Abstract
Multi-objective optimization (MOO) of cutting parameters for turning AISI 4340 steel is experimentally investigated by applying principal component analysis with Taguchi method. Five process paremeters, viz cutting environment, nose radius, feed rate, depth of cut and tool type are used to optimize multi quality charecteristics namely surface roughness, MRR, cutting force, tool tip temperature. Also to make the design robust, experimentation is performed under the different leves of spindle vibration. Due to the limitation of Taguchi method for multi optimization, principal component analysis is hybridly used to solve this problem. Image processing in matlab, the unconventional method of measuring tool wear is used. Coated(CVD & PVD) and un-coated cutting tools and the latest lubrication method (Minimum quantity lubrication) are also considered to match the current scenario of manufacturing system. PCA is used to change multiple objectives to a single objective. ANOVA and response table helped to find the optimal setting of process parameters for turning process.
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