69 research outputs found
Analysis of surface roughness and hardness in titanium alloy machining with polycrystalline diamond tool under different lubricating modes
Methodology of Taguchi optimization for multi-objective drilling problem to minimize burr size
A comparative study of the ANN and RSM modeling approaches for predicting burr size in drilling
Dry sliding wear of epoxy/cenosphere syntactic foams
Dry sliding wear behavior of epoxy matrix syntactic foams filled with 20, 40 and 60 wt% fly ash cenosphere is reported based on response surface methodology. Empirical models are constructed and validated based on analysis of variance. Results show that syntactic foams have higher wear resistance than the matrix resin. Among the parameters studied, the applied normal load (F) had a prominent effect on wear rate, specific wear rate (w(s)) and coefficient of friction (mu). With increasing F, the wear rate increased, whereas ws and mu decreased. With increase in filler content, the wear rate and w(s) decreased, while the mu increased. With increase in sliding velocity as well as sliding distance, the wear rate and ws show decreasing trends. Microscopy revealed broken cenospheres forming debris and extensive deformation marks on the wear surface. (C) 2015 Elsevier Ltd. All rights reserved
Integrating Box-Behnken design with genetic algorithm to determine the optimal parametric combination for minimizing burr size in drilling of AISI 316L stainless steel
Prediction of surface roughness and cutting forces using RSM, ANN, and NSGA-II in finish turning of AISI 4140 hardened steel with mixed ceramic tool
Comparison of machine learning algorithms for optimization and improvement of process quality in conventional metallic materials
Analysis of the hard turning of AISI H13 steel with ceramic tools based on tool geometry: surface roughness, tool wear and their relation
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