Symbiosis of Modelling and Sensing to Improve the Accuracy of Workpieces in Small Batch Machining Operations

In this paper a direction of research is proposed by the authors, using comprehensive analyses, aimed at better control of the accuracy of workpieces in small batch machining operations. It is based on a symbiosis of dedicated research on modelling of all the factors that may influence workpiece precision and the use of appropriate information obtained during actual production, such as that which might be obtained from appropriate sensor signals. It is suggested that the future modelling research should be carried out in a more systematic way, from fundamental/theovetical study to application. These should be special focus on the transition of generic models into applied ones. In addition to classical predictive models, a new concept - knowledge-based control model is presented. The characteristics of various control approaches are compared from the viewpoint of machining precision. Intelligence techniques and the synthesis of advanced technologies are stressed. The aspects robustness and optimisation of machining processes are also discussed. An intelligent machining system, which combines modelling and sensing, has been designed for improving the accuracy of workpieces in small batch production. It is part of the work of the RIMAS project-Robust Imelligent MAchining System - currently being conducted at Delft University of Technology.