The Emerging Era of Digital Twin Technology in Industry 4.0

A digital twin is the virtual model of a physical product or a real-world plant that provides a complete set of data through sensors, cameras, and other technologies. According to the Digital Twin Market Report from MarketsandMarkets.com, the digital twin market estimates to grow $35.8 billion by 2025, revealing that more digital twin applications are being implemented across several business verticals globally.

Why do we need a digital twin technology in the first place?

Before we look into the details of the digital twin technology and its role in various sectors, let us see its benefits and real-time examples.

Prevents downtime

As digital twin is all about using a virtual model for each physical asset present in an industry, it predicts any possible failures, and these data insights help to enhance the development of the actual asset.

Saves maintenance costs

Digital twin reduces the equipment breakdowns by the evolution of sensors, machine learning, and cloud services, which helps to avoid any significant maintenance costs and prevent any interruptions in production.

For instance, Chevron Corp. uses digital twins to prevent any defects in its oil fields and refineries. Their CIO Bill Braun said in a Wall Street Journal article that they expect to save millions of dollars by using digital twins to maintain their critical equipment.

What is the future of digital twin technology?

The future of the digital twin market will see the effective use of advanced technologies to leverage the speed and agility of the enterprise. Along with AI capabilities and augmented reality, digital twins are future-ready to tackle complex problems.

• The vice president at Gartner in a press release stated that by 2022, one-third of the companies would have implemented IoT with digital twin.
• Transparency of the product development of the digital twin will be increased in the future where all the stakeholders will be living 1000 miles away.
• The future of digital twins will have more advanced simulation techniques in active collaboration with AI-based capabilities, which will help to give better data analytics.

The role of digital twin technology in industry 4.0

When Michael Grieves introduced the digital twin concept, he came up with three tests to determine if a digital copy truly replicates the actual product without any mismatch and gives productive data.

1. Vision test: getting a 360-degree view of the virtual products with real-time data for analysis and also while disassembling, we get to know the granular details as well, giving in-depth each part details. 

2. Testing phase: passing through the simulation testing and digital wind tunnel testing to build a robust virtual model.

3. Retrieving the information: effectively getting the data from these virtual products through a physical inspection.

Hence, many MNCs like Siemens and GE, have already implemented digital twin technology in wind turbines and manufacturing units, while Tesla also uses them for every VIN they manufacture for its automobile industry.

Apart from the sensor data, digital twins also get data input from enterprise resource planning, product lifecycle management, and customer relationship management software to give detailed data.

Various use cases

Many IoT app development companies provide digital twin services to accelerate the business process. Here are some other example use cases.

Manufacturing

In the manufacturing industry, digital twin plays a significant role by providing valuable insights to the user throughout the lifecycle of a product. Right from the production and design to the actual product built in the field and developing the future outcome based on the feedback of the existing product. Hence, a single application digital twin, helps to retrieve all these details. 

Key benefits:

• Getting exact visuals of the factory floor and machinery parts to a stakeholder who is living 1000 miles away is only made possible through digital twin's visualization feature. Moreover, hybrid visualization offers both real and historical data of the physical object.

• Digital twins enable effective collaboration between various team members where data scientists, designers, floor managers, product managers all work in harmony. Any defects or machine failures as a result of human error or software defects will be automatically alerted to the appropriate managers to take immediate action.

• Product Line Engineering streamlines any complex manufacturing projects that integrate easily with the digital twin application using industry 4.0 technologies.

Automotive

Before the technology era, the automotive industry would typically take 5 - 6 years to build a car, right from the design stage to the launch date. After the evolution, Henry Ford reduced the time taken to build a car from 12 hours to just two and a half hours.

Key benefits:

• For each vehicle, the digital twin maintains the Original Equipment Manufacturer (OEM) of each VIN and gives software updates to customers upon request.
• Provides real-time vehicle updates such as the highlights of the vehicle components, and its features from the digital twin application where it informs the customers, which is frequent or rare use.
• Digital twin, along with the augmented reality, helps to provide an interactive UX model that enhances the sales experience as well.

Health care

Digital twin in the health care sector provides critical data about a patient's history. Along with AI-powered models, they now offer more insightful data for future analysis as well as records of behavioral patterns and lifestyle changes.

Key benefits:

• It helps to determine what type of therapy has advocated a patient. For instance, if a patient is having prostate cancer and looking to get a treatment plan, then digital twin helps them choose a medical plan accordingly.
• Based on various data inputs like imaging records, genetic data, and other supporting laboratory results and the patient's lifestyle, it suggests a treatment plan accordingly.
• Digital twin applications monitor for any chronic diseases and detect any early stage diseases. 10 to 15% of the world population is suffering from kidney disease due to improper guidance and lack of awareness, but digital twin applications monitor patient's health records and send alerts when the blood level of the specific category shows any abnormal range.

Conclusion

Right from getting proactive medicine care or real-time updates of the vehicles in the automotive industry, digital twin implementation is becoming more useful across several sectors. It increases the productivity of any enterprise by providing better decision making and transparency of the product development life cycle between teams and stakeholders.