Parameter Selection in Non-Traditional Machining Processes Using a Data Mining Approach
With ever-increasing demands for high surface finish and complex shape geometries on various difficult-to-machine materials, conventional metal removal methods are now being replaced by NonTraditional Machining (NTM) processes. These NTM processes use energy in its direct form to remove material from the work piece surface. They are also cost effective for a wide range of micro- and nano-level applications. For effective utilization of different NTM processes, it is quite important to study their characteristics and material removal mechanisms in order to identify the most significant control parameters affecting the process responses.