechanical grinding tools, are mostly considered as rigid composite bodies [1] , such as grinding wheels, composed of bond agents (vitrified/resin/metallic) and abrasive grains (SiC/Al 2 O 3 /diamond/CBN). Most ground workpiece also shows the infinite stiffness with no bending/distortion/ displacement occurring in the interaction with the tool [2,3]. Therefore, the material removal, surface profile and surface integrity are analyzed on the basis of the grinding processes with two rigid bodies (workpiece and tool) [4,5].…”

Section: Introductionmentioning

confidence: 99%

Controlling of compliant grinding for low-rigidity components

Yang

Liao

et al. 2020

International Journal of Machine Tools and Manufacture

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The machining of low-rigidity components (e.g. thin-walled) with compliant tools presents accuracy challenges as both sides in contact are being deformed. The controlling method presented in this paper enables, for the first time, to obtain the desired and uniform material removal rate by controlling the nominal tool offset when two bodies (workpiece and tool) are compliant in grinding. A contact deformation model is proposed to predict the relation between the nominal and actual tool offsets. The function of nominal tool offsets and material removal rates is obtained based on the calibration tests. Spot grinding tests have been performed for the validation of the calculated material removal rates, normal grinding forces and spot sizes, presenting position-dependent characteristics. The controlling method has been tested for the case of continuous grinding the whole area of a circular aluminium thin wall. The surfaces ground under the time-variant tool offsets (proposed approach) reach the desired removal depth with an average error of ≤10% and achieve 11.2μm~24.2μm (P-V) accuracy in the elastic domain, compared with the error of 76.8%~113.7% and accuracy of 42.6μm~50.1μm (P-V) in the circumstance of constant tool offsets (conventional approach).

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Section: Introductionmentioning

confidence: 99%

Controlling of compliant grinding for low-rigidity components

Yang

Liao

et al. 2020

International Journal of Machine Tools and Manufacture

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“…To guide the process of the ultrasonic-assisted internal grinding, Cao et al [24] established a mathematical model of grinding force and concluded that vibration can reduce the internal grinding force. Lu et al [25] explored the number of effective abrasive grains during processing during the establishment of an internal microtopography prediction model for dual-axis wheel polishing. In summary, most of the existing related models were developed for predicting grinding force and traditional polishing force, which cannot be directly applied to VARP polishing force prediction.…”

Section: Introductionmentioning

confidence: 99%

Development of Decoupling Device for Vibration-Assisted Roller Polishing of Silicon Carbide Ceramics

et al. 2020

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“…It is rather difficult to achieve uniform surface texture and high convergence rates of surface roughness (CRSR) at the same time in the conventional optical polishing process. Under the dual-axis mode, the variation of co-rotating speed has less influence on the polishing quality, very high CRSR and uniform texture can be achieved under different co-rotating speeds [1]. The preparation of…”

Section: Introductionmentioning

confidence: 99%

Adaptive neuro fuzzy determination of impactful factors on non-uniformity of polished surface

Petković¹

2019

JIEC

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In this study, the neuro fuzzy logic selection of the most influential parameters for non-uniformity of polished surface was performed. The influence of three parameters was analyzed: carrier load, thickness and the pads elastic modulus. Adaptive neuro fuzzy logic or ANFIS was used for establishing the nonlinear relationships between the three parameters and the non-uniformity polished surface. Dataset for training and testing procedure was extracted by finite element model. According to the regression models, thickness of pad has the greatest influence on the non-uniformity. Moreover, elastic modulus and pad thickness are the optimal combination of non-uniformity. Results could be useful in the improvement of chemical polishing process.

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Modeling and prediction of surface topography and surface roughness in dual-axis wheel polishing of optical glass

Cited by 56 publications

References 38 publications

Controlling of compliant grinding for low-rigidity components

Controlling of compliant grinding for low-rigidity components

Development of Decoupling Device for Vibration-Assisted Roller Polishing of Silicon Carbide Ceramics

Adaptive neuro fuzzy determination of impactful factors on non-uniformity of polished surface

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