An adaptive statistically based controller for through-feed centerless grinding

The purpose of this research is to develop a statistically based controller that is "self-tuning." High volume manufacturing processes such as through -feed centerless grinding are best controlled with a statistical approach, but traditional methods of statistical control generally rely on fixed para meters that must be determined. These values must be precisely known and th e true physical characteristics they model must remain constant throughout grinding, or traditional statistical control methods may break down. The me an and standard deviation of a process are measures of its accuracy and pre cision. The scheme developed here makes control decisions based on the real -time values of these quantities, This self-adjusting ability can compensat e for changes in machine parameters as they occur.