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FinalPPTDigitalTwinANWLMCE_1.pptx

Project Title: Digital Twin for Water Company Assets Project Code: Digital Twin A NWL MCE

Client: Northumbrian Water Group (NWG)

Acronyms:

Northumbrian Water Ltd - NWL

Introduction of Project Members

Name: Abhilash Mukherjee

Experience: 8+ years of experience in academics and site

Role: Project Manager

Name: Atif Sikandar Memon

Experience : 2 years of experience in site work

Role: Communication Lead

Name: Tejaswini Gurram

Experience: Seismic analysis graduate project

Role: Researcher

Objectives

Conducting an extensive literature review to establish feasibility and DT applicability for NWL

Drawing lessons and strategy from relevant case study to propose DT infrastructure and application in NWL

Subject

Evidence

Data

Research

Criteria

Knowledge

Conclusion

Method

Case study

Images and diagrams courtesy – creative commons and author

Objectives (contd.)

Proposing a final roadmap and implementation strategy for DT in NWL

Defining and setting out Common Data Environment (CDE) requirements

Images and diagrams courtesy – creative commons and author

Project implementation year

2.The stage of DT implementation

3.Scale of the company

Howden sewage water treatment plant scale

4.Authenticity and availability of data

Concept and planning

Stage 1

Stage 2

Final implementation

Parameters for Case Study Selection

Must be a case study for potable or waste water

Images and diagrams courtesy – creative commons and author

Selected Case Studies

Global Omnium, Valencia (Spain) [2]–[4]

North City Pure Water Facility, San Diego, California (USA) [7], [8]

Project Future City Flow – Gothenburg sewer network (Sweden) [9]

Comparative case studies on digital twin with respect to NWL

VCS (Denmark) [2]

Canal of Calais (France) [5], [6]

Organisational structure and hierarchy [1]

Potential benefits of DT in water industry [1]- [8]

Case Study Findings – Summary

Case Study Findings – Summary (contd.)

Potential challenges in DT implementation [2], [7], [9], [10]

Harsh Environment

Preventive Maintenance

Alarm

Global Unique Identifier (GUID)

Large data integrity and gaps

Dedicated Cloud server

CDE checks

Large number of data points, format and stakeholders

Organisational structure and dedicated teams

Colorful and intuitive user interface

NWL

GEGGE

GENERAL MANAGER

OPERATION TEAM

TRAINING TEAM

INFORMATION TEAM

BUSINESS ANALYST

Project Manager

Architect

Sensor Data

Collecting Team

Consultancy Team

BIM Manager

Maintenance

Maintenance Team

Inspection Team

Project coordinator

Finance Team

Team leader

Accountant

9**

Design Team

Software experts

BIM Coordinator

BIM Specialist

Organizational Structure In Detail

Images and diagrams courtesy – creative commons and author

Stakeholders Involved In The Implementation Of Digital Twin

Images and diagrams courtesy – creative commons and author

Common Data Environment

Images and diagrams courtesy – creative commons and author

Images and diagrams courtesy – creative commons and author

Detailed responsibility can be found in the attachment along with other deliverables

Sample Responsibility Matrix

Proposed Roadmap

Images and diagrams courtesy – creative commons and author

Making up a DT core team in NWL (as per recommendations)

Deciding upon the initial asset and scale of DT implementation

Gathering, categorizing and preparing the 2D drawings and data for specific asset

Two-stage open book procurement stage – cost – collaboration (as per GOV.in recommendations)

Training, Planning and designing the project details in collaboration

Establishing the proposed CDE (as per recommended stakeholder relations and CDE framework)

Acquiring the required infrastructure

Unanimous agreement and understanding of responsibility matrix (as per recommendations)

Following all the steps in responsibility matrix for rest of the steps

Recommendations

1

2

3

4

Pilot project requirements, fund, team and available data discussion

Create a separate fund and team as per the responsibility matrix

A site visit to any one of the companies who has already implemented DT

Follow all the steps in the roadmap for cost and quality efficiency

[1] P. Conejos Fuertes, F. Martínez Alzamora, M. Hervás Carot, and J. C. Alonso Campos, ‘Building and exploiting a Digital Twin for the management of drinking water distribution networks’, Urban Water Journal, vol. 17, no. 8, pp. 704–713, Sep. 2020, doi: 10.1080/1573062X.2020.1771382.

[2] A. N. Pedersen, M. Borup, A. Brink-Kjær, L. E. Christiansen, and P. S. Mikkelsen, ‘Living and Prototyping Digital Twins for Urban Water Systems: Towards Multi-Purpose Value Creation Using Models and Sensors’, Water, vol. 13, no. 5, p. 592, Feb. 2021, doi: 10.3390/w13050592.

[3] P. Conejos Fuertes, F. Martínez Alzamora, M. Hervás Carot, and J. C. Alonso Campos, ‘Building and exploiting a Digital Twin for the management of drinking water distribution networks’, Urban Water Journal, vol. 17, no. 8, pp. 704–713, Sep. 2020, doi: 10.1080/1573062X.2020.1771382.

[4] E. Universitat Politècnica de València, ‘Universitat Politècnica de València’, ing.agua, vol. 18, no. 1, p. ix, Sep. 2014, doi: 10.4995/ia.2014.3293.

[5] R. Ranjbar, E. Duviella, L. Etienne, and J.-M. Maestre, ‘Framework for a digital twin of the Canal of Calais’, Procedia Computer Science, vol. 178, pp. 27–37, 2020, doi: 10.1016/j.procs.2020.11.004.

[6] M. Callcut, J.-P. Cerceau Agliozzo, L. Varga, and L. McMillan, ‘Digital Twins in Civil Infrastructure Systems’, Sustainability, vol. 13, no. 20, p. 11549, Oct. 2021, doi: 10.3390/su132011549.

[7] J. M. Curl, T. Nading, K. Hegger, A. Barhoumi, and M. Smoczynski, ‘Digital Twins: The Next Generation of Water Treatment Technology’, J Am Water Works Assoc, vol. 111, no. 12, pp. 44–50, Dec. 2019, doi: 10.1002/awwa.1413.

[8] M. F. Mesquida, ‘Digital Twin in Water Distribution Networks’, Master’s thesis, Universitat Politècnica de Catalunya, Lisbon, 2021.

[9] B. Valverde-Pérez, ‘Operational digital twins in the urban water sector: case studies’, case studies, p. 17.

[10] J.-D. Therrien, N. Nicolaï, and P. A. Vanrolleghem, ‘A critical review of the data pipeline: how wastewater system operation flows from data to intelligence’, Water Science and Technology, vol. 82, no. 12, pp. 2613–2634, Dec. 2020, doi: 10.2166/wst.2020.393.

References

Thank you!!!

Full length research work and data available upon request, in word/pdf format. Kindly let us know at [email protected]

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