Fuzzy Neural Network and Wavelet for Tool Condition Monitoring
To reduce operating costs and improve product quality are two objectives for the modern manufacturing industries, so most manufacturing systems are fast converting to fully automated environments such as computer integrated manufacturing (CIM) and flexible manufacturing systems (FMS). However, many manufacturing processes involve some aspects of metal cutting operations. The most crucial and determining factor to successful maximization of the manufacturing processes in any typical metal cutting process is tool condition. It would seem be logical to propose that tool condition monitoring (TCM) will inevitably become an automated feature of such manufacturing environments. Due to failure, cutting tools adversely affect the surface finish of the workpiece and damage machine tools; serious failure of cutting tools may possibly endanger the operator’s safety. Therefore, it is very necessary to develop tool condition monitoring systems that would alert the operator to the states of cutting tools, thereby avoiding undesirable consequences .