Jitchaiyapoom, Tawesin and Panjapornpon, Chanin and Bardeeniz, Santi and Hussain, Mohd Azlan (2024) Production Capacity Prediction and Optimization in the Glycerin Purification Process: A Simulation-Assisted Few-Shot Learning Approach. Processes, 12 (4). p. 661. ISSN 2227-9717, DOI https://doi.org/10.3390/pr12040661.
Full text not available from this repository.Abstract
Chemical process control relies on a tightly controlled, narrow range of margins for critical variables, ensuring process stability and safeguarding equipment from potential accidents. The availability of historical process data is limited to a specific setpoint of operation. This challenge raises issues for process monitoring in predicting and adjusting to deviations outside of the range of operational parameters. Therefore, this paper proposes simulation-assisted deep transfer learning for predicting and optimizing the final purity and production capacity of the glycerin purification process. The proposed network is trained by the simulation domain to generate a base feature extractor, which is then fine-tuned using few-shot learning techniques on the target learner to extend the working domain of the model beyond historical practice. The result shows that the proposed model improved prediction performance by 24.22% in predicting water content and 79.72% in glycerin prediction over the conventional deep learning model. Additionally, the implementation of the proposed model identified production and product quality improvements for enhancing the glycerin purification process.
| Item Type: | Article |
|---|---|
| Funders: | Kasetsart University, Faculty of Engineering, Kasetsart University, Center for Advanced Studies in Industrial Technology, Center of Excellence on Petrochemical and Materials Technology |
| Uncontrolled Keywords: | glycerin purification; few-shot learning; production optimization; simulation-assisted |
| Subjects: | T Technology > TP Chemical technology |
| Divisions: | Faculty of Engineering > Department of Chemical Engineering |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 14 Oct 2024 08:46 |
| Last Modified: | 14 Oct 2024 08:46 |
| URI: | http://eprints.um.edu.my/id/eprint/45362 |
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