If you’re unfamiliar with the term digital twins, the concept is fairly simple. A digital twin is a virtual representation of a machine, system, or design. Consider any modern automobile. The car itself is the machine. It has sensors and data collection points. The digital twin is a virtual representation of the car. As the virtual twin gets feedback — low tire pressure, poor oil viscosity, higher engine temperature, etc., the digital twin is modified to reflect this information.
As a full-service managed IT provider for businesses, we often use this essential systems model to monitor the health and performance of a system and to predict potential issues. Contact us today to discuss digital twins and other IT concepts for your company.
Introduction to Digital Twins
One of the reasons that IT teams like using digital twins to monitor systems is the visualization aspect of the the tool. A visual representation can make the information more accessible to individuals who don’t have a technical background. Consider a complex machine that has multiple iterations of several types of gears. Simply receiving an alert that “hypoid gear #3 needs to be replaced” may be confusing to the uninitiated. A digital twin may highlight the problematic gear, allow the user to zoom in, provide directions for replacement, or even offer the option to notify the machinist.
But that example only highlights part of the usefulness of digital twins. Digital twins collect, analyze, and report on the information that they collect.
Where Did Digital Twins Begin?
Digital twins have been forecast in science fiction for years. However, digital twins in an industrial setting are a much more recent occurrence. The first practical consideration of digital twins is credited to David Gelerntner in his book “Mirror Worlds.” Geletner, a Yale computer scientist, wrote, “They are software models of some chunk of reality, some piece of the real world going on outside your window.”
However, the term “digital twin” wasn’t coined until 2010 when John Vickers of NASA used it to describe a concept that had already been integral to their operations.
Mechanics of Digital Twins
There are four main components of a digital twin:
1. The Physical Asset
This, of course, is the machine, system, application, or process that you’re monitoring. It is the template for the digital twin.
2. The Digital Model
This will be the virtual manifestation of the physical asset. It can be a 2-D or 3-D representation. With processes that don’t have a physical representation, the digital model can show data points, charts, flow charts, nodes, etc.
3. The Data Connections
These dictate how your data is being collected. To further the car analogy, data connections could be various sensors positioned in key areas of the automobile (i.e., engine, tires, climate system, etc.). For an automated process, the data connections could be the applications that you use to collect data.
4. AI and Analytics
This is the software that interprets the data, runs simulations, and attempts to anticipate outcomes. For example, if you’re running cybersecurity software, your analytics software may detect a suspicious login and restrict access in real-time.
These generic components are used in all digital twin modeling.
Advantages of Digital Twins in Predictive Maintenance
In certain industries, operations, and processes, digital twins are essential to avoid interruptions in vital service or to meet legal requirements. In other operations, they are just considered to be an efficacious way to avoid costly shutdowns and breakdowns in customer services. Here are some of the benefits of having a digital twin monitoring system:
Digital twins can predict maintenance issues at an early stage. A technician can easily identify the type of maintenance required and execute it before it causes a breakdown.
These types of models can reveal flaws in the system and find new opportunities for optimization.
The information provided by digital twin reports can lead to increased profitability and improved efficiency.
Depending on whether or not the asset is client-facing or not, improved performance can improve the customer experience.
Digital twins can be designed to enhance security, identify risks, and neutralize threats.
Digital twins can be used as training tools for employees before they work on physical assets.
Data Collection and Integration
The ability to collect, store, and process data has enabled digital twins to create and analyze models effectively. With a digital machine system, sensors or software trackers (depending on the physical asset) collect and store data. AI analytical tools can then constantly review the data, allowing it to make predictions and recommendations or automatically take action.
For example, consider a digital twin that’s been established to mirror the actions of an assembly line that produces medical device housing. The system has been programmed to do nothing if the machinery is working optimally. However, if it detects an increase in temperature in a specific portion of the machinery, it may indicate that a fan is offline. The digital twin then runs a diagnostic test and determines that the fan in question is indeed not spinning. This may have several causes, so the system alerts a machinist, providing them with the possible diagnoses and solutions. The machinist responds to the shop floor, takes the machine offline for a limited time, and rapidly makes repairs.
This is just one way that a digital machine can be utilized on a shop floor. To find out how your business can implement a digital machine, contact Flagler Technologies.
Industry-wide Applications of Digital Twins
Digital twins can be found in nearly every major industry. Here are some major sectors that utilize digital twin models.
Manufacturing
These businesses can establish digital twins to monitor various pieces of machinery, optimize processes, eliminate waste, reduce inventory, and more.
Automotive
In addition to the way that other manufacturers utilize digital twins, the car industry has been making great strides in creating digital twins for individual vehicles. Consider a Tesla’s dashboard screen, which has a virtual representation of the car right on screen.
There are undoubtedly many examples of digital twins used to replicate the auto manufacturing process, but this image shows how each car also has a discrete digital twin.
Energy
Whether using digital twins to monitor a nuclear power plant, an array of solar panels, or a fossil fuel power station, this technological advancement can help prevent blackouts and avoid catastrophic incidents.
Image via the U.S. NRC
Flagler’s Role in Digital Twins Technology
Flagler Technology can help your company implement its own digital twin monitoring system. If your company uses a complex process or system that you believe could benefit from having a digital twin, contact our technicians. We are a managed service provider that, among other things, can help you establish a digital twin system. Call today to get started.