Research
ONLINE TOOL WEAR PREDICTION MODELS IN MINIMUM QUANTITY LUBRICATION
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.
Experimental investigation of microbial contamination of nano cutting fluids with CNT inclusion
The use of cutting fluids in machining is indispensible. However, the microbial contamination of the fluids limits their usage. In the present work nano cutting fluids with carbon nano tube (CNT) inclusion are prepared for use in Minimum quantity lubrication (MQL). Microbial contaminations of these samples are analyzed along with the fluids under stored condition over a span of one month, and the bacteria present in the fluid is isolated and identified to help provide the appropriate remedial actions.
