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Building Industrial Digital Twins

You're reading from   Building Industrial Digital Twins Design, develop, and deploy digital twin solutions for real-world industries using Azure Digital Twins

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Product type Paperback
Published in Nov 2021
Publisher Packt
ISBN-13 9781839219078
Length 286 pages
Edition 1st Edition
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Authors (2):
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Shyam Varan Nath Shyam Varan Nath
Author Profile Icon Shyam Varan Nath
Shyam Varan Nath
Pieter van Schalkwyk Pieter van Schalkwyk
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Pieter van Schalkwyk
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Table of Contents (15) Chapters Close

Preface 1. Section 1: Defining Digital Twins
2. Chapter 1: Introduction to Digital Twin FREE CHAPTER 3. Chapter 2: Planning Your Digital Twin 4. Section 2: Building the Digital Twin
5. Chapter 3: Identifying the First Digital Twin 6. Chapter 4: Getting Started with Our First Digital Twin 7. Chapter 5: Setting Up a Digital Twin Prototype 8. Chapter 6: Building the Digital Twin Prototype 9. Chapter 7: Deployment and Value Tracking 10. Section 3: Enhancing the Digital Twin
11. Chapter 8: Enhancing the Digital Twin 12. Interview on Digital Twins with William (Bill) Ruh, CEO of Lendlease Digital
13. Interview on Digital Twins with Anwar Ahmed, CTO - Digital Services at GE Renewable Energy 14. Other Books You May Enjoy

The value proposition of Digital Twins

Digital Twin systems transform businesses by accelerating holistic understanding, optimal decision-making, and effective action.

Reduce complexity to improve understanding

Grieves and Vickers' initial objective was to manage assets and systems that were becoming increasingly complex with simpler, but representative, virtual instances. Digital Twins that are synchronized with physical entities provide situational awareness and other operational insights tailored to specific problems you are trying to address.

Better insights into real-time and simulated behavior support making better decisions faster. Insights from Digital Twins are often more reliable than traditional approaches of searching for data in multiple enterprise systems. The consolidated data integration approach of a Digital Twin provides more reliable, comprehensive insights that improve the quality of the decisions that are made on that data. The structured information approach of a Digital Twin also lends itself to decision automation rather than just decision support.

Having this improved understanding and better insights provides value in two key operational perspectives. We will look at these in the following subsections.

Improved situational awareness

Businesses are increasingly forced to work in real time or near real time. Every day, companies are exposed to more and more internal and external events that need to be responded to in real time. These events can come from a multitude of sources:

  • The actions of people in a business
  • The actions of competitors, customers, legislators, or suppliers and supply chains.
  • Equipment breakdowns, process failures, and weather events
  • Real-time intelligence from business applications, and near real-time data from web services
  • More recently, the influx of information from IoT with sensor-based or smart device machine-borne data in IoT platforms

Real-time situational awareness is a concept that came from the US Air Force when training fighter pilots to anticipate the actions of an enemy fighter. It is based on gathering information on the current state and environment of the situation, determining what the information means, and projecting the future state to create a corresponding action. It was described in military terms as the Observe – Orient – Decide – Act (OODA) loop.

Digital Twins might not require the same millisecond response times as a military jet fighter, but the real-time synchronization of a Digital Twin representing a physical asset provides critical situational awareness that drives critical decisions. The supporting information for decisions can be augmented with predictive models, physics, and/or analytics-based data to provide operators with comprehensive decision support. Combining rules with decision information creates an opportunity for Digital Twins to become prescriptive and take autonomous action through decision automation.

Both decision support and decision automation focus on delivering better business outcomes based on the situational awareness that's gained through the Digital Twin.

Improved business outcomes

Digital Twins improve business outcomes in various ways, but we will focus on the impact of an industrial Digital Twin that represents a physical asset or entity such as a motor drive, a production plant, or a factory.

The business impact of Digital Twins can be measured based on four major impact categories, as shown in the following table:

Figure 1.10 – The business impact of Digital Twins

Figure 1.10 – The business impact of Digital Twins

Each category represents a business value driver where a Digital Twin can act as a lever to influence overall business outcomes.

Transformational value

The transformational value of Digital Twins in industrial applications focuses primarily on the impact on digital business transformation, as well as the development of new or improved products based on the transformation of Digital Twins.

Business transformation through digital transformation

A Digital Twin is a change agent for formal digital transformation. A Digital Twin typically represents a specific initiative or use case around a business goal. Due to the digital nature of a Digital Twin, the particular use case or initiative is generally the project that drives specific digital transformation toward the business goal or outcome:

Figure 1.11 – Digital transformation versus digitalization

Figure 1.11 – Digital transformation versus digitalization

Digital Twins can affect business transformation by either improving efficiency through digitalization or providing added value by enabling new business models. The four quadrants in the preceding diagram show the impact of different Digital Twin initiatives that improve business process efficiency with digitalization and real-time data. Alternatively, it can monetize and leverage real-time data to change an organization's operating business model. The top right-hand quadrant represents opportunities where businesses can, for example, sell new services based on their equipment, such as support contracts and consumable replenishment, based on the real-time data from their products and customers.

Many organizations start with digitalization projects that improve efficiency. As they gain maturity when using Digital Twins, they move to the top right quadrant and look for ways to monetize these new digital assets.

New or improved products

There are different ways to monetize these new digital assets, including selling operational and maintenance intelligence to operators and users. Equipment manufacturers can also use this information to provide ongoing services based on conditions or predictions gathered from real-time data.

Original Equipment Manufacturers (OEMs) can also use information about the use and performance of their equipment in the field to provide feedback to help improve the design of their products and services. The actual use of assets in an industrial environment provides a wealth of information for Design Digital Twins, which can now use this information for better simulation, specifically in physics-based models.

Value at stake

The World Economic Forum value at stake framework provides an alternative perspective on assessing the impact of digital transformation with technology-based approaches such as Digital Twins.

The "value at stake" framework assesses the value in terms of the economics for the industry or the business and the impact on society. It has a simple representation, especially when communicating value to business executives and other stakeholders, who have a limited interest in the technical aspects of the Digital Twin but need to make the decisions to invest in Digital Twin technology.

The digital value to the industry is based on two elements:

  • Value migration, which represents how revenue can shift between stakeholders such as competitors, customers, and other industry players. This aligns with the business model innovation opportunity described earlier in this chapter.
  • Value addition, which represents the regular business operational opportunities, such as increased revenue and reduced cost.

The digital value to society focuses on three impact points:

  • The traditional economic measures for customers and employees in terms of cost, time saving, and efficiency improvements.
  • The societal impact in terms of job creation, new skills development, reduced traffic congestion, and safer working environments.
  • The environmental impact can be described by reducing CO2 emissions or improving the management of tailings in mining:
 Figure 1.12 – Example of a value at stake analysis for a Digital Twin

Figure 1.12 – Example of a value at stake analysis for a Digital Twin

Note

The preceding diagram has been adapted from https://reports.weforum.org/digital-transformation/introducing-value-at-stake-a-new-analytical-tool-for-understanding-digitalization/.

The single-page view of the value at stake for a Digital Twin, shown in the preceding diagram, provides a simple yet powerful way to describe a Digital Twin's value proposition.

Now that we can describe the value of a Digital Twin, the next key step is identifying ideal candidates for Digital Twins in your business.

You have been reading a chapter from
Building Industrial Digital Twins
Published in: Nov 2021
Publisher: Packt
ISBN-13: 9781839219078
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