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With the problems in usage of cutting fluids, the use of Minimum Quantity Lubrication (MQL) has gained prominence. Though several mathematical models have been postulated in literature on dry cutting, models that deal with cutting fluids are very rare and the models on MQL are seldom found. The present work tries to discuss regression and artificial neural network models postulated on influence of MQL on tool wear, while machining AISI 1040 steel using HSS tool. The proposed models were validated with the experimental results.
S.Narayana Rao. 2011. "ONLINE TOOL WEAR PREDICTION MODELS IN MINIMUM QUANTITY LUBRICATION". Global Journal of Research in Engineering - B: Automotive Engineering GJRE-B Volume 11 (GJRE Volume 11 Issue B5).
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
v1.2
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Total Score: 113
Country: India
Subject: Global Journal of Research in Engineering
Authors: S.Narayana Rao, Dr.B.Satyanarayana, Dr.K.Venkatasubbaiah (PhD/Dr. count: 2)
View Count (all-time): 356
Total Views (Real + Logic): 2084
Total Downloads (simulated): 93
Publish Date: 2011 07, Fri
Monthly Totals (Real + Logic):
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