Digital twin is the idea of keeping a digital matching part of a physical object. In addition, it also allows for operations using data from smart devices such as sensors. The digital thread is the channel that connects the digital twin to its physical matching portion.  

With the appropriate integration of Artificial Intelligence (AI) and data, the digital model will likely be updated and modified on a regular basis. It also allows for virtual reality technology.  

It is essential to combine the physical object and the computer-generated corresponding items. Digital twin technology is becoming more important as the technology trend in Industrial Internet of Things grows. 

Digital counterparts are connected to the network technology. Their ability to solve problems and provide better operational performance makes these parts essential elements for every company. 

The digital twin technology provides companies with a digital copy of their products. This allows them to spot potential problems early so they can address them. 

It is not easy to create a digital copy of the equipment. It is best to create a digital counterpart for one manufacturing unit division, and then put it into action. Afterwards, you can develop digital matching part for other areas. 

The digital twin technology is also distinct from the computer-aided design (CAD). The digital counterpart has real potential to offer a fast and widespread link between the digital and physical domains within industries. 

This technology is revolutionizing the manufacturing industry because it reduces costs, controls assets and minimizes downtime due to equipment failures. Industrial IoT is based on digital matching. This technology opens up new opportunities for all businesses worldwide.  

Digital replica makes use of technologies such as virtual reality. Furthermore, it uses data and graphics modeling to create a perfect virtual model of any equipment. 

The Digital Twin Technology Is Functional: 

This technology uses sensors to collect data from physical objects in factories. Sensors transmit the data to a computer-generated replica. In the end, the communication improves the performance of the physical object. The best part is that the virtual counterpart is available before the physical construction of the manufacturing units takes place. 

Engineers must combine data from many sources to create a virtual product. This includes manufacturing statistics, information about the product’s workings, and analytics software. Requirements for AI processes that integrate distinct equipment into the computer-generated copy are different ones. As you can see, you can use digital replicas at multiple levels in manufacturing.

Different Levels to Implement Digital Twin

Component Level 

Digital Twin is a high-level way to highlight the critical component of the entire manufacturing process. Besides, this component is very important and crucial to the entire manufacturing process. 

Asset Level 

Digital replica at asset level creates a digital copy of an equipment component which operators use during the production phase. 

System Level:

Manufacturers can use a system-level digital replica when they need to improve their production line. 

Process Level 

This level takes into account the complete product life cycle. From product/process design, through development, manufacturing, or production, all the way to the end user using the product. This aids to develop future and current products. 

Design Plan of Digital Twin: 


This involves the installation of multifarious sensors on a physical object to provide insight into its surroundings. There are two categories of measurements: 

  1. Operational Measurements measure the physical performance of an equipment such as its color, uniformity, and torque. 
  1. External data that affects physical equipment operations such as barometric pressure and room temperature. 

Encoders can transform these measurements into secure digital messages. These digital messages can then be transferred to a digital copy of the equipment. 


This phase creates real-time seamless bidirectional connectivity from the physical processes to the digital platform. For supporting physical equipment’s virtual counterpart, network connectivity is essential. It also involves three elements: 

  1. Edge Processing: this interface connects process historians with sensors. It then processes the data from the sensors to pass it on to the platform. Then, this interface interprets proprietary protocols to make data formats understandable and decrease network communication. Edge processing speeds up network communication by processing ingested data at endpoints. 
  1. Communication interface: communication interfaces allow for the transfer of processed data (information), from sensor function into an integration function. The digital twin configuration determines where the sensor can be placed to produce the insight. It can be located in a mine, at home, or in a lot. 
  1. Edge security: new security threats are emerging rapidly due to the rapid development of new communications and sensors. As IP-enabled assets increase, so will the need for new solutions to enable digital twins. Firewalls, encryption, keystrokes, and device certificates are the most popular security measures. 


The data aggregation can support data ingestion into a data warehouse/repository, which can be easily processed and prepared for analysis. Data processing and aggregation can be performed on-premises or in the cloud. 


Analyzing the data is another phase, and this stage involves analyzing all data. Data analysts and scientists typically use advanced analytics platforms to extract insights from data, thus allowing for intelligent decision-making. 

Displaying Insights

Analytics insights are displayed on dashboards that have visual representations. This highlights any differences between the digital twin model and the physical world in one or more dimensions, thus showing the potential areas that need to be investigated. 


Here you use the actionable insights from the previous step and feed them back to your physical asset. Decoders receive these insights and decode the commands and then feed them into actuators which control the movement and control of the equipment.  

Back-end systems that control supply chains can also update the insights. 

How do you lay the foundation with the digital twin technology?

Discover the Possibilities: 

It is pivotal to first envision and zero in on the areas that can benefit from the digital twin technology. Even though every manufacturing unit will have a different need, the right scenario will likely share these characteristics. 

  1. You must make sure that the equipment you choose is a key part of your manufacturing process before you can spend money on creating virtual counterparts. 
  1. Product-related issues related to processes can be solved which could unlock value for the enterprise and the customer. 

After narrowing down your options, you must evaluate the opportunity to identify factors that could offer digital twin benefits. 

Try to Detect the Process: 

Next, you need to identify the pilot digital twin configuration that is the most valuable and with the highest success rate. To identify the most suitable candidate for pilot, you can take into account organizational change management and operations. A handful of companies make the mistake of going too deep in building a digital twin for complex equipment or processes.  

This can lead to problems. Instead, companies should be able to focus on being broad and not deep. This will allow them to deploy the digital twin across their organization that delivers the greatest value and support. 

Go Narrow 

The pilot can only be part of a business division or product to limit its scope. Since this limited scope should not be less than what the enterprise can use, the pilot should be flexible and open-minded as you develop it. Agnostic ecosystems will enable adaptability and integration of data and allow for new partners and technologies. 

You want to be able to work with any data sources, but you need an end-to–end solution that is flexible enough to scale. 

Expand the Pilot 

After the pilot has been successful, you can scale it up. You will now need to find opportunities where the pilot can be scaled and reap its benefits. It may be a good idea to target processes that are close or have interconnections with Pilot. Take the lessons learned from Pilot development and scale it quickly. 

Do not forget, shareholders and larger companies should be aware of the benefits that the digital twin brings. 


You can measure the value of the digital twin by monitoring and measuring the implementations. It is possible to make iterative changes to the future digital-twin process and to observe the results to determine the optimal configuration. 

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