As emerging technologies continue to evolve faster than a Formula 1 race car, many businesses know they need to jump on board, but how? Decision-makers are left rifling through case studies and long articles only to be more confused about a path forward towards a successful digital transformation.
The concept of digital twin technology is easy to understand, and the benefits are straight-forward.
In this article, we cover how digital twin technology is used, common types of digital twins, various use cases and benefits, as well as the tools used to support digital twin technology.
Table of Contents
What is a digital twin?
A digital twin is a virtual representation of a physical object. The virtual model can be used to run simulations, study performance issues and generate possible improvements, all with the goal of generating valuable business insights. A digital twin commonly integrates with various IoT devices to collect real-time data and aid in simulating and predicting outcomes.
Equipped with that data, businesses can test and validate new processes and modifications in the digital twin before reproducing the same process or modification in the actual environment.
A digital twin is more than a simulation
While both tools use digital models to reproduce business processes, a digital twin creates a virtual environment that makes it more robust than a limited simulation. Typically, a simulation represents one particular process, while a digital twin reproduces multiple elements to study how a change in one system affects another. The result can be a positive or negative change, only the digital twin test will tell.
While a simulation typically studies one particular process, a digital twin can itself run any number of useful simulations in order to study multiple processes.
IBM
Another significant difference is that digital twin technology continuously shares real-time data back and forth with IIoT sensors in the live environment, enabling them to update each other in real time. Simulations, on the other hand, are programmed with data that must be manually updated, preventing them from offering a present view of what’s occurring.
Through working with continuously refreshed data across a variety of areas, in addition to the high computing power found in a virtual environment, a digital twin can process more variables over numerous points of view than a simple simulation. The result is the ability to test to improve processes and product outcomes, while reducing waste and downtime.
Digital twin examples
Investing in digital twin technology spans across every industry:
- Digital twin technology for pharmaceutical giant Merk
- Digital twin construction VR training software
- Digital twin in manufacturing at Unilever
- Digital twin for ESG initiatives at GE
Digital twin use cases
Benefits and use cases for digital twins include processes such as:
- System Design Improvement
Business leaders can use a digital twin to plan and test new production lines as well as alterations to existing sites. By building or modifying a digital twin production line, potential negative issues can be discovered and fixed before the physical version is built, saving time and money. - New Product Testing
A digital twin enables business leaders to rapidly evaluate new configurations needed to produce new products, while reducing the risk of expensive errors that can occur without such tests. - Monitoring and Predictive Maintenance
Anything that can be measured such as speed, vibration, motion, temperature, dust and humidity of machines and their environment can be used to monitor systems and produce a database of causes and correlations related to a business process that can be modeled in a digital twin. By using IIoT sensors to collect and analyze this critical information at the edge (that is adjacent to the machine on the job site) or in the cloud, managers can take action to prevent issues such as outages, spikes in usage or other sudden changes before they stop production, damage equipment or create a safety hazard for factory personnel. - Asset Lifecycle Management
A digital twin makes it easier and more effective to manage the lifecycle of assets for a business. Management can run a volume of data to model how long each part, component and asset will last and to develop a schedule for part maintenance and replacement. By using data in this way, management can extend the overall performance and lifecycle of the production line. - Employee Training
A digital twin provides a way to safely train new employees or current employees on new processes without disrupting operations on the job.
4 types of digital twins
Different types of digital twins offer different grades of magnification and comprehensiveness. Such different types of digital twins can run concurrently within a business system or process, such as:
- A component twin/part twin form the basic unit of a digital twin, representing the state of a single functioning component or part.
- An asset twin represents two or more components that work together to create an asset that, along with their interaction, can be studied as a digital twin. This produces performance data to be processed into actionable insights.
- A system or unit twin represents an entire system or unit to demonstrate how multiple assets work together to form a system or unit. It offers visibility that can yield additional ways to increase performance and reduce risk.
- A process twin provides a macro level of magnification, revealing how different systems function in order to create an entire production line. This can help management determine if the process is operating at peak efficiency. That knowledge can be used to improve scheduling of various operations across the manufacturing plant to improve output, maintain proper condition of equipment and reduce delays.
Digital twin technologies in 2023
Emerging technologies and tools used to support digital twins include:
- Virtual Reality (VR) Technology
Meta Oculus Quest - Mixed Reality and Augmented Reality (AR) Technology
Apple Vision Pro - Generative AI
Digital twin software companies driving value
Technology companies specializing in digital twin technology solutions:
- SAP Leonardo Internet of Things
- GE Predix
- Siemens Tecnomatix
- Bosch IoT Suite
- Invonto Unhorizon
Getting started with digital twin software
Building a digital twin can be nearly as complex as building the product itself. As a digital transformation initiative, selecting the type of digital twin technology that makes the most sense for your business requires both a solid strategy and development expertise.
At Invonto, we provide digital twin solutions to develop and execute a digital twin transformation strategy geared to each client’s individual needs. We will work with your managers who will use the digital twin to deliver significant ROI through optimizing production lines and preventing errors, while reducing time off line.
Our team of digital transformation consultants, technologists and developers are 100% US-based. Get a consultation to start a conversation on how we can help set your business up for success through a digital twin in manufacturing.