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Digital Twin Is The Key To Industry 4.0

A digital twin is an elementary component of industry 4.0 that..


A digital twin is an elementary component of industry 4.0 that focuses on a virtual representation of a system or an object, which stays updated from real-time data and spans its lifecycle. It uses the techniques of machine learning, simulation, and logical reasoning to help people make well-informed decisions.


Several technologies have evolved over the years that are essential in driving the advancement of the Industrial Internet of Things (IIoT) and smart manufacturing. While all these technological advancements are shaping the future of manufacturing, the digital twin has the most significant impact on how companies implement smart manufacturing.

What is Digital Twin?

Digital Twins have evolved over the years and become an important part of manufacturing. The basic concept of the digital twin involves merging virtual engineering models with the physical equipment in an environment that allows for optimization of that product or production system. It acts as a real-time bridge between the digital and physical worlds and enables you to remotely monitor and control systems. Finally, it can implement simulation models to test and forecast assets and process changes under different “what-if” scenarios.

Smart manufacturers can minimize the time and cost that comes along with assembling, installing, and enabling factory production systems. Moreover, implementing digital twins to manage assets promises quantifiable benefits for maintaining those assets in the field.

Leveraging digital twins, companies can realize substantial benefits such as improved operations, product and service innovation, and faster time-to-market.

Types of digital twins

There are several types of digital twins depending on the level of product magnification and their area of application. It is a common practice to have different types of digital twins co-exist within one business ecosystem.

Component Twins/Parts Twins

Component twins are the basic unit of a digital twin. They are mostly the same thing but concerned with components of lesser importance.

Asset Twins

When two or more components work together, they form an asset. Asset twins allow you to study the interaction of those components and generate a wealth of performance data to be processed. Later it is turned into actionable insights.

System or Unit Twins

A more advanced level of magnification involves a system or unit twins that enable you to see how different assets come together to develop an entire functioning system. It provides visibility regarding the interaction of assets and may suggest performance enhancements.

Process Twins

Process twins are the macro-level magnification that reveals how systems work together to create an entire production facility. Process twins can help determine the precise timing schemes that influence overall effectiveness.

3 Applications Areas of Digital Twins for Industry 4.0

Digital twin technology renders extraordinary prominence into assets and production to streamline operations, spot bottlenecks and innovate product development.

Below are the three major applications of digital twins for Industry 4.0.

Predictive Maintenance

An overall view of the health and performance of manufacturing equipment. Smart manufacturers can immediately detect anomalies and deviations in their operations. Maintenance and replacement of spare parts can be proactively planned to reduce time-to-service and avoid costly asset failures.

Process Planning and Optimization

A digital footprint ingesting sensor and ERP data of a manufacturing line can comprehensively analyze vital KPIs like production rates and scrap counts. This helps identify the root cause of any inefficiencies and throughput losses, thereby optimizing yields and reducing waste.

Product Design and Virtual Prototyping

Virtual models of in-use machinery offer comprehensive insights into usage patterns, degradation points, workload capacity, incurring defects, etc. Having a better understanding of a product’s characteristics and failure modes, designers and developers can correctly evaluate product usability and improve future component design.

Digital twin technology additionally aids in developing virtual prototypes and running vital simulations for feature testing based on empirical data.

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