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dc.contributor.authorRaghavan, V.
dc.contributor.authorMurthy, Ch.S.N.
dc.date.accessioned2020-03-31T08:41:52Z-
dc.date.available2020-03-31T08:41:52Z-
dc.date.issued2018
dc.identifier.citationJournal of the Southern African Institute of Mining and Metallurgy, 2018, Vol.118, 3, pp.321-329en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/12608-
dc.description.abstractThe objective of this investigation is to predict rock cuttability from measurements of rock cutting resistance (RCR) during the cutting process and to study the influence of mechanical properties on the depth of cut achieved. Point attack bits with angles of 45 , 50 , 55 , and 65 were used and the experiments were conducted at attack angles of 45 , 55 , and 65 , keeping the rotation speed constant while varying the cutting force and torque during cutting. The depth of each cut was measured and the cut material collected and weighed. The experimental data were compared using an artificial neural network (ANN) and finite element method (FEM) to predict RCR for the measured depth of cut. The results reveal that a 55 attack angle produced the optimum depth of cut. The Southern African Institute of Mining and Metallurgy, 2018.en_US
dc.titlePrediction of cuttability from rock cutting resistanceen_US
dc.typeArticleen_US
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