This research will extend and augment previous work on knowledge-based machine fault diagnosis, using artificial neural networks. The starting point of this effort will be the framework of previous machine monitoring research. Analytical modeling of behavioral phenomenon will be carried out to establish quantitative and qualititative relationships of spatial considerations and fault diagnosis models. This modeling will be interfaced to the real world to carry out intelligent monitoring. Intelligent monitoring of machine tools for diagnostic purposes is of great importance in automated manufacturing environments. This work is being conducted in close cooperation with a major manufacturing organization and is likely to yield important results.
