Understanding Digital Twins in Manufacturing
Digital twins are much more than static digital models or traditional simulations. They connect virtual environments with physical systems, enabling manufacturers to access real-time insights, improve operational visibility, and support more informed decision-making.
Despite their growing importance, the term “digital twin” is often used inconsistently. Digital models, digital shadows, simulations, and digital twins are sometimes treated as if they mean the same thing, even though they have distinct capabilities and levels of connectivity.
This article explains what digital twins are, how they differ from other digital representations, where they create value in manufacturing, and why they are expected to play an increasingly important role in the future of industrial operations.
What Is a Digital Twin?
A digital twin is a dynamic digital representation of a physical asset, process, production system, or manufacturing facility. It continuously exchanges information with its real-world counterpart, creating a connection between physical operations and the digital environment.
This two-way flow of data allows manufacturers to monitor performance, identify potential issues, test improvements, and optimize processes using current operational information.
To understand digital twins more clearly, it is useful to distinguish them from other types of digital representations.
Digital Model
A digital model is a virtual representation of a product, machine, process, or factory layout. It may be used for visualization, design, or simulation, but it is not connected to real-time information from a physical system.
Digital models can support planning and analysis, but they do not automatically reflect changes occurring in actual operations.
Digital Shadow
A digital shadow receives data from its physical counterpart. This one-way connection allows the digital representation to remain updated and supports monitoring and analysis.
However, the digital environment does not send information or instructions back to the physical system. As a result, it can observe operational conditions but cannot directly influence them.
Digital Twin
A digital twin establishes a continuous, two-way relationship between a physical system and its digital counterpart.
This connection enables manufacturers to monitor live performance, predict potential failures, evaluate operational changes, and improve processes based on real-time information.
Where Digital Twins Create Value in Manufacturing
In manufacturing, digital twins are particularly valuable when applied to production facilities and operational processes.
Plant and process digital twins go beyond visualization by combining simulation capabilities with operational data. This allows manufacturers to better understand how systems perform and evaluate potential improvements before making changes in the physical environment.
Several applications are already demonstrating the value of this technology.
Virtual Commissioning
Virtual commissioning allows manufacturers to test automation systems and control logic in a digital environment before implementation.
Traditional virtual commissioning is generally used during the design and validation stages. Once the physical system becomes operational, however, the original simulation may no longer reflect changes occurring in the real production environment.
Digital twins can extend virtual commissioning beyond a one-time validation process.
By maintaining a connection with operational data, a digital twin can support continuous performance monitoring, predictive maintenance, system analysis, and ongoing optimization. Manufacturers can identify potential issues earlier and make improvements based on actual operating conditions.
This level of visibility can also support safety and compliance efforts by helping organizations evaluate whether automation systems continue to perform according to relevant requirements during real-world operations.
Continuous Process Optimization
Manufacturing environments are constantly changing.
Production demand may fluctuate, equipment may experience wear, product requirements may evolve, and unexpected bottlenecks may affect workflow. A process that performs efficiently under one set of conditions may require adjustments when operational circumstances change.
Digital twins help manufacturers respond to these changes by providing a clearer view of how processes are performing in real time.
For example, in a packaging operation, changes in production volume or supply chain conditions may create congestion in specific parts of the workflow. A digital twin can help identify these issues and support decisions related to production flow, equipment speed, routing, or batch sizes.
By continuously analyzing operational conditions, manufacturers can maintain more consistent throughput, reduce disruptions, and improve overall efficiency.
Workforce Training and Knowledge Retention
Training employees in manufacturing environments can be challenging. Complex equipment, automated systems, safety requirements, and ongoing production schedules may limit opportunities for practical learning.
Digital twins provide a virtual environment where employees can explore equipment, understand production processes, practice operational procedures, and simulate troubleshooting activities without affecting live production.
This interactive approach can provide several benefits:
- Reduce onboarding time.
- Improve employee preparedness.
- Support safer training environments.
- Allow teams to practice different operational scenarios.
- Preserve knowledge as experienced employees transition to new roles or leave the organization.
Digital twins can also support continuous workforce development. As manufacturers introduce new robotics, automation technologies, or production processes, training environments can be updated to reflect current systems and operating practices.
This makes learning more adaptable and helps organizations develop the skills required for increasingly advanced manufacturing operations.
Why Simulation Is an Effective Starting Point
A fully integrated digital twin that connects every machine, process, and data source may appear complex and costly, particularly for organizations at the beginning of their digital transformation journey.
Simulation provides a practical starting point.
Simulation platforms allow manufacturers to design, test, validate, and optimize production systems in a controlled digital environment. Teams can evaluate factory layouts, process flows, automation strategies, and operational improvements before applying changes to physical operations.
This approach reduces risk and helps organizations understand the potential impact of decisions before committing significant resources.
Rather than transforming an entire facility at once, manufacturers can begin with a single process or production area. They can test concepts, validate improvements, measure results, and gradually expand their digital capabilities.
This phased approach makes digital transformation more manageable and creates a foundation for future digital twin implementation.
Digital Twins, Artificial Intelligence, and the Future of Manufacturing
The combination of digital twins and Artificial Intelligence (AI) is expected to create new opportunities for manufacturing.
AI can improve the predictive capabilities of digital twins by analyzing operational data, identifying patterns, detecting potential problems, and recommending actions before disruptions occur.
Instead of only notifying teams that equipment may fail, AI-enabled systems could help determine the most effective response and support preventive maintenance decisions.
AI-driven analytics may also contribute to:
- More accurate demand planning.
- Improved inventory management.
- Reduced material waste.
- Better use of production resources.
- More efficient energy consumption.
- Faster and more data-driven decision-making.
As technology becomes more accessible, comprehensive digital twins covering entire manufacturing facilities are also expected to become more common.
These systems could provide broader visibility across production operations and support real-time optimization at the factory level.
Sustainability will also play an important role in the development of digital twin technologies. By helping manufacturers reduce waste, improve energy efficiency, and optimize the use of resources, digital twins can support more environmentally responsible production.
Why Manufacturers Should Start Preparing Now
Manufacturers that begin exploring digital twin technologies today may be better positioned to improve efficiency, increase operational resilience, and strengthen their competitive advantage.
The journey does not need to begin with a fully connected digital replica of an entire factory. Organizations can start with simulation, evaluate individual processes, validate improvements, and expand their capabilities over time.
A structured and gradual approach can reduce implementation risks while helping teams develop the technical knowledge and operational experience needed for more advanced digital transformation initiatives.
Digital twins are expected to become an increasingly important part of modern manufacturing. By connecting physical operations with intelligent digital environments, they can support better visibility, predictive decision-making, continuous optimization, workforce development, and more sustainable production.
The future of manufacturing is becoming more connected, data-driven, and intelligent. Digital twins provide a practical pathway for organizations seeking to prepare for that future.
Source: Visual Components – Understanding Digital Twins in Manufacturing