Overview of Digital Twin Technology

Digital Twin Technology :

Digital twin is a representation done digitally which seems existence of real world or the actual system. We can say it as a virtual copy of the physical devices. It helps the data scientist and IT minds stimulating the things before manufacturing the actual device. 

Digital twins incorporates Big Data, Artificial Intelligence(AI), Machine Learning(ML) and Internet of Things(IoT) which are also the main key and are predominantly used in the industry of IoT these days. 

Types : 

Later down the line concept of digital twin was divides into different types  

1. Digital Twin Instance (DTI) : Its done once the product gets manufactured and accessed then individual has its instances.
2. Digital Twin Prototype (DTP) : It undertakes before the final physical product is created, it contents designs, analysis and process which realizes the final product.
3. Digital Twin Aggregate (DTA) : Gathers information to check and determine the capabilities of a product which includes parameters i.e. Run prognostic and test operation.

Characteristics :

Digital twin technology have certain specific characteristics with various consequence, lets discuss some of them.

1. Connectivity :

IoT has introduced forward numerous technologies and the foremost technologies enables connectivity between digital counterpart and physical component. So it’s all dependent on connectivity, digital twin would not exist without it.

2. Homogenization :

Digital twin can be characterized as a digital technology. But in both cases’ homogenization of data takes place, due to this fact any kind of data can be transmitted or stored in a digital form and later used for virtual representation. Therefore, data homogenization and decoupling of information is responsible for existence of digital twin.

3. Digital Traces :

Another major features noticed is digital twin always digital traces. These traces are useful for the technical engineers to diagnose when any problem is faced which eventually improves the quality and avoids malfunction in the future.

4.Reprogramming and Smart :

Digital twin is reprogrammable in several ways which includes auto manner. Through help of sensor of physical product, Artificial intelligence and predictive analysis.

Pros : 

1. Industries monitor constant stream of usages and all round performance in day to day life.
2. End to end assets or product life cycle data can be combined into digital threads.
3. New products are provided which promotes service business model.
4. Digital twins accelerate field of medical innovation in various ways.

Cons :

1. The successfully depends on internet connectivity.
2. No surety of security.
3. The concept of digital twin Morley based on 3D CAD models.
4. Globalization and modern technology can be challenging for the suppliers.

Finally, data twins allow the enhancement of business strategy, prevents costly failures in physical objects and also uses advanced analytical, monitoring and test process. It’s a mix of the latest machine learning and Artificial intelligence tools which overly helps the digital world in productivity, performance and maintenance.