Methodology for Continuous Infeed Cylindrical Plunge Grinding

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This project will develop a new methodology for optimal control of cylindrical plunge grinding cycles. In this type of grinding, a cycle generally consists of a few discrete infeed rates applied sequentially. The consideration of a limited number of discrete infeed rates makes the problem tractable and allows the cycle to be readily implemented with older machine control techniques (e.g., ladder logic). But it limits the extent of cycle-time reduction by optimization. The foundation of the methodology will be Model Predictive Control (MPC) where the value of infeed rate at each sampling instant is determined according to its projected effect on the process and part quality constraints. However, the basic form of MPC will not be adequate for this application because of the inherent uncertainty of the grinding process. To enhance its robustness, this control will be integrated with Recursive Constraint Bounding so as to incorporate conservatism into the optimization process.The optimal control methodology is able to provide a cycle with continuously varying infeed rates. This should lead to significant savings in cycle time and cost, as well as being more suited to implementation of the control with open-architecture controllers.