Prediction of surface roughness during abrasive flow machining

Gorana, V. K.; Jain, V.K.; Lal, G.K.

doi:10.1007/s00170-005-0197-4

Cited by 61 publications

(27 citation statements)

References 11 publications

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“…In the same way, Bigerelle et al [4,5] prove that abraded surfaces can be modeled by stochastic fractal functions and using the Monte Carlo model, and thus the belt finishing process as well [6]. This stochastic aspect is also used to take into account the roughness in the abrasion model thanks to the Gaussian approximation of surface roughness [7]. Simple sclerometric rheological material analysis shows geometrical dependences of ridge height and groove depth, in combination with the Peaks and Valleys (PV) [8].…”

Section: Introductionmentioning

confidence: 94%

Relevance of Wavelet Shape Selection in a complex signal

Bigerelle

Guillemot

Khawaja

et al. 2013

Mechanical Systems and Signal Processing

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Section: Introductionmentioning

confidence: 94%

Relevance of Wavelet Shape Selection in a complex signal

Bigerelle

Guillemot

Khawaja

et al. 2013

Mechanical Systems and Signal Processing

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“…If the non-linearity and temperature effects are considered, one can enhance the model accuracy and it would give a better agreement with the experimental results. Gorana et al [58][59][60] developed a theoretical model of forces acting on a single AP for studying the finishing mechanism of AFF process. Comparison of theoretical model results with the experimental data of force and active APs density obtained during AFF process has been reported [59].…”

Section: Process Modelling and Optimizationmentioning

confidence: 99%

Nano-finishing techniques: a review

Jain

Sidpara

Sankar

et al. 2011

Proceedings of the Institution of Mechanical Engineers, Part C:

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The quality of surface is one of the significant parameters which affects the life and functionality of any product. Many products require nano-level surface finish as their functional indispensability. Those processes having flexible finishing tool can be employed for such type of components. These finishing processes can be classified into two categories: with and without magnetic field assistance. The former includes magnetic abrasive finishing, magnetorheological finishing, and allied processes, and the latter includes abrasive flow finishing. This article reports the critical review of mainly three processes: abrasive flow finishing, magnetorheological finishing, and magnetorheological abrasive flow finishing. In this article, the issues that need attention of the researchers have been categorically mentioned. This article provides a comprehensive literature review of magnetorheological finishing process in terms of rheological characterization of magnetorheological fluid, experimental investigation, theoretical analysis, and applications. This article deals with various advancements in abrasive flow finishing and hybrid processes. The developments in magnetorheological abrasive flow finishing and its allied processes have been discussed in detail. By suitable modification of magnetorheological abrasive flow finishing process, it can achieve surface finish up to nano-meter on different materials such as brass, aluminium, stainless steel, and silicon-nitride.

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“…The strategy for improving surface roughness in the polishing process is to reduce the concentration of the polishing agent [35]. However, in order to ensure the correction efficiency of the surface profile, the polishing agent cannot be excessively diluted.…”

Section: Compensation Of Surface Roughnessmentioning

confidence: 99%

Pseudo-random Path Generation Algorithms and Strategies for the Surface Quality Improvement of Optical Aspherical Components

Zha

Zhang

et al. 2020

Materials

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This study proposes two path generation algorithms to diminish the superposition of the convolution effect on the polishing path in computer-controlled optical surfacing. According to the polishing of aluminum-alloy based hyperboloid optical components, different proportions of polishing agents were blended. Then, the surface roughness of the optical components were determined through a validation experiment of the algorithms. Furthermore, the relationship between surface roughness and the polishing agent concentration, and the compensation strategies for surface roughness were analyzed. The results show that the two algorithms effectively compensated for surface waviness. The findings support the strategies for improving the surface quality of optical components with aspherical surfaces.

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Prediction of surface roughness during abrasive flow machining

Cited by 61 publications

References 11 publications

Relevance of Wavelet Shape Selection in a complex signal

Relevance of Wavelet Shape Selection in a complex signal

Nano-finishing techniques: a review

Pseudo-random Path Generation Algorithms and Strategies for the Surface Quality Improvement of Optical Aspherical Components

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