Model-based control of machining processes

The goal of this project is to build and deploy the model based control strategies for machining processes and systems of these processes. With the advances in sensing and real-time control technology coupled with Open Architecture Control (OAC) CNC systems, there is a great potential of deploying such control algorithms for various aspects of machining process. Some of these areas include workpiece deflection error control, regenerative chatter control, tool-tip temperature control and control of in-process cutting forces. Model Predictive Control (MPC) algorithms will be deployed using the physics-based process models to yield benefit of forward looking control with better performance. The performance of the control system will be experimentally verified on OKUMA CNCs integrated with NI cRIO real-time system and sensors. 1.0 Introduction: There exist myriad of machining models, including tool wear, cutting force models and physics based flow stress models to describe the flow of material under cutting action. In this section, we will take a brief look at the existing models available. From the very basic tool wear equation given by Taylor, which is used in machining shop cutting speed calculation n VT C = , in the literature there are various extensions of this equation. This includes Taylor’s reference speed based