Cloud-Integrated SCADA System for Remote Optimization of Chemical Absorption Tower Performance

Abstract

Efficient operation of chemical absorption towers is essential for achieving optimal mass transfer performance, pollutant removal efficiency, and process stability in industrial gas treatment systems. Conventional supervisory control approaches often face limitations in real-time optimization, remote accessibility, and adaptive process management under dynamic operating conditions. This study presents a cloud-integrated supervisory control and data acquisition (SCADA) system for remote optimization of chemical absorption tower performance. The proposed framework integrates industrial sensors, cloud computing infrastructure, real-time data analytics, and intelligent process control algorithms to enable continuous monitoring and adaptive optimization of absorption tower operations. Key operational parameters, including gas flow rate, liquid circulation rate, temperature, pressure, pH, absorbent concentration, and pollutant removal efficiency, were continuously monitored using interconnected sensing and communication systems. Cloud-based analytics and predictive control models were implemented to process operational data, identify performance deviations, and optimize process conditions for improved mass transfer efficiency and reduced energy consumption. Experimental and simulation analyses demonstrated significant improvements in process stability, pollutant absorption efficiency, and operational responsiveness compared to conventional locally controlled systems. The cloud-integrated architecture also enabled remote supervision, predictive maintenance, anomaly detection, and real-time performance evaluation across distributed industrial facilities. Comparative analysis revealed enhanced resource utilization, reduced operational downtime, and improved environmental compliance through intelligent data-driven control and remote optimization strategies.