Failure mode analysis to define process monitoring systems

The high costs of using skilled operators in production processes has built a demand for reduced manning, 'lights out machining' manufacture. Process monitoring systems have become a widely researched area in recent years since there is a need for intelligent systems to replace the manual intervention in existing processes. Furthermore, using modern sensors and signal processing techniques, monitoring systems can obtain more informatio about a process and therefore reduce costs further though maximised life of cutting tools, optimised cutting parameters and reduced scrap or re-work. With many application areas available, such as tool condition monitoring, chatter avoidance or feedback control of cutting parameters, it is not always apparent what the key aspects required by an intelligent monitoring system are. In addition, different machining processes have different demands and limitations for monitoring. This paper considers an analytical approach to define the requirements of a monitoring system. A process failure mode effect analysis (FMEA) is carried out to determine the weaknesses of current production processes. From this analysis, the relationships between failures, causes and effects can be used to populate conditional relationships between process faults and sensor signal features in a monitoring system.