Case study · Water treatment

Yahong Bridge & Hejian Water Authorities

Centralised plant control and 3D digital twin visualisations

Three screens of a 3D digital twin of a wastewater treatment plant

Yahong Bridge and Hejian Water Authorities are local authorities that own and operate a number of wastewater treatment plants.

The brief

Data trapped on local servers

The existing operational systems sat on local servers spread across the client's treatment plants. Management depended heavily on local operation of each plant, which made asset management inefficient.

Because data was decentralised, large amounts of operational data could not be used to improve processes or provide operational insights. The clients wanted to centralise, digitise and automate their operations to improve safety, resources and asset efficiency across the plants, alongside their existing SCADA systems.

Our strategy

Upgrade the controls, then centralise

CT began by upgrading the client's legacy plant PLCs to Siemens SIMATIC S7 and KingSCADA, bringing them up to the latest supported versions.

The project then centralised all related plant data into the CT IoT platform, including SCADA, asset management data, and chemical and water-quality systems.

Diagram: SCADA, asset management, chemical, water quality, ERP and equipment information feed the platform data ingestors and the business application and 3D visualisation layer

3D digital twin visualisation

Fly around the plant, look through the pipes

The platform supplements the SCADA systems by ingesting and integrating the existing plant operation systems. Its 3D digital twin layer gives the most intuitive and comprehensive view of every integrated plant operation: remote inspections, fly-arounds and look-throughs, and live equipment status, water quality, underground pipework and hydraulic flows.

Three views of the 3D digital twin of a treatment plant

Process driven

Act without leaving the twin

Using the integrated plant data, users can select and control equipment from within the 3D digital twin, retrieve maintenance history, specification sheets and O&M manuals, check critical spares, and raise purchase orders and work orders, all without leaving the platform. Every part of the working plant is covered, including instant historical trend data.

Aerial view of a wastewater treatment plant beside a river

Machine learning

Models trained on the plant itself

Striving for continuous improvement, CT developed customised machine learning algorithms on the aggregated, contextualised data to find plant optimisation opportunities, reduce equipment downtime, and improve energy use and process outcomes.

A laptop showing a 3D digital twin of a water treatment plant

Transformation

What changed.

CT has deployed this solution across five water treatment plants to date. The platform, with its interactive 3D visualisation layer and centralised plant control, has:

  1. 01Improved safety and responsiveness across operations
  2. 02Streamlined communication and information sharing between control rooms and plant staff
  3. 03Optimised plant, process and resource use, including maintenance and staff management workflows

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