Influence of optimization techniques and nano surface coating materials on microstructure of iron-nickel-chromium alloy using wire EDM process

This research proposes developing the new hybrid optimization techniques for getting optimized wire EDM machining parameters and analysing the performance and microstructure of hybrid treatment alloy 20 material (high-velocity oxygen fuel spraying and plasma nitriding on iron-nickel-chromium alloy) after machining in wire EDM. The devising optimization is carried out using back-propagation neural networks (BPNN) integrated with fuzzy logic techniques. Taguchi L27 method uses optimized parameters in 3 factors and 3 level methods to BPNN wire EDM processing parameters. Those processing parameter errors are controlled by applying fuzzy logic system in hybrid optimization techniques. The hybrid optimization provides best results (±5% error) while comparing other techniques. This proposal was started with research review of defined factors and BPNN parameters level for hidden layer number, learning algorithm, neurons numbers, and so on. The analysis of variance (ANOVA), analysis of means (ANOM) and signal to noise (S/N) ratio have been used to identify Taguchi results. The BPNN techniques have been employed significantly to tackle hidden layer's uncertain parameter structures. The fuzzy logic controllers in general have been designed engaging the relations between system performance and factor through error method calculation. The microstructure analysis showed that the no evidence was found of recast layer formation on hybrid treated material after machining in wire EDM due to compressive stress and compound layer on material surface.