Fang, Ming-ChunMing-ChunFangLee, Hao-YehHao-YehLeeHsieh, Cheng-TingCheng-TingHsiehHsieh, Yu-ChenYu-ChenHsiehLee, Chih-LungChih-LungLeeLin, Shih-ChiehShih-ChiehLinHuang, Tzu-HsienTzu-HsienHuangChou, Wei-TiWei-TiChouJeffrey Daniel Ward2025-06-172025-06-172025-11-18https://www.scopus.com/record/display.uri?eid=2-s2.0-105005258791&origin=resultslisthttps://scholars.lib.ntu.edu.tw/handle/123456789/730120The increasing demand for automation and autonomy in fields such as autonomous driving, smart homes, and power grid management has highlighted the crucial role of cyber physical systems (CPS) in the modern economy. Advances in electronic technology and artificial intelligence (AI) have made CPS implementation more accessible and affordable. However, its application in chemical processes is still rarely reported in the open literature. Chemical processes often involve sparse and monotonous operating data, which limits the development and application of data-driven models. To address this challenge, this work develops the process model using Aspen Plus, leveraging first-principles modeling for better extrapolation performance. A commercial-scale coke oven gas (COG) desulfurization process is used as a case study. An operation guidance system based on the Aspen Plus process model is created to provide optimal scrubbing liquid and steam flowrates based on measured inlet COG and coal water properties. This system enhances energy efficiency without compromising regulations on purified COG and wastewater composition. Additionally, a process improvement strategy is proposed, which, according to simulations, could reduce the outlet COG H2S concentration by over 70 % while maintaining compliance with wastewater regulations. This strategy does not rely on expensive catalysts or adsorbents, making it an attractive solution for reducing the steel industry's environmental impact.Coke oven gasCyber physical systemIndustry 4.0Internet of thingsSmart manufacturingSteel industry[SDGs]SDG6[SDGs]SDG7[SDGs]SDG9[SDGs]SDG12journal article10.1016/j.seppur.2025.133533