<b>ANALYSIS AND DEVELOPMENT OF OPTICAL SENSORS FOR HIGH PRECISION MONITORING IN SMART MANUFACTURING</b>

<p dir="ltr">Monitoring systems are like the nerves systems of human beings that make it possible for machines to feel the environment, diagnose themselves, and evaluate the products. As we step into Industry 2.0 or even 3.0 era, monitoring data becomes increasingly essential for product quality improvement, system health validation, efficiency improvement, and dynamic control, to name a few. High quality sensors or monitoring platforms are the sources of monitoring data which are used for decision making and control processes. However, with the development of modern technology, sensors with higher sensitivity, precision, and accuracy are required especially for high precision manufacturing processes work under harsh environments. Fiber optic sensors have advantages of compact size, immune to electromagnetic interference, resistance to chemical corrosion, etc. while remaining their general qualities of high resolution, accuracy, and precision. The light-light interaction (interference, resonance, etc.) and light-matter interaction (absorption, surface plasmon, etc.) are two general resources for high precision monitoring. With these resources, we can monitor sub-nanometer scale optical displacement or distance, optical material properties and their response to the environment, or other parameters that can be reflected by these factors. In this dissertation, we will introduce the development of theories and applications of different types of sensors for smart manufacturing using optical technologies. We will mainly focus on the applications of optical sensors for electrochemical machining and semiconductors industry (wafer inspection and thin film deposition). Development of various optical fiber sensors in smart manufacturing applications will also be introduced. For the electrochemical machining process, optical fiber sensors were used to monitor the interelectrode gap and machining depth in real time for an optimized machining control. This research developed the theories to extract the interelectrode gap information from the noisy interference spectrum so that this gap can be remained as the optimized value and the machining depth can be monitored in a high precision and accuracy that outperforms the existing methods. For the wafer inspection applications, we developed systems to monitor the surface contaminations, 3-dimensional profiles, and surface and internal defects of bare silicon wafers to ensure a high-quality manufacturing process. Also, we developed theory and methodologies to monitor the thickness and surface roughness of the thin film deposition process in real-time which further improves the control process, film quality, and finally improves the manufacturing efficiency.</p>