Real-Time Process Optimization of Seawater RO Desalination Using Industrial PLC Automation and Digital Twin Simulation

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Authors: S.Mohammed Ismail, P.Venkateswari, Dr T.Sivakumar, C.Ramesh, P.Vanitha
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Abstract

Digital Twin technology represents a significant advancement in sustainable water management for seawater desalination plants. This paper outlines a real-time optimized structure that enhances operational efficiency, reduces energy usage, improves reliability, and ensures compliance. Key features include IoT devices for data collection, PLC programming and HMI design for modeling and anomaly detection, and optimization algorithms for decision support. In this paper, various key elements related to the automation of Reverse Osmosis (RO) based seawater desalination treatment plants are discussed, including pretreatment, desalination, posttreatment, chemical usage and dosing, activated purification processes, brine disposal, pH adjustment, and demineralization, utilizing multiple small control systems within the proposed automation system. PLCs (Programmable Logic Controllers) manage the desalination treatment plant by monitoring pumps, closures, and other devices, executing commands, and controlling processes based on sensor data and algorithms. A control panel was created using a Digital Twins program to facilitate the monitoring and control of seawater desalination, adhering to specified requirements. This study discusses the communication between local PLC controllers and Digital Twins applications in a sea water desalination plant. It emphasizes the use of a Functional logic diagram for pump control and the importance of the alarm and monitoring system for managing key components, such as supply lines and reservoirs. The findings suggest that Digital Twins can enhance smart water desalination infrastructure by enabling real-time process optimization, serving as a valuable resource for utilities, engineers, and legislators aiming for more efficient and sustainable sea water management.

Fields of Study & Subjects

Industrial Automation and Control Systems Digital Transformation in Industry Advanced Control Systems Optimization

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
18 January 2026