- What is a digital twin?
- How does digital twin technology differ from digital twin thinking?
- Why is digital twin thinking more important than any technology?
- How important is information management in a digital twin strategy?
- How does digital twin help in the use of analytics and artificial intelligence (AI)?
3Q 2019
Digital Twins and AI Deliver the Energy System of Tomorrow
There is much confusion surrounding the concept of digital twin. Most vendors will have their own idea of what a digital twin is. Often, this definition is reflected by the vendor’s own product set. Much that is said of digital twin is pure hype. Artificial intelligence (AI) is experiencing similar publicity. However, this should not detract enterprises from investigating either concept. In fact, the two go hand in hand.
This report cuts through the digital twin hype by proposing six maturity dimensions for the digital twin, which can be as basic as one datum. The report emphasizes the fact that digital twins are nothing new; rather, they change the conversation regarding data management. But this data management approach opens the door for new analytics-based business processes that can save companies millions of dollars. Efficiency is a major market driver, and savvy vendors will adopt tools that streamline data management.
This Guidehouse Insights Strategy Insight report discusses workable definitions of digital twins and AI. It includes perspective on why there are so many definitions for each technology and how to frame them optimally. This report offers suggestions for selecting the right kind of digital twin for different needs. It also provides recommendations for asset-based companies on how to choose the best iteration of digital twin for their respective needs.
Pages
20
Tables | Charts | Figures
5
Key Questions Addressed
Who Needs This Report
- Digital twin vendors
- Systems integrators
- Machine learning and AI and analytics vendors
- Grid and generation asset owners
- Electricity suppliers
- Smart home and building vendors
- Smart cities
- Investor community
Table Of Contents
Spark
Context
Recommendations
Digital Twin: More Mindset Than Technology
A Digital Twin Has Surprisingly Few Prerequisites
Guidehouse Insights’ Digital Twin Maturity Dimensions Help Mitigate Confusion
Digital Twin Technology Is Different from Digital Twin Thinking
Oil Refiner MOL Exemplifies the Power of Digital Twin Thinking
Digital Twin Is a New Badge for Existing Technology
Digital Twin Maturity Is Multidimensional
Richness of Data
Visualization
Select the Right Approach for Enterprisewide Digital Twin Requirements
Select the Right Digital Twin Toolset for Specific Requirements
A Network Connectivity Model Needs Constant Management
Accurate Network Connectivity Models Are Important
Digital Twins Can Be Just About Improving Visibility
A Common Language Is Essential for a Digital Twin
Digital Twins Enable Enterprisewide Analytics Strategies
Analytics Improve Data Quality in a Digital Twin
Predictive Maintenance
FirstEnergy’s Digital Twin Approach Ensured High Quality Outputs from Its Predictive Maintenance Program
Network Planning
Digital Twins Make Self-Aware Grids Possible
What Do We Recommend?
Ignore The Hype: Companies Already Digital Twins
Digital Twin Thinking Is the Most Important Aspect for Implementation
Start Small and Use Guidehouse Research’s Maturity Dimension to Grow
Pick the Lowest Hanging Fruit
Data Quality Is Essential
List of Charts and Figures
- Digital Twin Maturity Dimensions
- Growth of Devices in the Fractal Grid
- CAD Representations of Digital Twins
- ABB Ability Digital Enterprise
- Deep Self-Modeling
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