The water industry over the years has primarily focussed on upgrading and investing in clean water provision. However, as research into the science and management of clean water services has progressed rapidly, wastewater provision and services has been slower. Focus, though, is now shifting within Industry and Research into wastewater services. The water regulator, Ofwat, for England and Wales demands the Sewerage Undertakers demonstrate efficient management of wastewater systems in order to obtain funding for Capital Investment projects. South West Water, a Water Service Provider and Sewerage Undertaker located in the South West of England, identified a need gap in their asset management strategies for wastewater catchments. This paper will introduce the production of a Decision Support Tool, DST, to help SWW proactively manage their Wastewater Catchments, examining Sewage Treatment Works, Pumping Stations and Networks. The paper will discuss some concepts within the DST, its production, testing and a brief case study. The DST provides a framework for prioritising catchments to optimise investment choices and actions. The Tool ranks catchments utilising Compromise Programming, CP, as well as AHP Pair-wise comparisons for preference weights. The DST incorporates Asset models, a Whole life Costing Module, as well as a Decay and Intervention Module.
Artificial intelligence-based human-centric decision support framework: an application to predictive maintenance in asset management under pandemic environments
