What is Digital Twin Technology — Use Cases, Solutions, and Examples

What is a Digital Twin?

A digital twin, in simple terms, is a virtual model of a product, process, or service. By pairing the virtual and physical worlds, digital twins enable data analysis, system monitoring to alert problems, downtime prevention, and future planning via simulations.

The digital twin has smart components with sensors to gather real-time data, operational status, working conditions, etc. A cloud-based system receives and processes the data that these sensors monitor. An analysis is performed on this data against business and contextual data.

This entire process opens up vast opportunities by uncovering hidden information. These new learnings from the virtual environment can be applied to the real physical world, improving your business outcomes.

A Digital Twin Solution for Manufacturing Industry

Digital twins can provide highly customized solutions. Take drug manufacturing, for instance. Our global pharma client wanted to improve the visibility of their plant operations to predict the quality of the batches produced.

We built the digital twin of a chemical synthesis process monitor that could monitor the operations and create an alert in case of any sudden failure. It supports the operator in optimizing the yield by choosing the right process parameters.

It can also predict the yield quality of the drug under a given set of conditions or parameters. We deployed the process control monitor using the digital twin technology.

The solution has 4 components:

  • Mobile Alert: Open your mobile and put it in your pocket. You will get an alert when quality drops.
  • Floor Monitor: Display on a large screen on the plant floor. Operators can track in real-time when quality drops.
  • Predict Quality: Find out if a batch will produce a good result or a bad result — without running it.
  • Simulator: Re-run the last batch to explore the minimal change required to improve batch quality.

These four views were built in just 3 days using Gramex’s 8 components, replacing over 2,500 lines of code.

Watch the video to learn the exclusive features of our manufacturing digital twin

The client saved $2 Mn due to Golden Batch yield improvements.

Why Digital Twin is Gaining Popularity?

Innovation and performance play a key role in keeping an organization successful in the dynamic business landscape. IDC predicts that companies who invested in digital twin tech in 2018 will see a 30 percent improvement in cycle times of critical processes.

The next five years will see the rapid development of digital twins leading to interesting collaboration among physical world product experts and data scientists. It will reveal a lot about enhancing operations using data.

The digital twin is becoming so popular because organizations can employ their power to understand customer needs better, deliver an unmatched customer experience, develop product enhancements, optimize operations and services, and drive new business innovations.

It seems that the digital twin technology is on the verge of an explosion — As more success stories keep rolling out, more companies would want to deploy their digital twins to gain a competitive edge.

How Do Digital Twins Work? (The Concept of Process Simulation)

To start building a digital twin, applied mathematics or data science experts perform research on the operational data of a physical object or system to develop a mathematical model for process simulation.

The developers ensure that the virtual computer model receives sensor feedback about data from the real-world version.

Gathering performance insights and identifying potential problems becomes simple by creating a digital version simulation of what happens in real-time.

A digital twin can be either complex or simple, depending on the amount of data used to make the simulation. The twin may require a prototype to work and offer feedback on the product while it is developed.

It can also be made into a prototype that models what can occur with a physical version when built.

The digital twin is created by combining a set of data with computational modeling to verify it. The interface can include sending and receiving feedback and data in real-time between the digital model and the actual physical object.

Types of Digital Twins

As digital twins (DTs) are built from the bottom up, the lowest level is the simplest and yields the least amount of information, while the higher levels provide more sophisticated and diverse information. DT consists of an emerging hierarchy that includes:

Robust parts twinning is the foundation of digital twinning. Virtual representations of components at this level allow engineers to understand a part’s physical, mechanical, and electrical characteristics.

Computer-aided design/manufacturing (CAD/CAM) solutions today, for example, allow users to perform a variety of analyses relating to durabilities, such as static stress and thermal stress.

Using electronic circuit simulation software, for instance, we can predict how components will react to various electrical signals. In order to predict real-life behavior under different scenarios, it is necessary to build mathematical models with a sufficient amount of complexity.

While twinning individual components offer useful insights, twinning the interoperability of components as they work together is crucial to enabling product twinning.

As a result of knowing how parts work with each other and the environment surrounding them, owners are able to optimize the operating characteristics of their products, which minimizes such things as mean time between failures (MTBF) and mean time to repair (MTTR).

At a higher level, system twinning enables engineers to integrate, configure, and maintain an entire fleet of products working together to accomplish a result in a system.

Imagine an energy grid that can adjust the amount of electricity produced by monitoring the demand. You can extend this to any type of system family you want.

Communication systems and traffic control systems, as well as industrial manufacturing systems, will achieve unprecedented levels of efficiency and effectiveness with unprecedented monitoring and experimentation.

Besides physical objects, digital twinning can be applied to processes and workflows as well. Process twinning facilitates the optimization of operations involved in preparing raw materials for finished goods production.

A Digital Twin model would also be beneficial to workflows with a business focus, even if there are still humans involved. It would allow managers to tweak inputs and see how outputs are affected without disrupting existing workflows, which otherwise would make the business completely stop.

Through process twinning, senior corporate leadership will be able to monitor key metrics in a much more data-driven manner than previously possible.

Digital Twins Use Cases Based on Industries

By leveraging the power of big data, IoT, and AI, the Digital Twin allows for in-depth analysis. Simulation is helpful in detecting potential issues, preventing downtime, testing new business opportunities, planning future scenarios, and customizing production based on customer requirements.

Technology allows immediate feedback about current activities, which can then be applied to future changes in record time. Digital Twins are particularly useful for maintaining connected heavy machines and infrastructure that generate and analyze large volumes of data due to their functionality. The application of digital twins goes beyond this, however.

Take a look at a few use cases of Digital Twin:

Using digital twins in healthcare, physicians can experiment with different care delivery approaches, prevent disease years apart, and train for complex invasive procedures based on patient-specific anatomy.

A digital twin can provide healthcare organizations with insight that can lead to innovative practices that will correct issues and minimize potential risks. In addition, real-time epidemiology data can help hospital workers track where infections agents might exist and who might be at risk from contacts.

Healthcare providers can use digital twins to optimize patient care, cost, and performance by virtualizing healthcare experiences.

Digital twins are most commonly used in the manufacturing industry. A high volume of data is generated by high-cost equipment used in manufacturing, which facilitates the creation of digital twins. Manufacturing applications of digital twins include:

Engineers can use digital twins to test the feasibility of upcoming products before they are launched. In response to test results, engineers start producing or shift their focus to developing a practical product.

Digital twins enable businesses to design various permutations of products so that they can offer personalized products and services to their customers.

Monitoring and analyzing digital twins allows engineers to see which products contain defects or have lower performance levels than expected.

Digital twins are used by manufacturers to predict the potential downtime of machines so that maintenance efforts are minimal and machines are more efficient because the technicians can act before a breakdown happens.

An eco-economic and socially sustainable city can be helped through a Digital Twin. In addition to guiding their future plans, it enables users to create models that help solve complex issues confronted by cities.

A Digital Twin can provide city managers with information in real-time about flooding, interrupted infrastructure, and hospitals that are expected to be affected, allowing them to take immediate action in case of a disaster.

Human activities are causing Earth’s climate to change faster than it ever has, primarily because of the recent rise in global temperatures.

There have already been numerous impacts of global climate change across all regions and across many sectors of the economy expected to grow in the coming decades.

Fires, floods, and droughts are now commonplace. In such scenarios, Digital Twins allow for the construction of smarter infrastructure, such as dams, utility networks, emergency response plans, and zoned areas.

With the implementation of a digital twin, you can simulate business process outcomes in a virtual environment, improving efficiency and reducing supply chain costs — which can dramatically improve your ROI.

Real-world data about a physical object or system is used as input, and it produces output in the form of predictions or simulations of how those inputs will affect the object or system.

The following are some of the most common use cases across the industry:

  • Real-time visualization of products in use by real users
  • Troubleshooting equipment located far away
  • Complexity management and linking systems-of-systems
  • Integrating disparate systems to promote traceability

Operating Digital Twins integrate and correlate streaming IoT data with other inputs. This dynamic virtual representation of the entire plant is then created utilizing machine learning, artificial intelligence, and advanced modeling techniques.

Manufacturers gain full insight into how assets, processes, and operations are interconnected for the first time.

Digital Twins vs Process Simulations

A digital twin is a concept, not a product or technology. The concept will become a reality when a multitude of technologies are combined — 3D simulation, Internet of Things, 4G/5G, big data, blockchain, edge computing, cloud computing, and artificial intelligence.

The core principle consists of creating a digital equivalent of a physical asset or entity in the virtual world.

Many people ask, “Are Digital Twins and simulations the same thing?” As the concept of Digital Twins is so new, the question is quite natural. The digital twins aim to accomplish much more than simply simulate things.

It is common to use simulations for designing and, in some cases, for optimizing offline. A digital twin, on the other hand, can be used during every phase of design, execution, change, and decommission.

At best, simulations can help us understand what may happen in reality. Digital Twins help us understand not only what may happen, but also how it actually happens (how the design behaves in reality).

Simulations cannot provide insight into how physical systems interact. The digital twin, however, helps reveal clashes and conflicts when physical objects interact.

Industry Applications of Digital Twins

Drug development, supply chain management, and other manufacturing practices are being applied to digital twin concepts by the pharmaceutical industry with the aid of regulatory agencies and academic institutions.

A Pharma 4.0 strategy is in the works which will be flexible and based on International Council for Harmonization (ICH) guidelines, as well as Industry 4.0.

A digital twin technology creates a virtual model of a complex physical product that can be tested and improved before the physical product is built.

To identify potential problems and failures prior to production, companies can use digital twins to simulate and validate each step of the development process.

In addition to helping development teams to understand the effects of any potential changes in manufacturing processes on production outcomes, Twin Engineering helps them to adjust manufacturing operations to achieve targeted improvements.

Consequently, manufacturers can optimize operations and reduce the overall cost of engineering.

The manufacturing industry competes more and more as consumers demand customized products in shorter time frames due to their increased sophistication.

Compared to small businesses, industrial companies of all sizes place more emphasis on improving production processes and strengthening customer relationships than on meeting custom product requests as revealed by Industry Week’s special report on the future of manufacturing.

To simplify product customization, manufacturers embrace Twin Design Customization, which allows consumers to customize the physical product virtually before it is developed, ensuring their needs are fully met.

The use of digital twins can be used by engineers to test the viability of upcoming products before they are released. When engineers receive test results, they start creating a feasible product or change their focus.

Using Twin Operations Management, you can improve operational efficiency, preventive maintenance, and dynamic simulation. A real asset is embedded with IoT sensors, resulting in a continuous stream of real-time, dynamic information about the condition of the asset.

Digital replicas are built using static data and continuously updated dynamic information. Virtual monitoring and management of asset performance and manufacturing operations is possible for employees.

Benefits of Digital Twins: Reducing Cost & Optimizing Performance

Digital Twins, in general, are highly successful when it comes to providing new opportunities and increasing productivity and efficiency.

By implementing a Digital Twin, you can predict problems and prevent downtime, thus increasing productivity and reducing costs.

Utilize past performance data to create simulations and forecast future improvement strategies for the manufacturing process based on the conclusions from the simulations.

Manufacturing can be monitored with digital twins from design to completion. As a result of improving performance, production can be faster, which assists you in meeting your targets.

As a result of analyzing data in real-time, Digital Twins enable you to take preventive maintenance steps before long-term damage occurs. Preventing smaller technical problems from becoming much larger and more expensive breakdowns is always preferable.

In the meantime, you can keep hitting targets and prevent unnecessary losses because no production downtime occurs. Moreover, the simulations you create will allow for increased profitability without adding additional resources.

Transform Business, Improve ROI & Make Operations Seamless with Digital Twins

By creating a digital twin, businesses would be able to see the tangible value, create new revenue streams, and answer critical strategic questions.

Companies may now be able to create digital twins more quickly with lower capital expenditures and shorter time to value with new technology capabilities, flexibility, agility, and lower cost.

It can offer real-time answers to questions that couldn’t be answered previously, providing advantages that were unimaginable just a decade ago.

With the help of trusted technology partners and the identification of winning use cases, tangible business value and ROI can be obtained with digital twin implementation.

Providing additional stakeholders with key performance data and lowering costs throughout an organization can be accomplished by beginning with the design phase and continuing through servicing operations.

Providing transparency throughout an organization’s value chain through digital and physical convergence is becoming increasingly necessary as products move toward ‘as-a-service’ models.

By introducing and adopting the digital twin, we can accomplish this digital transformation and connect the digital thread.

Contact us for custom built low code data and AI solutions for your business challenges and check out digital twin solution built for our clients, including Fortune 500 companies. Book a free demo right now.

Contact Gramener for building custom digital twin solutions for manufacturing and pharma industry

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Gramener

Gramener

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Gramener is a design-led data science company that solves complex business problems with compelling data stories using insights and a low-code platform, Gramex.