Automation of Water Treatment Facilities with Adaptive KPI Integration within a Sustainable Development Strategy

Zaiets, Nataliia; Lutska, Nataliia; Vlasenko, Lidiia; Junge, Volodymyr

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Proceedings of International Conference on Applied Innovation in IT · 2026/04/22 · Vol. 14 · Issue 2 · pp. 203–210

Automation of Water Treatment Facilities with Adaptive KPI Integration within a Sustainable Development Strategy

Nataliia Zaiets, Nataliia Lutska, Lidiia Vlasenko, Volodymyr Shtepa and Stefan Junge

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Abstract

This paper is devoted to the development of engineering methods for integrating a Sustainable Development strategy into automated process control systems of industrial enterprises. The relevance of the study is driven by the need to shift from conventional variables stabilization systems to adaptive control models capable of dynamically responding to environmental and energy-related challenges. An original approach is proposed in which Key Performance Indicators (KPIs) are transformed from reporting tools into dynamic setpoints for local control loops. The authors develop a dynamic model for KPI selection and adjustment based on an integral sustainability compliance index, enabling real-time balancing between environmental requirements - such as wastewater treatment quality indicators - and economic efficiency. The adaptive behavior of the model is achieved through time-dependent weighting coefficients, which are automatically adjusted according to the proximity of monitored process variables to regulatory discharge limits, thereby prioritizing environmental safety under critical operating conditions. Special attention is given to an object-oriented approach that ensures the adaptation of strategic sustainability goals to specific technological units of wastewater treatment facilities. The paper also analyzes the impact of an enterprise’s digital maturity level on the reliability of KPI calculation and proposes the use of soft sensors for forecasting complex environmental variables under conditions of limited instrumentation. The effectiveness of the proposed solutions is validated through simulation modelling of wastewater treatment processes at a dairy processing plant. The results demonstrate that the implementation of the dynamic control model reduces specific energy consumption by 28.1% while fully complying with established environmental regulations. The practical significance of the study lies in the creation of an algorithmic foundation for modernizing industrial process automation systems, enabling the integration of technological reliability with the requirements of the global green transition.

Keywords

Automated Process Control System Key Performance Indicators Sustainable Development Water Treatment Automation Digital Maturity Dynamic Control.

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