The aim of this research project is to develop and evaluate a prototype autonomous grinding system for cylindrical plunge grinding. The system will adjust the operating parameters of the cycle from part to part to reduce cycle time while satisfying part- quality constraints in response to in-process and post-process measurements which characterize the processing conditions and part quality. In order to cope with quantitative uncertainty of the process, the cycle time reduction methodology will employ if-then rules derived from a simulation of the grinding process. Only two in-process sensors will be used, a power monitor and a size gage, which can withstand a harsh production environment. It is shown that information derived from these sensors, together with post-process measurement (inspection) of part quality (i.e., finish and roundness), can be used to characterize the state of the grinding process through process models. The cycle time reduction methodology will be designed and evaluated in simulation. Practical implementation and testing of the autonomous system will be on a commercial internal grinder, retrofitted with electrical drives and sensors and interfaced to a personal computer for data acquisition, system identification, and machine control. The result of this investigation will provide the scientific and technological basis for commercial development of a new generation of grinding systems as well as retrofitting (upgrading) of older grinders.
