Experimental investigation and modelling of MQL assisted turning process during machining of 15-5 PH stainless steel using response surface methodology

被引:0
|
作者
P. Sivaiah
机构
[1] Madanapalle Institute of Technology & Science,Department of Mechanical Engineering
来源
SN Applied Sciences | 2019年 / 1卷
关键词
Response surface methodology; Minimum quantity lubrication; Machining; Surface roughness; Flank wear; Material removal rate; 15-5 PH SS;
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学科分类号
摘要
Built-up-edge formation is one of the problems in conventional (flood) machining of 15-5 precipitated hardened stainless steel (PH SS) which results in poor product quality. Further, concentration on stringent environmental conscious regulations has been increasing in metal cutting industries due to environmental pollution. The present work target is to address these problems using minimum quantity lubrication (MQL) machining technique. MQL machining technique is one of the promising techniques for the metal cutting industries because it satisfies the stringent environmental conscious regulations set for metal cutting industries in terms of usage and disposal of chemically contaminated emulsion based coolants. In the present work, studied the effect of MQL cooling, process parameters on turning performance characteristics and also established a relationship between the turning controllable process parameters and responses in the machining of 15-5 PH SS using response surface methodology (RSM) under MQL environment with tungsten carbide cutting insert. Spindle speed (v), feed rate (f), depth of cut (d) and MQL flow rate (Q) have been taken as MQL machining process parameters. Output turning performances considered were surface roughness (Ra), tool flank wear (Tw) and material removal rate respectively. Experiments were done based on the central composite design of RSM. From RSM analysis, it was noticed that developed mathematical models predicted the performance results close to the experimental results. Further, it was observed that surface roughness and tool wear reduced significantly with an increase in MQL flow rate respectively.
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