Model Based Prediction and Control of Machining Deflection Error in Turning Slender Bars

Model based control of machining processes is aimed at improving the performance of CNC systems by using the knowledge of machining process to reduce cost, improving machining accuracy and improving overall productivity. In this paper, real time control of the machining process to maintain dimensional quality when turning a slender bar is addressed. The goal is to actively control the machining feed rate to maintain constant and predicable deflection through a combined force-stiffness model integrated to the process controller. A brief review is presented on manufacturing process models, process monitoring, and model based control strategies such as Model Predictive Control (MPC). The main objective of this paper is to outline a method for deploying such models to process control. To demonstrate this, model of the deflection of the workpiece under tool cutting forces is developed. Unknown process parameters have been calculated using series of FEA simulations and verified with basic experimental data. A simple but effective control strategy has been formulated and simulated. In the initial results, the diameter of bar is maintained within 1.04% error with controller as opposed to up to 4% error without controller. Ultimately, the goal is to deploy such control strategies in the industrial control system. With the continual development in physical understanding of machining processes and affordable computing technology (both software and hardware) coupled with Open Architecture Control (OAC) applied to CNC machine tools, such approaches are now computationally feasible. This will be an enabling factor to deploy model based control in an industrial environment. The last section discusses the proposed hardware architecture to achieve this. The paper concludes with a brief plan for the future work and a summary.