Self-tuning process monitoring system for process-based product

The hidden qualities of a product are often revealed in the process. Subsurface material damage, surface cracks, and unusual burr formation can occur during a poorly controlled machining process. Standard post process inspection is costly and may not reveal these conditions. However, by monitoring the proper process parameters, these conditions are readily detectable without incurring the cost of post process inspection. In addition, many unforeseen process anomalies may be detected using an advanced process monitoring system. This work created a process monitoring system for milling machines which mapped the forces, power, vibration, and acoustic emissions generated during a cutting cycle onto a 3D model of the part being machined. The hyperpoint overlay can be analyzed and visualized with VRML (Virtual Reality Modeling Language). Once the Process Monitoring System is deployed, detailed inspection may be significantly reduced or eliminated. The project deployed a Pro-Engineer to VRML model conversion routine, advanced visualization interface, tool path transformation with mesh generation routine, hyperpoint overlay routine, stable sensor array, sensor calibration routine, and machine calibration methodology. The technology created in this project can help validate production of WR (War Reserve) components by generating process signatures for products, processes, and lot runs. The signatures of each product can be compared across all products made within and across lot runs to determine if the processes that produced the product are consistently providing superior quality. Furthermore, the qualities of the processes are visibly apparent, since the part model is overlaid with process data. The system was evaluated on three different part productions