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contributor authorLin, Bin
contributor authorZhou, Ping
contributor authorWang, Ziguang
contributor authorYan, Ying
contributor authorKang, Renke
contributor authorGuo, Dongming
date accessioned2019-02-28T11:02:32Z
date available2019-02-28T11:02:32Z
date copyright9/17/2018 12:00:00 AM
date issued2018
identifier issn1087-1357
identifier othermanu_140_12_121001.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252018
description abstractGrain depth-of-cut, which is the predominant factor determining the surface morphology, grinding force, and subsurface damage, has a significant impact on the surface quality of the finished part made of hard and brittle materials. When the existing analytical models are used to predict the gain depth-of-cut in ultra-precision grinding process of silicon wafer, the results obtained become unreasonable due to an extremely shallow grain depth-of-cut, which is inconsistent with the theory of the contact mechanics. In this study, an improved model for analyzing the grain depth-of-cut in ultra-fine rotational grinding is proposed, in which the minimum grain depth-of-cut for chip formation, the equivalent grain cutting tip radius, elastic recovery deformation in cutting process, and the actual number of effective grains are considered in the prediction of the ultrafine rotational grinding of brittle materials. The improved model is validated experimentally and shows higher accuracy than the existing model. Furthermore, the sensitivity of the grain depth-of-cut to three introduced factors is analyzed, presenting the necessity of the consideration of these factors during the prediction of grain depth-of-cut in ultrafine grinding.
publisherThe American Society of Mechanical Engineers (ASME)
titleAnalytical Elastic–Plastic Cutting Model for Predicting Grain Depth-of-Cut in Ultrafine Grinding of Silicon Wafer
typeJournal Paper
journal volume140
journal issue12
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.4041245
journal fristpage121001
journal lastpage121001-7
treeJournal of Manufacturing Science and Engineering:;2018:;volume( 140 ):;issue: 012
contenttypeFulltext


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