Model-based identification of manufacturing processes operational dynamic parameters

Abstract

The increasing demands for precision and efficiency of machining ask for development of new control strategies of a machining system based on the identification of its static and dynamic characteristics under operational conditions. This paper presents a procedure for formulating an analytic model of the dynamics of the machining system based on the identification of the system’s parameters during its normal operation. This provides realistic prerequisites for in-process machining system testing. The models based on on-line identification may be used to control dynamic stability in machining and further for implementing a pro-active machining system optimization by correlating model parameters to for instance surface roughness features. This qualitative identification procedure and model parameters are used to formulate a decision rule for ascribing to a given machining process one of possible type of classes. The decision rule is formulated in terms of certain statistical characteristics in such a way to minimize the classification errors.