A new surface roughness prediction model for ceramic grinding
A new surface roughness prediction model for ceramic grinding
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DOI：
10.1243/095440505x32832
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发表时间：
2005-11
期刊：
影响因子：
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通讯作者：
Sanjay Agarwal;P. Rao
中科院分区：
文献类型：
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作者：
Sanjay Agarwal;P. Rao
摘要产品质量保证是当今工业界非常关注的问题。陶瓷磨削加工的表面质量是产品整体质量的重要组成部分。表面粗糙度是磨削产品的主要质量属性之一，因此它被用来确定和评价产品的质量。虽然表面粗糙度的评价已经标准化，建立一个可靠的表面粗糙度预测模型仍然是一个关键问题。本文提出了一种新的分析模型的算术平均表面粗糙度的预测的基础上的随机性质的磨削过程中，主要由随机几何形状的颗粒和随机分布的切削刃的砂轮表面上具有随机的颗粒突起高度。得到了表面粗糙度与切屑厚度之间的简单关系，并通过碳化硅磨削实验结果进行了验证。
Abstract Product quality assurance is a very important concern in industries these days. Surface quality is an important constituent of overall product quality in ceramic grinding. Surface roughness is one of the major quality attributes of a ground product and hence it is used to determine and evaluate the quality of the product. Although the surface roughness evaluation has been standardized, establishment of a model for reliable prediction of surface roughness is still a key issue. This paper presents a new analytical model for the prediction of arithmetic mean surface roughness based on the stochastic nature of grinding process, governed mainly by the random geometry of grain and random distribution of cutting edges on the wheel surface having random grain protrusion heights. A simple relationship between the surface roughness and the chip thickness was obtained, which was validated by the experimental results of silicon carbide grinding.