With the evolution of simulations and 3D tech, innovative technologies are starting to emerge. Digital Twin is an emergent technology gaining massive momentum in the industry. As the Fourth Industrial Revolution comes closer, digital twins’ technologies are maturing and evolving rapidly, increasing the utilization of practical applications of digital twins.
Moreover, with the incorporation of technologies like Artificial Intelligence (AI), Machine Learning (ML), or Big Data, companies are converging digital twin technology with emerging technologies like Augmented Reality (AR) and Virtual Reality (VR). As a result, it enables rapid design and development and allows smart solutions in production, sales, logistics, and the global supply chain.
Digital twins are a massive boon for rapid prototyping during the design and development of a product. Furthermore, due to the ability to enhance current manufacturing & product development, industries worldwide are incorporating digital twin technology in their business, product development, and even consumer experience. The current global digital twin market sits at 5.4 Billion US Dollars, but this slump is due to the COVID-19 pandemic shutting down many industries and production along with it. As a result, the world was simply not ready to adopt it rapidly.
However, with adaptation, digital twin technology is rapidly rising in applicability and usability and increasing accessibility even at the end-user side. With this in hindsight, researchers predict that the global digital twin market will cross 63 Billion US dollars by 2027. This estimation shows a high annual growth rate of 42.7%. Furthermore, it shows that the market, industries, and even consumers are moving towards the much-awaited digital transformation of Industry 4.0.
Read more: Reduce Costs with IoT and Digital Twins
To understand the practical applications of digital twins, we first have to understand the technology itself.
Know Your Technology: Digital Twins
Digital twins technology is evolving in both its technological reach/sophistication and its meaning. While the idea of digital twins is not new, it is undoubtedly going through a massive revelation in the industry currently. Furthermore, with technologies like 3D models, simulations are rising. As a result, digital twins are also gaining momentum in the industry.
The digital twin accurately represents a real-world physical object or an environment in a digital form. Do not confuse digital twins with 3D models or simulations. It is much more than that. Digital twins represent a subject (any object in the real world) not just in a static manner but in a dynamic way. It means that the digital twin will always represent the product/object throughout its lifecycle. The twin always reflects any change or modification on the real-world object or vice versa, in which the real-world object demonstrates a shift in the digital twin.
While 3D models just simulate some properties and structure of an object, the digital twin represents and accurately reflects all properties and characteristics of the real world. From design, materials, behaviors, and properties, the digital twin represents them all. So it becomes easier to reflect changes of both the digital twin and the real object. Furthermore, it remains accurate throughout the whole design phase, developmental phase, prototyping, or even after production for maintenance or repair, effectively reflecting all stages of a product.
Furthermore, unlike a 3D model, which is just an informational model, digital twins react and behave in a certain way similar to the real object in different environments and conditions. Due to this, the digital model is more dynamic and adaptive. Moreover, with AI at its core, digital twin technology enables communication, updating, and even learnability similarly to its real-world counterpart through the exchange of data among each other.
With technologies like AI with ML or data analysis, digital twins are becoming more accurate and smart. It also enables more flexible product phases for the design and development of a product. They help product developers explore different solutions freely without concerns relating to physical material costs or loss. Companies worldwide are rapidly adopting digital twin technology, enabling various applications and use cases to arm themselves with this type of revolutionary technology.
Here, we list some of these potential uses and practical applications of digital twins technology as shared by 13 different tech experts of the Forbes Technology Council.
1. To calculate product performance statistics and measures
Michael Campbell from PTC shares that with innovations enabling digital twins to be a comprehensive digital equivalent of a product or process in the real world, product developers or manufacturers can understand how the product is in use or performing. They can even track if the product or supply line may break down or is low in supplies. Campbell remarks that all this can lead to a better experience for the end consumer.
2. Simulating complex manufacturing scenarios
Eugene Khazin from Prime TSR remarks that digital twins have great use in the form of a precise virtual representation of a production supply chain. It will use advanced analytics and machine learning systems to predict and simulate different complex “what-if” scenarios without running these in actual production. As a result, manufacturers and production sites will utilize resources more efficiently and accurately to increase product quality.
3. Removing risks from different experimentations and analysis
Kathleen Brunner from Acumen Analytics Inc states that digital twin technology is a game-changer saying that it can eliminate the need to perform various experiments and studies with actual equipment or processes. Digital twins offline can enable multiple investigations of various complex and what-if analyses of different scenarios. Practical applications of digital twins allow optimization of other parameters and outputs with a digital representation or replica interface that responds to human and environmental inputs. These digital experiments significantly de-risks these physical experimentations by deeming them unnecessary.
4. Improving software products
Vince Padua from Axway explains that one way for the practical application of digital twins is to leverage actual customer usage data. This data can improve enterprise software products through its analysis. The data collection can include whether users are using a particular feature and how they receive notifications or collaborate with other users. Developers can create a digital twin of the customer experience using this data, while Artificial Intelligence can determine and predict the fastest and most efficient ways to solve various issues.
5. Real-Time information sharing and analysis
Gerald Rousselle from One Concern shares that digital twins can produce new functionalities since they represent the physical world in a form that computers can understand. He says that a GPS in mobile can be a digital twin of the natural world to provide accurate and real-time direction and navigations to your destinations.
6. Creating valuable digital assets
Ghufran Shah from Metsi Technologies Ltd explains that there is a lot of hype around cryptocurrency and non-fungible assets/tokens or NFTs. He clarifies that NFTs are a way to represent a physical asset such as a picture, video, or even a music clip in a digital format. Once a physical object is mapped into an NFT, a unique identity of this asset can now live forever within the blockchain. These assets can even gain monetary value and become valuable collectible.
7. Facilitating hybrid teaching methods
Zeng Fan from the University of Miami Herbert Business School says that the schools and universities are equipping classrooms to accommodate virtual conferencing tech for virtual teaching due to the pandemic. This technology is similar to one of the practical applications of digital twins, face-to-face and digital/virtual class deliveries. This technology can also be in use for recording asynchronous digital course content.
8. Improving vehicle safety
Stefan Kalb from Self Engine explains that it's costly to use real cars and crash test dummies to get actual life data about car crashes, potentially saving lives. If digital twins technology is used, it can collect sensor data from inside a car as in the real world. This data, over time, can go through analysis and study and perform numerous cost-effective and efficient car crash simulations. These simulations can provide data that can improve the safety of real-live cars.
9. Supporting sustainable clothing practices
Julia Dietmar from Vue.ai explains that an excellent example of digital twin technology can be a “digital passport” for different pieces of clothes that are manufactured. Such “passports” can contain various information such as product attributes, raw materials, factory information, and even previous owner information. It can prove to be very useful for sustainable clothing practices.
10. Collecting and providing input for databases
Vitaly Kleban from Everynet says that the lack of ML and data analytics data is a genuine concern, even putting multimillion-dollar investments at risk. But digital twins can serve as an interface between real-world hardware and sensors to collect data from the physical world. The practical applications of digital twins can even prove to be a key to providing enough data for ML systems.
11. Preventing sports injuries and enhancing athletic performance
Laurie McGraw from AMA explains that the NFL has a digital twin for every player through field cameras and sensors. It can recreate every move or body posture of the players. This level of sophistication has huge potential regarding injury prevention and even improving player and game performances. These types of data and information can prove to be very useful for more than just elite athletes.
12. Providing personal assistance
Kerrie Hoffman from getting Digital Velocity and Focal Point Business Coaching state that smartphones are already digital twins of every person. Smartphones are already acting as our digital twins since they provide various functionalities like “Swipe to Pay '' when entering a coffee joint or providing alternate routes when there is a traffic jam ahead.
13. Optimizing traffic flows
Joaquin Lippincott from Metal Toad explains that practical applications of digital twins in the transportation sector are enormous. With smart vehicles and smart cities, planning and real-time adjustments to traffic are possible, optimizing traffic flows and saving time. Such technology may be dangerous, but we can test, optimize, and later implement such technology much more safely with digital twins.
Robotics technology is continuously changing and evolving. With the development of simulation technology, the current industry is rapidly moving towards digital solutions together. With industries on the verge of shifting towards Industry 4.0, digital technologies, simulation technology, AI, AR, and VR will be the most critical pivot points. Robotic technology in industries and manufacturing processes provides vast benefits and advantages. Robot integration in production, manufacturing and other industries gives them cost savings, lower time, and efficient resource usage. Together, it all can help us to explore offline robot programming software solutions.
The traditional robotic training, testing, and operations method pales in comparison to the influx of modern demand and supply. Consequently, various industries are looking to make their supply chain from production to distribution more efficient and cost-effective. So naturally, robots are the ultimate answer for automation and efficient completion of a process with precision.
Along with the advancement of technology, industries across different fields are now looking to integrate their operations with robotic technology. However, robotic development is not an easy feat. Due to the sheer complexity of robot development and research, some industries are hesitant to adopt robotic technology. Nevertheless, the cost-benefit analysis of the development and use of robotics is simply too lucrative to ignore.
However, with the traditional methods of robot development, testing, and training, various industries cannot move towards it. Furthermore, it brought several misconceptions in the industry that robotic programming is too complicated and too resource-heavy to use. With these misconceptions, the industry was hesitant to take on the challenge. Even though offline robot programming has come a long way from its inception, misconceptions still linger around the industry with false beliefs. Words go around that it cannot handle all the variables present in real-world development or complicate things compared to the traditional approach.
Robot Offline Programming is an “offline” approach to programming that takes the robot programming away from the traditional pendant/robot cell and physical robots in production. Instead, Offline Robot Programming allows users to generate robotic instructions or code from their computers and different software solutions instead of using a robot on or taking it out of production.
The idea is simple; remove the traditional method of generating robotic instructions and code, i.e., using teach pendants and replace them with computer software or simulation software. It was necessary because the conventional process of using teach pendants or robot cells for robotic programming code was too inefficient and time-consuming. Pair this with the fact that it constrains profitability and business growth. It then becomes a throne in the process of robotic research and development.
Teach Pendants are devices that robot developers/operators use to control an industrial robot remotely. Teach pendants to allow users to manage and work with robots without connecting the device with a terminal but instead works wirelessly, i.e., no tethering to a fixed terminal. Technicians use these devices to test a robot either for programming, i.e., robotic coding or repair, or for performing some maintenance. Due to this, teaching pendants are a crucial part of industrial robotic operations.
However, using pendants is time-consuming. It's prolonged and even resource-consuming. Hence, the replacement of these traditional devices with offline robot programming software is necessary. It will allow users to operate robots either for testing or repair or maintenance or even robotic code generation with much efficiency and simplicity. Furthermore, it enables robot developers to perform all these actions through their computers without even taking out the robot from production or if it is not fully ready to be operational. Thus, it radically maximizes productivity and even reduces cycle time and downtime of the production.
Offline Programming or OLP solutions are therefore sought after by industries looking to utilize robotic solutions. Due to the advancement of simulation technology and offline programming software, it's becoming faster, more reliable, and more efficient to use OLP solutions than the traditional approach. Simulations and offline programming may differ because simulations exist without offline programming, but offline programming cannot live without simulations. Although this might make simulation and OLP seem different, they go hand in hand and sometimes are used interchangeably.
Robotic OLP can exist because of robotic simulation technology, which is currently one of the most frequent use cases of simulation technology in industries. With simulations enabling 3D representation of a robot, i.e., its digital twin, it can also represent and reproduce robotic functions, movements, behaviors, and operations in different conditions and environments. Thus, It essentially enables Robotic OLP to exist.
Although simulations make it easy to generate any environment for any use case, knowing these requirements beforehand is necessary to see the type of service one requires regarding OLP solutions. Along with this, there are some other things one needs to consider when exploring Robotic OLP.
Some of the things to consider when exploring Offline Robot Programming Software solutions are given below:
Offline Robot Programming is a technology that enables rapid programming with efficient processes and even automation in the mix. It is advantageous and beneficial to perform robotic coding for robots with complex structures, numerous moving parts, and axes or programming complex paths. These complex programming tasks generally take a massive amount of time, resources, and hard labor with teaching pendants, while it's straightforward, efficient, and swift with OLP.
Furthermore, with virtual environments to teach the robot, downtimes are no longer present when teaching the robot a new programming or operation path. OLP can even upload new programming in the robots when in a live production environment or when it is operating. Apart from these, safety, quicker cycle times between teaching the robots, or a straightforward approach to test a new configuration, all are easier to perform through OLP.
Various companies like FS Studio provide OLP solutions to make it easier for companies/industries/manufacturers to adopt OLP solutions in their existing production environment. FS Studio provides Robotic Simulation Solutions crucial for OLP solutions with a decade of collective knowledge, experience, and skills in store. It helps the production team to focus on the actual product rather than shift their resources in offline robot programming implementation and adaptation. Nevertheless, OLP is a technological innovation that will help productions reach new levels of innovation with more possibilities and opportunities to explore.