Combined Power of IoT, AI, Data, Cloud, and Machine Learning

Digital Twin Solutions

An architectural overview and business value for the industry

Purpose of the Article

In this article, I introduce the Digital Twin concept as an emerging technology construct used in various industries.

My aim is to give an overview and shed light on this emerging technology, architectural construct, and business initiative based on my experience. I explain the digital twin concept using the Cyber-Physical System architecture, business use cases, and value proposition.

The Digital Twin concept is simple; however, manifesting them, in reality, can be complex and challenging due to the combination of underlying technology stacks, tools, and integration requirements. Therefore, a structured and methodical approach to the topic is essential.

What is a Digital Twin?

At the highest level, a digital twin (DT) is an architectural construct that is enabled by a combination of technology streams such as IoT (Internet of Things), Cloud Computing, Edge Computing, Fog Computing, Artificial Intelligence, Robotics, Machine Learning, and Big Data Analytics.

Even though the term digital twin was coined in 2002 by Michael Grieves at the University of Michigan, this technology architecture was used by NASA in the Apollo 13 program in the 1970s.

The goal was to create identical space vehicles, one in space and one on earth. But we lacked the underlying technology capabilities in those days: no Cloud, no ML, no IoT, no Big Data.

With limited capabilities, this approach enabled NASA engineers to manage the physical device using the virtual counterpart on the surface.

As you may have read, the famous book, Mirror Worlds by David Gelernter, popularized the concept in 1993.

The digital twin concept turned into reality thanks to rapidly grow new technology stacks and capabilities such as Cloud, IoT, AI, and Big Data.

DT nowadays is used in various industries, in large business organizations, and startup companies. The manufacturing industry embraced it for its compelling business proposition. There are many DT initiatives globally.

DT initiatives use the PLM (Product Lifecycle Management) method.

PLM is implemented using various agile approaches integrated with propriety methods belonging to business organizations. The method is supported by Design Thinking workshops during the conceptual stage. You can find more on Design Thinking in the attached article.

To add clarity, let me give you an architectural overview of the DT concept.

The Architecture of the Digital Twin Concept

In the DT concept, each physical object has its virtual counterpart. These virtual counterparts are called virtual mirror models. These virtual mirror models have built-in capabilities to analyze, evaluate, predict, and monitor physical objects.

This innovative architecture of the DT concept creates a powerful communication mechanism between the physical (material) and the virtual world by using data.

In DT architecture, physical and virtual components integrate synchronously to create a close loop.

Digital twin initiatives are the practical implementation of Cyber-Physical Systems (CPS) architecture in engineering and computer science domains. To understand the technical aspect of the digital twins, we need to know the CPS architecture.

In a nutshell, CPS is a technical construct converging physical and virtual domains. The core architecture of CPS is to embed communication and computing capacity into physical objects so that physical objects can be coordinated, controlled, and monitored via virtual means.

CPS integrates physical processes, computing, and networking as a single entity called embedded object. We can use embedded objects in various devices and appliances. The prime examples are medical devices, scientific instruments, toys, cars, fitness clothes, and other wearables.

CPS requires architectural abstraction and modeling. Based on the models, we can develop designs leveraging computation power, data, and application integration for monitoring physical phenomena such as heat, humidity, motion, and velocity.

CPS can leverage the IoT (Internet of Things) technology stack. CPS can be part of the IoT ecosystem in global IoT service providers. You can read the details of the IoT ecosystem in the attached article.

The scalability and capacity of the embedded objects are critical. You can read more about the architectural implications of the scalability and capacity of IoT devices from this article.

Use Cases and Business Value of Digital Twin Initiatives

The primary use case for DT is asset performance, utilization, and optimization. DT enables monitoring, diagnosing, and prognostics capabilities for this use case.

For example, DT can be used to optimize cars, locomotives, and jet engines. This use case can improve productivity and customer satisfaction.

DT can be ideal for creating 3D modeling of digital objects from physical objects. This use case is a critical success factor for smart manufacturing initiatives.

DT is commonly used for identifying symptoms with constant monitoring and finding the root causes of production issues in factories. The business value of this use case is to improve productivity.

Healthcare projects commonly use DT for simulation purposes. For example, doctors practice risky operations in simulated environments before attempting them on patients. This approach addresses safety concerns.

Town planners use DT initiatives by using virtual models to improve the city conditions in a proactive manner. This approach can reduce the complexity and simplify the processes for planners.

In Enterprise Architecture initiatives, we use DT as an architectural blueprint of the business organization. This helps us articulate the big picture to our business stakeholders.

As a stream of the hyper-automation concept in the IT industry, we use DT as part of the Robotics Process Automation (RPA) initiatives. You can check the details on RPA in my attached article.

Conclusions

A digital twin is a reality now. It is not a concept anymore.

Even though it is seen as an emerging technology, it is widely used in various industries such as manufacturing, automotive, healthcare, and smart cities.

There is a growing interest in the use of this technology globally. For example, last week in Australia, the NSW government launched a large DT initiative. The initiative includes the virtual environment of more than half a million buildings.

Understanding the underlying technology stacks is critical for architecting and designing digital twin solutions. To this end, the key technology considerations are IoT, Cloud, Edge, Fog, AI, ML, Robotics, and Big Data Analytics. You can check the following articles related to these technology domains.

As a concluding remark, while architecting and designing digital twin solutions, we need to understand the business goals, requirements, and use cases based on the industry.

There may be additional industry compliance and ethical considerations that solution architects and designers need to know upfront.

I covered more points about the activities of solutions architects in the attached handbook on Medium.

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