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A model for a “characteristic grain” consisting of the superimposition of a large and a small wavelength has been introduced. The large wavelength representing the grain has been used in establishing the elastic deflection of the grain. Due to the elastic deflection, the small wavelength representing the cutting edges cuts a smaller “characteristic groove” on the surface, which provides a prediction of the rms value of the ground surface. Specific energy of grinding can also be predicted. The theoretical expressions for the deflection of the grain and for the rms values are developed from this model and found to agree very well with the values obtained by experiments. With an online measurement of the wheel profile, this approach has potential in computer control of grinding.

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This paper initiates a new approach to the analysis of surface generation, by fitting mathematical models to wheel and work surface profiles under actual grinding conditions. Data Dependent Systems (DDS) methodology has been used to model work surface profiles in the longitudinal (across the width of cut) and transverse (along the direction of feed) directions, and the wheel profile along the longitudinal direction. A model for the “characteristic grain” consisting of the superimposition of a large and small wavelength is used to provide an indication about the grain-wear and surface roughness. The large wavelength representing the grain has been used in establishing the deflection of the grain. Due to the elastic deflection, the small wavelength representing the cutting edges cuts a smaller groove, which provides a prediction of the rms value of the ground surface in the transverse direction. From the wavelength decomposition of longitudinal profiles, the superimposition of components due to topography of the wheel and kinematic conditions have been identified. The mechanism that leads to such a superimposition is analyzed. Experimental verification of the theory and predictions is given.

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