Interscale Content Hub – Have you ever wondered how digital twins work, making virtual copies of physical objects and changing the way industries do things?
By creating a model that’s just like the real thing, digital twins are a great way to optimize, predict, and innovate in lots of different sectors.
From manufacturing and healthcare to construction and urban planning, it’s important for professionals in the AEC industry and beyond to understand digital twins.
In this detailed description, we’ll explore the ins and outs of digital twins.
What Are the Basics of Digital Twins?
Digital twins are basically virtual replicas of physical objects or systems that operate in real time. This means they can be used for continuous monitoring, simulation, and optimization.
The idea of digital twins, as explained in “Digital Twin Technology” by Zongyan Wang, actually started with NASA’s Apollo program, where they used identical spacecraft for training and simulations.
This early application showed how digital twins could reflect the real-time status and predict the conditions of physical objects, which helped with decision-making during missions.
Digital twins bring together lots of different data from sensors attached to physical objects.
These sensors collect real-time data on things like temperature, pressure, and operational status.
This data is then processed and analyzed to create a digital representation that mirrors the physical object’s behavior and performance.
For instance, as Roberto Argolini and others discussed in the McKinsey & Company article, “Digital Twins in Manufacturing & Product Development,” digital twins help companies optimize product design and reduce time to market.
By simulating products digitally, companies can catch design flaws early and make the necessary adjustments before building physical prototypes, which saves a lot of time and money.
The Core Principles of Digital Twins
Digital twins are all about three main things: real-time data, simulations and analysis, and a feedback loop.
These principles work together to create a dynamic and responsive system that mirrors the physical object in a digital format. This enables continuous improvement and optimization.
Integration of Real-Time Data
One of the key things about digital twin technology is making sure that the data from the physical object is linked up with the digital version.
Sensors and IoT devices collect data on different things, like environmental conditions and operational metrics.
Take the energy sector, for instance. Digital twins of wind turbines and solar panels gather data on performance and external conditions, which helps to keep energy production as efficient as possible.
This constant flow of real-time data ensures that the digital twin stays an accurate representation of the physical object, so you can monitor and control it precisely.
Simulation and Analysis
Another must-have feature of digital twins is the ability to simulate and analyze different scenarios using real-time data.
This feature lets digital twins predict what’ll happen and test out different operational strategies.
In industries like aerospace and defense, digital twins of aircraft or spacecraft can simulate flight conditions and perform stress tests, giving us valuable insights into how these vehicles would perform under different scenarios.
This is a must-have for spotting potential issues before they become problems and making data-driven decisions to boost performance and safety.
Feedback Loop
The feedback loop is a key part of the digital twin ecosystem. It’s where insights from simulations and analyses are fed back into the physical system.
This loop lets you make real-time adjustments and optimizations, so the physical object can operate at its highest efficiency.
For instance, in healthcare, digital twins of organs can simulate how different treatments affect them and suggest adjustments, which helps doctors get the best results for their patients.
This continuous cycle of feedback and improvement is what makes digital twins a great tool for maintaining and enhancing the performance of complex systems.
For details on the digital twins main concept, you can read “What is Digital Twin? How Digital Twins Transform for Smarter Projects?”
Components of a Digital Twin System
A digital twin system consists of a few key parts that work together to create a detailed and up-to-date digital version of a physical object.
Physical Object
A digital twin is all about the physical object it represents. This could be anything from a machine to a vehicle or building.
Zongyan Wang says that the concept of digital twins can be used in lots of different ways, from individual components to entire systems and even complex processes.
This physical object is the foundation for the digital twin, providing the real-world data that the digital twin will use.
Digital Model
A digital model is a virtual representation of a physical object. It’s created using advanced 3D modeling and simulation tools.
This model is really detailed and shows the geometry, structure, and behavior of the physical object in great detail.
In product development, for instance, digital models can show how new designs will perform, which means we don’t need to make physical prototypes.
This capability not only speeds up the design process but also helps identify potential issues before they become problems in the real world.
Data Collection Tools
The data collection tools, which include sensors and IoT devices attached to the physical object, are essential for a digital twin system to work.
These tools collect real-time data on various operational and environmental factors, such as temperature, pressure, and usage patterns.
It’s important to get the data right, because it affects how accurate the digital twin is. If it’s not accurate, it won’t represent the physical object properly.
Connectivity
A solid network is key for getting data from physical objects to their digital counterparts without any hiccups.
5G tech helps us send lots of data really quickly and reliably, so our digital twins are always up to date.
This connectivity lets you monitor and control things in real time, so you can respond to changing conditions quickly.
Analytics
Advanced analytics, including machine learning and artificial intelligence, are really important for processing and analyzing the collected data.
These tools help us spot patterns, predict what’s going to happen, and give us useful information we can act on.
For instance, AI can analyze sensor data to predict equipment failures and schedule maintenance proactively, which helps avoid downtime and boost efficiency.
Visualization Tools
Visualization tools, like interfaces and dashboards, let users see the data and simulation results. This makes it easier for them to interact with and understand the information.
These tools are really important for making decisions and managing operations.
In the construction industry, for instance, visualization tools can provide real-time updates on project progress, which helps with better project management and ensures that projects stay on track.
Kindly read “Remote Collaboration through BIM During COVID-19: Hero of Workspace,” to get a better understanding of BIM and components of digital twins can be useful in remote work.
How Digital Twins Work: Step-by-Step Process
This approach combines different tech and analytical tools to create a dynamic and accurate digital representation of physical objects or systems.
Based on insights from “Digital Twin: From Concept to Practice” by Ashwin Agrawal, Martin Fischer, and Vishal Singh, we’ll look into the details of this process.
Step 1: Data Collection
To create a digital twin, the first step is to collect data. We install sensors and IoT devices on the physical object to capture real-time data.
These devices collect a lot of different information, including things like environmental conditions, operational parameters, and performance metrics.
For instance, sensors might monitor temperature, pressure, and vibration in machinery in manufacturing.
As Agrawal et al. say, the data you collect is the basis for building the digital twin. It ensures that the virtual model reflects the physical object’s current state accurately.
Step 2: Data Transmission
Once the data is collected, it has to be sent to a central system for processing. 5G is a big help here, letting us handle lots of data in real time.
This step really depends on having a solid network in place to make sure the data gets transferred quickly and reliably.
As Agrawal and his co-authors explain, it’s important to keep data safe during transmission so that the next steps can work properly.
High-speed internet means there’s minimal delay between data collection and processing, so we can monitor and respond in real time.
Step 3: Data Processing and Analysis
Once the data has been transmitted, it’s processed using some pretty advanced analytical tools. Machine learning algorithms and artificial intelligence play a big part in this stage.
These tools analyze the data to spot patterns, predict future states, and give you actionable insights.
For instance, AI can analyze trends and anomalies in machinery data to predict equipment failures, allowing for proactive maintenance measures in predictive maintenance.
The whole process of processing data means that the digital twin can run through all kinds of scenarios and make adjustments to performance based on what it’s seeing in real time.
Step 4: Visualization and Feedback
The last thing to do is to look at the processed data and give users feedback.
Visualization tools, like dashboards and interfaces, make it easy to understand the data and simulation results.
This helps operators understand the current state of the physical object, predict future conditions, and make informed decisions.
The feedback loop is really important because it lets you make adjustments and optimizations on the fly, based on what you learn.
This continuous feedback loop ensures that the physical system runs at peak efficiency, using the latest data to refine operations all the time.
How Interscale Becomes Your BIM Supporting System
We at Interscale bring digital twin technology into Building Information Modeling (BIM) to help manage and operate buildings better.
Interscale’s BIM management services offer a complete solution for handling complex building systems through digital twins.
We’ll work with you to tailor our solutions to your project needs so we can be your go-to team for efficient building design, construction, and maintenance.
For instance, Interscale’s use of digital twins lets us monitor building performance in real time, from energy consumption to HVAC systems.
This makes it easier for you to make better decisions and run buildings more efficiently.
If you’re interested in learning more about how Interscale can support your BIM projects with digital twins, kindly read our Interscale BIM Management Support page.
Conclusion
As this digital twin technology keeps developing, it’ll be used in more places, and it’ll bring even more benefits to different sectors.
As digital twin technology keeps getting better, it’ll keep on delivering benefits to lots of different industries. So, your company can really benefit from how digital twins work.
