ABSTRACT
Hard Turning provides an alternative to grinding in some finishing applications. Average Surface Roughness Ra has been widely used in industry to establish surface texture needed for a given application. It is known that the single parameter Ra is inadequate to define the functionality of a surface texture. The quality of a surface can be determined by the nature of its interaction with another surface. Thus a surface with significant peaks will not make as good a bearing surface as a surface with deep valleys and low peaks. Two different surfaces with similar values of Ra can behave differently under fatigue loading conditions. 3-D visualization of expected surface texture will facilitate optimization of machining parameters to produce function-specific surfaces. The advantages and shortcomings of some current surface texture prediction models are discussed. A new method based on neuro-fuzzy techniques is proposed. Optimization using some 3-D surface parameters was carried out and compared with the results of those obtained using 2-D parameters.
ACKNOWLEDGMENT
This project was funded by Dana Spicer Driveshaft Inc. and is part of a comprehensive project on providing an alternative process to finish grinding operations. Mr. Sudheer Kodem, The University of Toledo and Mr. Ranganath Kothamasu, The University of Cincinnati played a vital role in combining the manufacturing and computational aspects.