Have you ever considered how modern enterprises can forecast maintenance requirements, model a whole factory, or even optimize workflows without interfering with real-world operations?

Introducing digital twin technology; a technology that is not only innovative but also necessary for companies looking to innovate and increase efficiency.

A remarkable 25% increase in operational efficiency has been reported by businesses that deploy digital twins. Why?

Because by eliminating uncertainty from decision-making, these virtual duplicates help businesses forecast results and keep aware of costly errors.

Consider overseeing an exquisite electronics plant where delays are caused by misaligned conveyors. By simulating the production line, detecting problems early, and streamlining processes, a digital twin ensures efficiency while saving time and money.

In light of this, the blog will break down the four main categories of digital twins—component, product, system, and process for better insights on digital twins.

1. Process Digital Twin

Process twins, the superior type of digital twins, combine system twins into a single entity to investigate system synchronization and cooperation. This system provides the most comprehensive picture of how things happen inside the factory or plant.

Therefore, it enables a far more in-depth and flexible output examination.

Process twins helps in:

• Adjust inputs without disruption: Process twinning enables adjustments to factors like raw material feeding rate and manufacturing climate without impacting the manufacturing process or compromising quality.

• Test predictions risk-free: Executives can simulate various business scenarios safely, avoiding reliance on intuition or theoretical assumptions.

• Monitor KPIs efficiently: Provides real-time tracking of key performance indicators to ensure data-driven decision-making and improved operational effectiveness.

For instance, a process twin could simulate every aspect of the plant, even down to the workers running the machinery on the production line. In contrast, a system twin might simulate a manufacturing process.

Also read: How Digital Twin Platforms are Transforming Industries

2. System/Unit Digital Twin

System twins are copies of assets that show how multiple components come together to form functioning components at the system level.

System twins provide a:

• Comprehensive view: System twins offer a detailed perspective of the entire plant or manufacturing facility.

• Optimize systems: Enable testing of different system settings for maximum efficiency and uncover opportunities for new income streams.

• Asset group focus: Cover a group of assets performing specific functions, such as primary product manufacturing or energy delivery.

• Advanced capabilities: Go beyond detecting errors and breakdowns, providing continuous tracking and modeling for deeper insights.

• Strategic decision-making: Facilitate tactical choices with complete process transparency and critical operational information.

At this level, continual tracking and digital twin modeling go beyond the primary digital twins' ability to detect errors and breakdowns. It is a route to obtaining information necessary for making tactical choices and achieving complete process transparency.

Meanwhile, to develop a successful outcome from this innovation, you must partner with the best digital twin companies.

Big businesses mostly prefer process and system digital twins, with their increased complexity. This is because they are capable of financing long-term research and development initiatives. 

Consequently, these businesses are able to achieve higher degrees of intelligent automation. They free up workers from overwork, reduce the number of defective batches, and optimize the use of water and electricity. 

The system and process digital twins strengthen protection, or take complete control over their operations and production quality. These activities are primarily found in companies like Unilever.

Suggested read: Digital twin applications in various industries

3. Asset/Product Digital Twin

A product or asset digital twin is a digital replica of tangible assets such as machinery, buildings, and automobiles. It offers updated information on an asset's atmosphere, performance metrics, and functional health.

Product digital twin has the following characteristics:

• Integration of component twins: Asset/Product digital twins combine multiple component twins or their data to model complex assets like engines, pumps, or buildings.

• Performance analysis: Examine how components function as an integrated unit, identifying areas for optimization.

• Enhanced efficiency: Help engineers identify improvement opportunities, reducing downtime and improving operational effectiveness.

• Strategic insights: Provide valuable operational data, aiding in better equipment management and business innovation.

A good illustration of this situation is the compressed air solution maker Kaeser. This business tracked the amount of air that each of its items consumed using digital twin technology. Rather than offering their equipment for sale, they choose to bill clients based on the rate of air usage.

Please read: How much does it cost to develop a digital twin

4. Component/Part Digital Twin

The most basic type of digital twin technology is known as the component twin or parts twin. It is equivalent to the simplest components of the system, such as a particular piece of machinery or a product, like a sensor, switch, valve, etc.

Component digital twins has the following features:

• Function monitoring: Sophisticated parts can have their functionality tracked and current conditions simulated using digital models.

• Performance assessment: Evaluate reliability, durability, and effectiveness to ensure optimal operation.

• Simplified factory representation: Part-level digital twins offer a basic resemblance to the factory architecture for focused monitoring.

• Enhanced maintenance: Enable better equipment component monitoring, ensuring timely maintenance and reducing downtime.

• Operational reliability: Guarantee consistent manufacturing operations and maintain the quality of the final product.

Further read: Why Digital Twins Are Key to Sustainability in Business

1. Ford

Ford was among the first businesses to adopt a digital twin in automotive. The company ensures that resources are used wisely and that things are made as successfully as possible by using digital twins. This helped them track and oversee their manufacturing operations in real-time.

Ford employs digital twins in manufacturing to enhance product design. For instance, the company utilizes it to model how various manufacturing techniques affect the longevity of its goods.

2. Intermarche 

The French grocery operator Intermarché uses digital twins to enhance customer experience during purchasing. The digital twin monitors clients' movements and examines how they engage with objects. This provides Intermarché with information on what consumers are attracted to and how they communicate with them. 

Following that, customized advertising initiatives and enhanced product positioning and design may be made using this data.

Further, Intermarché uses digital twins in the supply chain to enhance operations in addition to consumer research. For instance, the business has optimized inventory levels and modeled the effects of varying weather on the availability of products using digital twins.

3. The Living Heart Project 

Could you visualize studying the heart with digital twins in the healthcare sector? 

The Living Heart Project is a research project aimed at revolutionizing healthcare industry education and training through the use of digital twins in clinical trials. 

By using a virtual duplicate of the organ, doctors can examine the function and movement of a human heart in ways that are not feasible with live hearts. Thus, medical experts can create novel medicines and advance their knowledge of heart disease.

This innovative technology has the potential to lower expenses and delays, given that heart disease is the primary cause of mortality worldwide. Additionally, implementing digital twins in healthcare boosts patient safety and fosters confidence.

4. GE Aviation 

GE uses digital twins to enhance the efficiency and appearance of various items, such as gas turbines and jet engines. 

The business has developed a "virtual engine" with digital twins that allows it to test concepts and plans before putting them into practice. This streamlines the manufacturing procedure and lowers the possibility of an unsuccessful outcome.

GE has benefited clients by using digital twins' real-time monitoring abilities to save 1.6 billion dollars. By taking an upfront, complete assessment of the product, they have also been able to cut wasteful production by up to 75% and overall expenses by up to 30%.

A growing number of industries have begun to realize the potential that exists inside digital twins in the past decade. Manufacturing continues to be a leader in the acceptance and development of digital twins. This is despite the fact that we can observe successful instances of digital twin implementation in the fields of healthcare, logistics, retail, and e-commerce. 

Numerous global industrial giants, such as Ford, GE, Tesla, Microsoft, and IBM, share their remarkable outcomes from implementing digital twins. 

Meanwhile, you must partner with the right digital twin company to gain the best insights into your idea.  

Toobler can be your best digital twin partner, with experience across different industries. Toobler is a digital twin consulting firm that specializes in offering customized digital twin solutions for a range of sectors and uses. 

Our proficiency in creating Digital Twins, together with our use of cutting-edge technology and industry best practices, allows us to offer scalable, economical, and practical solutions that maximize the performance of tangible assets or systems. 

Connect with us right now to get your digital twin readiness into reality. 

1. What are the key benefits of digital twins?

The key benefits of digital twins are:

• Real-time monitoring: Track operations and performance in real-time.

• Predictive analytics: Identify potential issues and optimize processes.

• Cost reduction: Minimize wastage and prevent costly errors.

• Enhanced decision-making: Leverage accurate simulations and data insights.

• Innovation support: Test ideas virtually to accelerate innovation.

• Reduced downtime: Implement predictive maintenance to avoid disruptions.

• Improved customer satisfaction: Deliver personalized solutions using detailed user and product data.

2. How do process twins improve operational efficiency?

Process twins improve operational efficiency through these:

• End-to-end visibility: Provide a detailed view of workflows and operations.

• Optimization insights: Identify bottlenecks and inefficiencies in real-time.

• Scenario simulation: The test process changes virtually before implementation.

• Predictive capabilities: Anticipate and resolve issues before they escalate.

• Data-driven decisions: Enable smarter decision-making with actionable insights.

• Resource management: Optimize resource allocation to reduce waste.

• Performance tracking: Continuously monitor and enhance operational performance.

3. Can different types of digital twins work together?

Yes, several kinds of digital twins can collaborate to build an all-encompassing, networked system. For example, system twins combine many components for optimal operations, whereas product twins can work with process twins to improve production efficiency.

Integrating these digital twins facilitates better insights, smooth data exchange, and comprehensive decision-making. This integration optimizes productivity by guaranteeing that all system components—products, processes, and environments—are harmonious and operating as a single unit.

4. Are digital twins applicable to non-physical processes?

Yes, non-physical processes can greatly benefit from the use of digital twins. By simulating software systems, financial models, customer journeys, and workflows, they can provide real-time insights and predictive analytics.

Digital twins, for instance, can be used to assess the effects of policies, simulate market trends, and optimize supply chains in business processes. By developing a virtual version of intangible processes, organizations can improve decision-making, detect inefficiencies, and improve results without interfering with real-world operations.

They are, therefore, instrumental in both the physical and non-physical spheres.