ONLINE TOOL WEAR PREDICTION MODELS IN  MINIMUM QUANTITY LUBRICATION

ONLINE TOOL WEAR PREDICTION MODELS IN MINIMUM QUANTITY LUBRICATION

Article ID

TW4IV

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ONLINE TOOL WEAR PREDICTION MODELS IN MINIMUM QUANTITY LUBRICATION

S.Narayana Rao

Dr.B.Satyanarayana

Dr.K.Venkatasubbaiah

DOI

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Abstract

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.

ONLINE TOOL WEAR PREDICTION MODELS IN MINIMUM QUANTITY LUBRICATION

Authors

S.Narayana Rao

Dr.B.Satyanarayana

Dr.K.Venkatasubbaiah

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How to Cite

Dr. S.Narayana Rao. 2011. “. Global Journal of Research in Engineering – B: Automotive Engineering N/A (GJRE Volume 11 Issue B5): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

GJRE Volume 11 Issue B5
Pg. 13- 18

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Submission Received May 21, 2011
Accepted June 19, 2011
Published July 1, 2011

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Article Matrices

Total Score: 113

Country: India

Subject: Global Journal of Research in Engineering - B: Automotive Engineering

Authors: S.Narayana Rao, Dr.B.Satyanarayana, Dr.K.Venkatasubbaiah (PhD/Dr. count: 2)

View Count (all-time): 152

Total Views (Real + Logic): 5489

Total Downloads (simulated): 2816

Publish Date: 2011 09, Wed

Monthly Totals (Real + Logic):

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Total Views: 5489

Total Downloads: 2816

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