<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Driven by artificial intelligence technology and the popularization of the “Internet +” concept, many chemical enterprises have gradually transformed to production automation. However, regarding automation control, these enterprises often still have certain deficiencies. Because of this, this paper proposes an ant colony optimization algorithm to find the best path for the automation control of chemical enterprises. It builds a chemical automation control system based on it. This system mainly focuses on monitoring and managing various aspects of chemical enterprises. After introducing this control system, it conducts in-depth research and Analysis on the production capacity and equipment safety of enterprises. Test results show that the chemical control system constructed in this paper can effectively maintain the standard output of the production equipment in the interval of [16,25] per second, and the maximum output per hour is up to 1017. At the same time, the quality of the production products of the PPM index value continues to be at a high level. In addition, the automated control system can provide early warning of potential equipment hazards by monitoring different levels of current fluctuations. The chemical automation control system proposed in this paper shows excellent performance in detecting and controlling the automated production process in chemical companies.</p>
</abstract>

Driven by artificial intelligence technology and the popularization of the “Internet +” concept, many chemical enterprises have gradually transformed to production automation. However, regarding automation control, these enterprises often still have certain deficiencies. Because of this, this paper proposes an ant colony optimization algorithm to find the best path for the automation control of chemical enterprises. It builds a chemical automation control system based on it. This system mainly focuses on monitoring and managing various aspects of chemical enterprises. After introducing this control system, it conducts in-depth research and Analysis on the production capacity and equipment safety of enterprises. Test results show that the chemical control system constructed in this paper can effectively maintain the standard output of the production equipment in the interval of [16,25] per second, and the maximum output per hour is up to 1017. At the same time, the quality of the production products of the PPM index value continues to be at a high level. In addition, the automated control system can provide early warning of potential equipment hazards by monitoring different levels of current fluctuations. The chemical automation control system proposed in this paper shows excellent performance in detecting and controlling the automated production process in chemical companies.

Chemical Automation Control Based on Intelligent Optimization Algorithm in the Background of “Internet+”

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Driven by artificial intelligence technology and the popularization of the “Internet +” concept, many chemical enterprises have gradually transformed to...

Chemical Automation Control Based on Intelligent Optimization Algorithm in the Background of “Internet+”

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 12. Jan. 2024

Akzeptiert: 21. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0528

Schlüsselwörter
Ant colony optimization algorithm, PPM, Monitoring management, Automated control

© 2024 Xianglong Huang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Chemical Automation Control Based on Intelligent Optimization Algorithm in the Background of “Internet+”

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 12. Jan. 2024

Akzeptiert: 21. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0528

SchlüsselwörterAnt colony optimization algorithm, PPM, Monitoring management, Automated control

© 2024 Xianglong Huang, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Ant colony optimization algorithm, PPM, Monitoring management, Automated control