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Prediction of Grinding Machinability when Grind P20 Tool Steel Using Water Based Zno Nano-Coolant

K., Kadirgama and M., Yogeswaran and S. , Thiruchelvam and M. M., Rahman (2014) Prediction of Grinding Machinability when Grind P20 Tool Steel Using Water Based Zno Nano-Coolant. Jokull Journal, 66 (5). pp. 1-15. ISSN 0449-0576

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Abstract

Grinding is often an important finishing process for many engineering components and for some components it is even a major production process. In this study, prediction model have been developed to find the effect of grinding condition in term of depth of cut and type of grinding coolant. Zinc Oxide (ZnO) nano-coolant was used as a coolant with water as a based liquid. The experiments conducted with grinding depth in the range of 5 to 21μm. Silicon Carbide wheel are used to grind the AISI P20 tool work piece. Artificial intelligence model has been developed using Artificial Neural Network(ANN). Result shows that the lower surface roughness and wheel wear obtain at the lowest cutting depth which is 5 μm. Besides that, grind using ZnO nano-coolant gives best surface roughness and minimum wheel wears compared to grind using normal soluble coolant. The surface roughness have been reduced approximately 47.84% for single pass experiment and 126.1% for multi pass experiment. However, there is no wheel wheel wear obtain for grinding using ZnO nanocoolant. From the prediction of ANN, it can predict the surface roughness closely with the experimental value.

Item Type: Article
Additional Information: IF: 1.604 Dr. Kumaran Kadirgama (K. Kadirgama) Prof. Dr. Md Mustafizur Rahman (M. M. Rahman) Muthusamy Yogeswaran (M. Yogeswaran)
Uncontrolled Keywords: Grinding; Nano-coolant; Surface rougness; Wheel wear
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Dr. Kumaran Kadirgama
Date Deposited: 27 Mar 2014 07:41
Last Modified: 25 Jan 2018 03:16
URI: http://umpir.ump.edu.my/id/eprint/5271
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