![]() No open standards exist that guide and manage sensing, prognostics and health management (PHM), and control at all levels (from the component to the system to the enterprise level). The simultaneous operation of complex systems within the factory increases the difficulty to determine equipment and process degradation, and resolve failures due to ill- or undefined information flow relationships. Complex system, sub-system, and component interactions within smart manufacturing systems make it challenging to determine the specific influences on process performance, especially during disruptions. There is increasing interest to leverage the same data to generate diagnostic (what happened) and prognostic (when something will happen) intelligence at the machine, process, and system levels. Early implementations of smart manufacturing technology have enabled manufacturers to use sensor-rich equipment and process the resulting data to provide decision-makers with information on many performance-related measures (e.g., machine status and utilization) and overall process health. The Prognostics, Health Management, and Control (PHMC) project will deliver methods, protocols, and tools for robust sensing, diagnostics, prognostics, and control that enable manufacturers to respond to planned and un-planned performance changes thereby enhancing the efficiency of smart manufacturing systems. The requirement for standards and guidance becomes more critical as manufacturers become capable of collecting larger volumes of data, the health of their equipment changes, and their processes evolve to meet changing consumer demand. Manufacturers need standards and guidance for how to effectively design, implement, verify, and validate monitoring, diagnostic, and prognostic technologies to enhance factory floor-level decision-making that directly impacts maintenance and control strategies. Industry Forum: Monitoring, Diagnostics, and Prognostics for Manufacturing Operations
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