A typical manufacturing job shop comprises of legacy machine tools, new (modern) machine tools, material handling devices, and peripheral manufacturing equipments. Automated monitoring of legacy machine tools has been a long-standing issue for the manufacturing industry primarily because of the computer numeric controller (CNC) closed architecture and limited external communication functionality. This paper describes a non-invasive methodology and development of a software application to monitor real-time machine status, energy usage, and other machining parameters for a legacy machine tool using power signal analysis. State machine algorithm is implemented to detect tool changes and part count. The system architecture, implementation, benefits, limitations, and future work needed for the legacy machine tool monitoring application is explained in detail.
Reference: Legacy Machine Monitoring Using Power Signal Analysis; Deshpande A., Pieper R.; Proceedings of the ASME 2011 International Manufacturing Science and Engineering Conference, Corvallis, OR.
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