【Technology Introduction】
This innovative film thickness measurement technique leverages machine learning for rapid and precise structural analysis, significantly outperforming traditional optical methods in efficiency. It is capable of accelerating analysis speeds by at least 20 to 100 times and is ideal for real-time coating process monitoring. Accuracy in machine learning heavily relies on extensive qualified data. Therefore, this approach uses thin-film optical simulations to swiftly generate large amount data sets, addressing the timeliness issue in data acquisition and allowing for the simulation of process variable impacts on film microstructure. Despite minor discrepancies with actual process data, this method enhances the precision of film composition analysis through an effective training data preparation technique. Crucial for real-time monitoring and quality control in various coating processes, it combines machine learning with thin-film optical theory, offering a fast, accurate solution for immediate film composition analysis needs.

Figure 1.Our institution's innovative approach, integrating machine learning with optical theory, enables more precise and rapid analysis of thin-film compositions.

【Project Planning/Technology Application】
This innovative machine learning-based film composition analysis significantly boosts energy-saving membrane processes by ensuring precise thickness control which is crucial for optimal performance. Its real-time monitoring capability allows for immediate adjustments during manufacturing process, maintaining the consistency and quality. Moreover, accurate thickness measurement enhances the membranes' thermal and optical properties so as to improve energy efficiency. Overall, this technology advances the efficiency, quality and sustainability of energy-saving membrane manufacturing.


Figure 2.This advanced machine learning technology for analyzing thin-film composition is utilized to monitor the manufacturing process of energy-saving films.


Figure 3.The AI monitoring system performs real-time analysis of the thin-film composition.

【Future Arrangements】
This technology is applied across various fields, significantly enhancing semiconductor manufacturing by ensuring precise film thickness for optimized circuit performance, which boosts chip precision and yield. In solar cell production, it increases efficiency and longevity through accurate thickness control. For display tech such as electrochromic devices and OLEDs, it improves film uniformity and image quality. In quantum technology, accurate film thickness control is essential. It also enhances sensor accuracy in environmental monitoring. Overall, this technology is crucial for energy-efficient processes and has wide industrial and technological applications, highlighting its significant value.

【Contact Information】
Name: Wu, Tzong-Daw
TEL: 886-3-4711400 Ext. 7346
E-mail：tdwu@nari.org.tw