In order to make best use of NC machine tools with minimal labor costs, they need to be in operation 24 hours a day without being attended by human operators except for setup and tool changes. Thus, unattended machining is becoming a dream of every modern machine shop. However, without a proper mechanism for real-time monitoring of the machining processes, unattended machine could lead to a disaster. Investigated in this thesis are ways to using PC camera as a real-time monitoring system for unattended NC milling operations.
The state of the NC machining process is modeled as a discrete event system employing the DEVS (discrete event system) formalism. The states of NC machine are defined as a cross product of power on/off, spindle on/off, table moves, alarm on/off, and tool breakage, and then machining process states are defined as Ready, proper Machining, machining with Broken tool, Pause, machine Failure and properly Completed. To detect the states of the machining process, digital image frames and sound signals from the PC camera are processed and analyzed.
An image change detection algorithm has been developed to detect the table movements, and an image segmentation algorithm has been developed to detect cutting tool breakage. Power on/off, spindle on/off and cutting status (machining or not) could be successfully detected from the sound signals. Initial experimentation shows that the PC camera could be used as a reliable monitoring system for unattended NC machining.
