What is a digital twin?

The digital twin concept is a perfect example of how the physical and virtual worlds converge. Essentially, a digital twin makes use of real-world data to create a simulation via a computer program that predicts how a product or process will fare. These programs are easily integrated into the Internet of Things (IoT), artificial intelligence (AI), as well as software analytics--all in a bid to enhance output.

The importance of digital twins in industry 4.0

The fourth industrial revolution, or Industry 4.0, revolves around automation and data exchange, and a wide range of manufacturing technologies form the core of its functioning in the world of business.

The concept of digital twins brings unlimited possibilities. The traditional approach of building something and then tweaking it in new versions and releases is now obsolete. With a virtually-based system of designing, the best possible efficiency level of a product, process, or system can be identified and created simply by understanding its specific features, its performance abilities, and the potential issues that may arise.

The development cycle of a product with digital twins makes a complex process much simpler. Right from the design to the deployment phase, organizations can create a digital footprint of their creation. Each aspect of these digital creations are interconnected and will be able to generate data in real time. This helps businesses to better analyze and predict possible challenges in implementation, right from the initial design stage. Problems can be corrected in advance, or they can give early warnings to prevent any downtime.

This process also opens up possibilities to create newer and improved products in a more cost-effective manner, as a result of the simulations in real world applications. The end result will be a better customer experience. Digital twin processes incorporate big data, artificial intelligence, machine learning as well as the Internet of Things, and represent the future of the engineering and manufacturing spaces.

Types of digital twins

There are several kinds of simulators for digital twins.

Product twins

These are digital models of separate products. Manufacturers create these virtual models and examine the product under different conditions. All the necessary changes to the product can be made on the single product level before the production line is created and a physical product is made. It results in more efficient design and reduces manufacturing expenses as well as time to market.

Process twins

These are digital models for manufacturing processes. With a virtual model of how a production process may work in varying scenarios, businesses can evaluate its functioning in each kind. This is the simplest way to create an efficient production methodology. This process can be fine-tuned with a digital twin for every equipment piece there is. For enterprises, this means the ability to have preventive maintenance systems in place. This lowers the occurrence of costly downtime and speeds up manufacturing operations safely and efficiently.

System twins

Digital models are also made of entire plants or factory systems. Vast amounts of operational data can be collected from a range of devices as well as products in an existing system. This helps with gaining insights for the creation of newer and better business opportunities that optimize all involved processes.

Some predict digital twins will replace human workers when it comes to diagnosing malfunctioning equipment. In fact, this is already the case with some enterprises. Virtual models tend to be more effective, as they have the ability to gather information. For example, a virtual model can assess the condition of spare parts from a wide range of sensors present in the online mode. This ensures they can be repaired or replaced quickly.

Applications of digital twins

There is no doubt that the digital twin concept is the next big thing for most business sectors. It will help with the accurate prediction of the current and future state of physical assets simply by analyzing digital counterparts. With a digital twin, an organization will be able to gain smarter and more accurate insights into product performance and enhance customer service. Organizations will be able to make better operational, as well as strategic, decisions based on insights gathered. Here are some of the sectors using them extensively.

Manufacturing

Digital twins are changing the foundation of the manufacturing industry, creating efficient design models and improving maintenance and upgrades. Manufacturers will be able to reduce production times significantly.

Automobile

Digital twins create a virtual model of a connected vehicle, capturing behavioral and operational data. This helps analyze the overall functioning and performance levels of the vehicle and all its connected features, resulting in a personalized experience for car owners that can be customized to their specific needs.

Retail

Virtual models of the customer can be created to try on clothes, lipstick shades, and accessories, something already used in online shopping. Digital twins can be used to simulate the appearance of an interior design plan, right down to decor and fixtures. This is what the customer experience is all about, and the digital twin plays a central role in augmenting retail customer experience by creating virtual twins and simulating how a customer would look or feel in relevant scenarios. Digital twins can assist with in-store planning as well as with security implementation and energy consumption management.

Healthcare

Digital twin applications can be found in a wide range of sectors within the healthcare industry. When combined with IoT, it can create smooth functioning at every stage—from monitoring a patient, to preventive healthcare, and even customized healthcare outcomes based on digital twin simulations.

Smart cities

Digital twins can help plan smarter cities; combined with IoT, digital twins can enhance economic development as a result of efficient resources management, a reduction in the ecological footprint of industry, and an overall increase in the quality of life. Based on insights gathered from several sensor networks and intelligent systems, city planners will be able to implement better policies for the running and maintenance of a city, with an eye on accommodating expansion.

Industrial IoT

Industrial firms that adopt digital twins have the ability to monitor, track, and control the physical aspects of their industrial systems digitally. Not only operational data, digital twins provide the ability to also capture environmental data, including details such as location, configuration, and financial models. All of this helps in future predictions in operations as well as dealing with anomalies.

Space exploration

The National Aeronautics and Space Administration (NASA) tests all equipment designs in a virtual environment before manufacturing physical versions. Only when it addresses all necessary requirements in the digital form is a spacecraft considered ready for creation. The same approach can be applied by space centers across the world.

Oil and gas industry

Using digital twins, engineers working at British Petroleum (BP) are able to visualize and control thousands of underground pipes deep under Alaskan snow. Siemens does the same with its monitoring of massive gas turbines. Thousands of tests are run over sensors to help with the digital twin process.

In other sectors, the use of a digital twin enables operators to train on a digital mock-up rather than spending resources on the creation of a dedicated simulator. With machine learning and AI increasingly growing in importance, machines may soon be largely autonomous. The prediction is that these machines will be able self-diagnose and self-repair, if any faults arise. Correcting this in a virtual environment will be the most cost-effective way to manage things in the real world.

The benefits of digital twins for businesses

Digital twins have mainly been used in manufacturing. However, this is quickly changing and there is potential for a wide range of businesses, especially those that are incorporating the IoT into operational processes. Several industries are going to realize the benefit of digital twins in the immediate future.

Cost-friendly production of a fault-free product

The process of taking a product from the drawing board to the showroom can be expensive. Each iteration of the product involves several stages and labor costs. With digital twins, a business is able to reduce existing or potential defects during production, giving engineers a chance to test and simulate the product in a virtual set-up. It is much more cost-effective to correct errors in a virtual environment than in a real one. Manufacturers will be able to eliminate all possible risks in the output and ensure the product, once launched, functions as intended.

Quick time-to-market for products

With a digital twin, companies reduce the amount of time taken to get to market and can beat out competitors. The entire lifecycle of the product can be simulated in a digital environment with all improvements made quickly and efficiently, significantly reducing risk for the company. With the virtual copy validating how a product will work in reality, the time to develop is quicker.

Predictive maintenance

Digital twins can also anticipate problems and provide solutions in advance, which is referred to as predictive maintenance. All remote copies are constantly monitoring their physical counterparts and gathering a range of information via sensors. This data is analyzed in real time and any downtime or breakdowns can be predicted and resolved. Human operators use this information to report on issues and address them immediately.

Disadvantages of digital twin technology

The benefits of the technology are truly amazing and can be game changers for businesses that adopt them. But, like all technology, there are certain pitfalls to avoid when choosing the technology.

Data security

One of the fundamental problems with the concept of digital twins is that of data security and privacy. The system uses smart software, which naturally has access to a wide set of resources and private information about businesses, making it a target for cyber-attacks and data theft attempts. Businesses have to think and strategize options when it comes to implementing security systems for digital twin technology.

High levels of investment required

Another drawback to digital twins is the high level of investment that is needed to implement. Not every business can afford the return on investment when financial resources are tight.

With the level and speed of innovation in machine learning and the use of big data, these virtual models have a permanent place in modern day engineering, in the constant effort to boost innovation and enhance performance. Using digital twin concepts, every business will be able to embrace and enhance technological trends of strategic importance. They will be able to prevent expensive failures in physical products. Businesses will also have the perfect base for advanced analytics monitoring and predictive abilities.