Cutting Forces in Drilling Operation: Measurement and Modeling for Medium-scale Manufacturing Firms

Abstract

Advanced manufacturing systems often caters to rapidly changing product specification determination by the continuously increasing productivity, flexibility and quality demands. The estimation of cutting forces is mandatory to select tools and accessories for machining. Complex interrelationships exist between process parameters and these forces. In the present work, the applicability and relative effectiveness of artificial neural network based model has been investigated for rapid estimation of cutting forces. The results obtained are found to correlate well with the actual experimental readings of cutting forces. Experiments were conducted at different process parameters of cutting in Drilling operation. The proposed work has wide application in selection of tools and online tool wear monitoring.