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2019
DOI: 10.1007/s42452-019-0827-3
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Experimental investigation and modelling of MQL assisted turning process during machining of 15-5 PH stainless steel using response surface methodology

Abstract: 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 c… Show more

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Cited by 15 publications
(7 citation statements)
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References 31 publications
(32 reference statements)
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“…It was also showed to be similar to the studies in the literature [22]. With increased flow rate, Ra roughness slightly decreased [33]. Graphs showing the relationship between surface roughness values and turning parameters are given in Fig.…”
Section: Results and Discussion 31 Surface Roughnesssupporting
confidence: 87%
“…It was also showed to be similar to the studies in the literature [22]. With increased flow rate, Ra roughness slightly decreased [33]. Graphs showing the relationship between surface roughness values and turning parameters are given in Fig.…”
Section: Results and Discussion 31 Surface Roughnesssupporting
confidence: 87%
“…15-5PH steel is widely used in the aerospace, petrochemical industries, food processing, paper production, metalworking, gear and pump manufacturing [3]. The majority of 15-5PH stainless steel components are manufactured via machining methods.…”
Section: Introductionmentioning
confidence: 99%
“…It was concluded that MQL is a far superior method of applying cutting fluid and poses less health risks. Sivaiah [32] evaluated turning performance under MQL cooling by varying process parameters. They observed that the mathematical models constructed using the RSM approach accurately predicted performance results.…”
Section: Introductionmentioning
confidence: 99%