Automatic recognition of geometric and topological features from solid models has a great impact on the various levels of integration. The commercial CAD systems contain information of a component which is not suitable for the use in the next level of product life cycle such as process planning. Various solid modeling software's hold the design data in their individual files. The structures of the files differ from each other based on the modeling software. To have a common structure which can communicate with various CAD systems a recognition algorithm using any of the neutral file formats is necessary. This paper presents geometric algorithms to recognize features from various 3D CAD models of prismatic parts. The features are recognized by three approaches; Hhint based approach, Volumetric decomposition approach and Hybrid approach. A program in Java is developed to recognize geometric entities, with their directrix contained in a solid model.. The algorithm developed to extract the information from the IGES translator uses an inference engine which can handle complex feature libraries. The algorithm works efficiently for complex models built using volumetric decomposition as well as hybrid of hint based and volumetric decomposition approaches. The model is reconstructed for validation using the recognized entities.

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In the present work, an attempt is made to develop the numerical models to predict the Material removal Rate (MRR) in a turning process of mild steel specimens using the computational methods namely Multiple regression Analysis MRA and Radial Basis Artificial Neural Network. The machining parameters dealt were Spindle speed, Feed rate and depth of cut. The experiments were conducted in accordance with the Taguchi’s L16 orthogonal array on a conventional lathe using single point HSS Tool. The results as predicted by the computational methods were compared with the experimental results and it was found that a Radial Basis ANN model performed better in comparison with MRA Nomenclature F Feed rate (mm/rev) DOC Depth of cut (mm) N Spindle Speed (rpm) MRR Material Removal Rate (m3/min)