Abstract
Advanced sensing and control are strategically as important to manufacturing as are design and new product. Through the application of advanced sensor technologies, more detailed information about manufacturing plants is obtained. Although evaluation and improvement have been made on individual machine performance based on sensor data, there is still no data-driven system model for the identification of system inefficiencies and process optimization. In this paper, we build a mathematic model based on sensor data to describe the production dynamics. Furthermore, a systematic methodology is further developed to perform real-time diagnosis and prognosis on permanent production loss and conduct analysis on system robustness to disruption events, which can enhance overall system efficiency by increasing system responsiveness.
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