Dynamic Failure Risk Assessment of Wastewater Treatment and Reclamation Plant: An Industrial Case Study

Due to the growing scarcity of water resources, wastewater reuse has become one most effective solutions for industrial consumption. However, various factors can detrimentally affect performance a treatment plant (WWTP), which is considered risk not fulfilling effluent requirements. Thus, ensure quality treated wastewater, it essential analyze system failure causes and their potential outcomes mitigation measures through systematic dynamic assessment approach. This work shows how Bayesian network (DBN) be effectively used in this context. Like conventional (BN), DBN capture complex interactions between contributory factors. Additionally, forecast upcoming likelihood using prediction inference. proposed methodology was applied WWTP Moorchekhort Industrial Complex (MIC), located center Iran. A total 15 years’ time frame (2016–2030) been work. The first six data have develop model identify crucial that are further reduce remaining nine years. increased from 21% 42% 2016–2021. Applying decrease 33% 9% 2022–2030. showed capability management help WWTPs’ managers operators achieve better higher reclaimed quality.