Acquisition of adaptive knowledge in case-based reasoning for the online set-point control of industrial process

Kwang Rim Song; Song Ho Kim; Chol Guk Han; Un Sim Ri

doi:10.1117/12.3057800

3 January 2025 Acquisition of adaptive knowledge in case-based reasoning for the online set-point control of industrial process

Kwang Rim Song, Song Ho Kim, Chol Guk Han, Un Sim Ri

Author Affiliations +

Proceedings Volume 13519, Third International Conference on Communications, Information System, and Data Science (CISDS 2024); 1351907 (2025) https://doi.org/10.1117/12.3057800
Event: Third International Conference on Communications, Information System and Data Science 2024, 2024, Nanjing, China

Abstract

In CBR for industrial process control, it is an important issue for improving the efficiency of reasoning to adapt the case base using the online knowledge acquired during operation. In this paper, a new method for online updating and addition of case-base is proposed and applied to set-point control of the rolled cake production process. First, we present an approach for quantitatively evaluating the rolled cake based on sensory quality. Second, we propose an interactive method to acquire knowledge from the operator's experience and adapt the case base according to the behavior of the process and the quantitatively evaluated quality level. The comparative experiments for the validation show that the proposed method results in the 4.1% improvement in the ratio of good products.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kwang Rim Song, Song Ho Kim, Chol Guk Han, and Un Sim Ri "Acquisition of adaptive knowledge in case-based reasoning for the online set-point control of industrial process", Proc. SPIE 13519, Third International Conference on Communications, Information System, and Data Science (CISDS 2024), 1351907 (3 January 2025); https://doi.org/10.1117/12.3057800

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