WBL, along with the global wastewater treatment industry, faces substantial challenges around climate change and the stricter regulations that make transport systems and treatment plants increasingly technically complex. At the same time, there are a growing number of available digital technologies that can convert data streams into valuable insights.
To leverage the opportunities from these technologies and future-proof operations, WBL launched a digital transformation initiative for its wastewater treatment infrastructure. A key aim was to incorporate data science technologies like machine learning and artificial intelligence to help them make better decisions, take appropriate action more quickly, continuously maximise value from infrastructure and optimise the cost-efficiency of operational management.
“Digitisation allows us to maintain better control of the system, and a more efficient system means fewer costs of failure, lower maintenance costs and reduced energy costs,” said Niels Schallenberg, WBL’s Global Director of Digital, Water and Maritime. “Ultimately, this gives us better control of the quality of the treated water we return to the water system.”
As part of this mission, WBL was looking to harness digital capabilities to better manage its complex infrastructure, including the ability to detect leakages faster, gain better insights on water volumes and take a more predictive approach to maintenance.
Leon Verhaegen, WBL’s Senior Project Manager for ICT and Innovation, explained: “We are looking to become a data-driven organisation that understands how all assets function. That way, we can analyse all past events to improve our response and, ultimately, anticipate and understand how our assets will function in future.”
WBL partnered with Royal HaskoningDHV and its Twinn Aquasuite experts to help realise this data-driven transformation. Our approach brought together our domain expertise, software and data capabilities to create an innovative solution. There were 2 elements to the collaboration: