Predictive modelling of surface roughness and tool wear in solid lubricant assisted turning of AISI 1040 steel

被引：1

作者：

Krishna, P. Vamsi ^{[1
]}

Rao, D. N. ^{[2
]}

Srikant, R. R. ^{[1
]}

机构：

[1] GITAM Univ, Dept Ind Prod Engn, Visakhapatnam, Andhra Pradesh, India

[2] Andhra Univ, Dept Mech Engn, Visakhapatnam, Andhra Pradesh, India

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART J-JOURNAL OF ENGINEERING TRIBOLOGY | 2009年 / 223卷 / J6期

关键词：

surface roughness; tool wear; solid lubricant; regression model; MATHEMATICAL-MODELS; FINISH;

D O I：

10.1243/13506501JET475

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This article focuses on developing empirical models for tool wear and surface roughness prediction in the solid lubricant assisted turning process. Solid lubricant suspensions like graphite and boric acid in SAE 40 oil are employed in the turning of AISI 1040 (EN 8) steel. Results indicate that surface roughness is improved by reducing cutting forces and tool flank wear as compared to dry and wet machining. A comparison of predicted values from the empirical models and measured values is also carried out.

引用

页码：929 / 934

页数：6

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