Statistical Approach Optimizing Slant Feed Grinding

Shimada, Keita; Liew, Pay Jun; Zhou, Tianfeng; Yan, Jiwang; Kuriyagawa, Tsunemoto

doi:10.1299/jamdsm.6.898

Cited by 10 publications

(4 citation statements)

References 13 publications

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“…The simulation results and the experimental results of grinding force and ground surface roughness show a close similarity. Shimada et al [9] modified the models of Matsui and Syoji [4,5,6] and Matsui [7] and proposed a theoretical model of grinding mechanism for calculating the surface roughness for the slant feed grinding operations. The calculated results were validated by experimental ones using a customized vibration assisted micro-grinding device.…”

Section: Literature Review On Grinding Mechanismmentioning

confidence: 99%

Elucidating Grinding Mechanism by Theoretical and Experimental Investigations

et al. 2018

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Grinding is one of the essential manufacturing processes for producing brittle or hard materials-based precision parts (e.g., optical lenses). In grinding, a grinding wheel removes the desired amount of material by passing the same area on the workpiece surface multiple times. How the topography of a workpiece surface evolves with these passes is thus an important research issue, which has not yet been addressed elaborately. The present paper tackles this issue from both the theoretical and the experimental points of view. In particular, this paper presents the results of experimental and theoretical investigations on the multi-pass surface grinding operations where the workpiece surface is made of glass and the grinding wheel consists of cBN abrasive grains. Both investigations confirm that a great deal of stochasticity is involved in the grinding mechanism, and the complexity of the workpiece surface gradually increases along with the number of passes.

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Section: Literature Review On Grinding Mechanismmentioning

confidence: 99%

Elucidating Grinding Mechanism by Theoretical and Experimental Investigations

et al. 2018

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“…A model that mimics the surface generation mechanism of grinding must consider the Functional Requirements (FRs) shown in Table 1. The models developed so far [7][8][9][10][11][12][13] deal with a partial list of the abovementioned FRs. In addition, the modules dealing with the deterministic and stochastic formulations are not clearly identified.…”

Section: Issues Of Surface Generation Mechanism Of Grindingmentioning

confidence: 99%

“…To build such as a system, the mechanism that generates the roughness on the work-surface must be captured and codified as precisely as possible. Numerous authors have studied the mechanism that controls the surface generation process due to grinding [7][8][9][10][11][12][13]. One of the remarkable features of the mechanisms developed so far [7][8][9][10][11][12][13] is the use of statistical (or stochastic) formulation along with the deterministic formulation.…”

Section: Introductionmentioning

confidence: 99%

A Surface Generation Mechanism of Grinding

Ullah

Chowdhury

Kubo

2016

AMM

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This paper presents a surface generation mechanism of grinding that captures the microscopic interaction between the abrasive grains and work-surface. The mechanism utilizes both deterministic and stochastic formulations and deals with such realistic constraints as loss/wear and uneven distribution of abrasive grains, roughness of already-ground work-surface, and machine stiffness. Apart from the theoretical treatments, numerical examples are cited showing how the topography of the work-surface evolves because of the proposed mechanism. The work will help build computerized systems ensuring a reliable prediction of the surface roughness due to grinding under the realistic constraints.

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“…Surface texture is then discussed by considering EP. From Asmp (vi), whether X is removed within a removal process is equal to whether any cutting edges pass the triangle region beneath X whose tip angle is 2α [7]; hereinafter the region is named as T(X). If the probability whether any cutting edges pass T(X) is expressed as Q(z t ), EP after a removal process, C 1 (z w ), is theoretically determined as:…”

Section: Theoretical Calculationmentioning

confidence: 99%

Stochastic Simulation of Tape Grinding for Wafer-Like Workpiece

Shimada

Watanabe²,

Takasu³

et al. 2016

MSF

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Advanced semiconductor materials including silicon carbide and gallium nitride possess excellent properties like high hardness, and high heat and chemical resistance compared to silicon. Such properties reversely prevent efficient production of wafers, therefore a new wafer finishing method, tape grinding, is developed to improve productivity. This paper proposes a simulation method of tape grinding, which method is developed by modifying the stochastic approach developed for plunge grinding. The distribution of abrasive grains on the grinding tape is represented by number density, and the material existence probability that is represented by Abbott-Firestone curve is modified by considering machining parameters. Tape grinding process were then conducted to confirm the calculation method.

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Statistical Approach Optimizing Slant Feed Grinding

Cited by 10 publications

References 13 publications

Elucidating Grinding Mechanism by Theoretical and Experimental Investigations

Elucidating Grinding Mechanism by Theoretical and Experimental Investigations

A Surface Generation Mechanism of Grinding

Stochastic Simulation of Tape Grinding for Wafer-Like Workpiece

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