Developing Gaussian Process Model to Predict the Surface Roughness in Boring Operation

In machining industries, achieving better surface finish of a product is very essential. Surface finish is important in terms of tolerances, it reduces assembly time in mating surfaces which results in overall cost reduction. In this work, three cutting speeds, three feed rates and three depth of cuts were used in boring operation. During the boring operation, the accelerometer was fixed on the tool post to record the vibration signal. The surface roughness was measured using perthometer. Finally the Gaussian Process regression model has been developed to predict the surface roughness based on tool post vibration and cutting conditions. Keywords— Surface roughness prediction, Gaussian Process, Boring operation, Vibration.