Panel 3: Actualising the

Benefits of Digital Twins9:10-9:55 pm BST

Moderator: Bob Taylor, CEO (Portsmouth Water)

Nigel Watson, CIO (Northumbrian Water)

Sean O'Boyle, Asset Information Development Manager

(Northern Ireland Water)

Celine Hyer, Water Conveyance Practice Leader, Senior Vice

President (ARCADIS)

Patrick Bonk, Software Solutions Lead – Asia Pacific (Innovyze)

Alberto Deponti, Product Manager (Siemens)

Digital Twins at NWG

The NWG

Digital

Water

Company

Vision

The NWG

Digital

Water

Company

Vision

SMART NETWORKSWe adopt smart technologies to give us a deep understanding of our current performance and simulate future scenarios, enabling us to drive more targeted improvements to our KPIs.

Initial Analysis

Visit Optimisation

Asset Reliability

Power Use

Flood Risk

LTRAcdnt

Low Press

Taste odour

CMEX

Travel Time

CSO Spills

ChemUse

• Data ScienceVisit Optimisation

• Digital TwinAsset Reliability

• DiscardPower Use Digital Twin Model

Site 4

Site 3

Site 2

Site 1

Roll out to other similar Assets

Digital Twin

Pipeline

Digital Twin Model

SCADA SensorData Lake

Maximo Mobile App

Digital Twin

Integration

Digital Twin

Roll Out Once we have a twin built we can rapidly roll out to

other similar assetsthat have

equivalent data available

Customer Digital Twin

• Reducing water poverty

• Understanding & influencing CMEX

Triad Power Use Reduction

• Reduce energy use during high cost periods

• Driving opex efficiency

Sewage Pumping Station Predictor

• Early warning of SPS failure / identification of sub-optimal performance

• Reducing pollution incidents

Aquadapt - Distribution System Optimisation

• Optimising network distribution based on tariffs and treated water costs

• Optimised pumping schedule leading to reduced costs

CSO Spill Reduction

• CSOs at risk of operating outside consent

• Positive impact on pollution incidents & bathing water quality

Digital Twin Projects

Maturity ➔

Smart Water Networks ForumActualising the Benefits of Digital Twins

Sean O’Boyle

Asset Information Development Manager

18/11/2019 WB00006-18686

What is a Digital Twin?

Digital Twin

Common Data Environment

Smart Data

BIM

GIS

Hydraulic

Modelling

Architecture

System of Record

Visualisation

SCADA

Telemetry

Asset RegisterCAD

Smart Processes

Finances

Asset Data Definitions

Governance

Protocols

Our key challenge

© BlueMikeSpecial | Minecraft

© Pinterest

Decision

Support

Work

Management

Asset

Maintenance

Scheduling

Rapid

Response

Business

Analytics

Location

Intelligence

Reactive

Work

Scheduling

Cost to

Serve

£Capital

Delivery

Systems Integration

(e.g. Source to Street,

Street to Sea, RAPID,

Telemetry, DIAMOND)

Outcomes

Are Asset Management and BIM a Natural Fit?Celine Hyer, PE, IAM

Senior Vice President

Asset Management Focuses on Decision Making Over the Full Life Cycle of the Asset

IAM Asset Management Model • BIM historically has focused on only on the design phase of an asset

• Capabilities exist for much more:• Shared knowledge resource for asset

attributes, O&M requirements, performance, etc.

• Collaboration platform for decision making

• Digital representation of the physical and functional characteristics of a facility

First Step is Alignment Between AM and BIM

• Asset Hierarchy

• Asset Definitions

• Attributes

Use or disc losure of data contained on this sheet is subject to the restr iction on the title page of this proposal or quotation.

Maintenance CMMS

OperationsEOM

3D BIM

Case Study: Chlorine System Information Management

• 3D Model: Develop a 3D Building Information Model (BIM)

• Operations: Collect and populate the web-based Electronic O&M Manual (EOM) with operations and maintenance information using WordPress

• Maintenance: Review and update preventive maintenance tasks and schedules in the CentralSquare Lucity Computerized Maintenance Management System (CMMS)

• Information Management and Access: Integrate 3D BIM with existing CMMS and EOM

Integrating Asset Creation and O&M

Benefits

• Effective one-stop access to asset information; connects digital asset with O&M information

• Reduces duplicate efforts

• Better understanding of managed asset

• Integrate planning, creation, operations and maintenance phases of the asset lifecycle

Plan / Create

Dispose

Maintain

Operate

Adoption of Digital Twins

Patrick Bonk, Software Solutions Lead

P.Eng., M.Eng.

Aligning Operational Models, Analytics & AI

Digital Twins for the Problem You’re Solving

PRESENT/NOWNow & last 24-48 hours for evolving conditions.Real-time Optimisation, Asset Performance, Incident & Day-to-Day Management

PASTHistorical Analysis 1-24 hours, 1-24 months for near, longer term and seasonality considerations Compliance Reporting, Pump Performance, Maintenance Programs, Asset Condition & Capacity.

FUTUREForecast & Predictive Recommendations 4-8 hours at level of the asset, 5-days for network level.Contingency Planning, Crew Safety, Emerging & Evolving Risk, Energy Reduction & Maintaining Compliance

Wellington Water digitises preventative asset maintenance with Cardno

Innovyze Operational Analytics Approach:A data modelling application with workspaces open to the end

user’s expertise and unique data needs to inform operational

and network performance decision making.

KPIs:

• Continuous monitoring & testing of pump performance

• Reduce Energy Opex

Highlights:

• Eliminate antiquated Excel spreadsheet calculations and free up time for analytics and performance monitoring.

• Utilise internal and external expertise.

• Streamline, standardise and scale analysis.

USER STO RY

Thames Water predictive alerts for sewer crew safety & deployment

Highlights: • Trusted alerts to support health and safety decisions on person entry

into live sewers.

• Streamlined decision support frameworks to articulate complexity of crew safety.

• Forecast rainfall data available and continually improving for predictive use cases.

KPIs:

• Spatial Rainfall predictions with 5-7 day and 4-6 hour forecasted alerts.

• Discernment on hydraulic results for individual assets 4-6 hours in advance.

Innovyze Operational Model Approach: Predictive Decision Support tool provides a future state of networks with a degree of trust to protect workers.

USER STO RY

Innovyze AI Approach: Control aeration blowers to optimise reactor dissolved oxygen levels while satisfying effluent compliance limits

Emagin AI was able to learn their complex process

Providing significant OPEX cost savings

Canadian city optimises energy costs while maintaining compliance with Innovyze AI

KPIs:

• Reduce energy OPEX

• Maintain effluent compliance limits (Ammonia, TSS, COD)

Highlights:

• Value Based, ROI of 6-Months

• Predictive, Real-Time Recommendations

• Saved 29% in Energy Costs while meeting stricter compliance

USER STO RY

Ease of Adoption

+ Self Adjusting AISelf adjust to system & environmental changes in real-time.

+ Remote Install & Remote AccessWorking from home innovation is happening out of necessity.

+ Conserve Costs on your Existing BudgetReduction of Energy & Chemical Costs while maintaining compliance without having to request new budget.

Continuous digital thread

for the water industryAlberto Deponti

Simcenter Flomaster Product Manager

alberto.deponti@siemens.com

Where today meets tomorrow.

.

Unrestricted © Siemens 2020

Unrestricted © Siemens 2020

2020-07-21Page 25 Siemens Digital Industries Software

Continuous digital thread for the water industry

Ideation

Operation

Realization

“Static and dynamic hydraulic modeling of the area’s town water supply

system performed in Simcenter Flomaster assists in optimizing critical

plant components and result in lower life cycle costs and more reliable

system operation.”Terry Kehoe, Director, Kehoe Myers Consulting Engineers

Jurgen Sprengel, Principal, JS Pump and Fluid System Consultants