The Importance of Virtual Twins in Manufacturing Operations

Virtual twins are revolutionizing manufacturing operations by enhancing operational efficiency, reducing downtime, and optimizing resource utilization.

Introduction

Digital transformation has been a central theme in manufacturing for over a decade, yet its importance continues to grow as new challenges and opportunities emerge. While many organizations have made significant strides in digitizing their operations, the journey is far from complete. The integration of advanced technologies like AI, IoT, and big data analytics is pushing the boundaries of what’s possible, making digital transformation a constantly evolving field.

At the heart of this evolution is the emergence of the virtual twin, an advanced iteration of the digital twin that is becoming indispensable for companies to realize the benefits of AI and other emerging technologies. The rise of the unified namespace—a single, consistent reference point for all data across operations—is driving this evolution, enabling virtual twins to seamlessly integrate data from disparate sources. This capability is essential for accurately simulating, predicting, and optimizing operations. As the manufacturing landscape becomes more complex and competitive, the ability to dynamically simulate, predict, and optimize operations through virtual twins is not just advantageous—it’s essential. Companies like Arch Systems and Dassault Systèmes are at the forefront of this transformation, driving innovation and setting new standards for efficiency and insight in manufacturing operations.

What is the difference between a digital and virtual twin?

Digital twins have long been used in manufacturing as digital replicas of physical assets, processes, or systems. These models allow manufacturers to simulate and analyze operations by providing insights into production processes without the risk and expense of real-world trials. Digital twins have been helpful in improving efficiency; however, they are often static or limited in their ability to reflect real-time changes.

The concept of the virtual twin marks a significant evolution beyond traditional digital twins. While a digital twin is a snapshot in time, a virtual twin is a dynamic, continuously updated model that integrates real-time data from across the entire manufacturing ecosystem. This real-time integration is enabled by technologies such as IoT sensors, advanced analytics, and AI, all harmonized through a unified namespace.

Here are the key differences and why they matter:

• Dynamic vs. Static: A digital twin typically relies on historical data or periodic updates, which means it may not fully capture the current state of operations. A virtual twin, on the other hand, is continuously updated with real-time data, providing a living, breathing model that evolves alongside the physical environment it represents.
• Holistic Integration: Digital twins often focus on specific assets or processes, which can lead to siloed insights. Virtual twins integrate data from across all aspects of the manufacturing operation, including machines, processes, and even human inputs, creating a comprehensive, unified model that offers a more complete picture of the factory’s operations.
• AI-Driven Insights: While digital twins are powerful for simulation and analysis, they often require manual interpretation to derive actionable insights. Virtual twins, by contrast, are designed to leverage AI and machine learning algorithms to automatically generate insights, predict outcomes, and suggest optimizations, reducing the need for human intervention and enabling more proactive decision-making.
• Support for AI and Future Technologies: Digital twins provide a foundation for analysis and optimization, but their static nature limits their ability to support more advanced AI applications. Virtual twins are built with future technologies in mind, serving as the backbone for AI-driven innovations, such as predictive maintenance, autonomous operations, and real-time decision support.

In summary, while digital twins have been and continue to be valuable tools for manufacturers, the virtual twin represents the next generation of this technology. It not only captures the current state of operations in real-time but also integrates seamlessly with AI and other advanced technologies, providing a comprehensive, actionable model that drives continuous improvement across the entire manufacturing ecosystem.

Importance of virtual twins in manufacturing operations

Virtual twins are revolutionizing manufacturing operations by enhancing operational efficiency, reducing downtime, and optimizing resource utilization. One of the key strengths of a virtual twin is its ability to act as a copilot for factory personnel—from the shop floor to the executive level—by providing real-time, actionable insights that improve decision-making and process efficiency.

A unified namespace plays a critical role in this process by ensuring that all relevant data, whether from machines, sensors, or even the tacit knowledge of experienced workers, is available in a single, accessible framework. This integration is essential because, to truly maximize the impact of a virtual twin, it must encompass not only the data generated by machines but also the deep, experience-based knowledge held by factory experts.

This tacit knowledge, often gained over years of hands-on experience, is a vital component of manufacturing operations. When captured and integrated into the virtual twin, it enriches the system’s ability to predict and resolve issues, providing a more holistic and effective tool for managing complex manufacturing environments.

Elements of virtual twin Implementation

Implementing a virtual twin involves more than just digitizing existing processes. It requires a strategic approach that includes:

• Scope of Operations: A clear understanding of which processes and systems need to be included in the virtual twin.
• Need for Real-Time Information: Continuous data flow from all relevant sources, ensuring the virtual twin reflects the current state of operations.
• Data Integration and Management: Seamless integration of data from various sources, including IoT devices, sensors, and human expertise, to create a unified model.
• Product/Resource and Data Models: Developing both physical and data models that allow accurate simulations and analyses, forming the backbone of AI-driven insights.

Key benefits of virtual twins

The benefits of virtual twins extend far beyond operational improvements:

• Real-Time Monitoring and Management: Virtual twins enable continuous monitoring and adjustments, ensuring that operations are always running at optimal levels.
• Enhanced Accuracy in Simulations: With a virtual twin, simulations are not just accurate but also predictive, allowing manufacturers to anticipate issues before they occur.
• Improved Collaboration: Virtual twins serve as a common platform for all stakeholders, facilitating better communication and collaboration across departments.
• Optimization of Asset Utilization: By providing a complete view of asset performance, virtual twins help in making informed decisions about maintenance and resource allocation, leading to improved ROI.
• Support for Sustainable Manufacturing: Virtual twins contribute to sustainability by optimizing energy use, reducing waste, and ensuring that resources are used efficiently.

Real-World applications of virtual twins

Both DELMIA and Arch Systems have driven innovation in Virtual Twin technology for manufacturers who are driving digital transformation in their organizations.

The DELMIA Virtual Twin Experience is a transformative platform designed to enhance manufacturing efficiency by simulating operations in a digital environment. In practice, this solution excels in the high-tech manufacturing sector by reducing the time and cost of new product introductions. By providing a comprehensive virtual model of manufacturing operations and processes, it empowers manufacturers to remove production risks, minimize equipment downtime, and streamline production processes. This leads to improved operational efficiency and significant cost savings, positioning companies to better respond to market demands.

ArchFX enhances the power of virtual twins by leveraging data from all facets of the manufacturing environment. This advanced data platform, meticulously designed for manufacturing efficiency, seamlessly integrates with existing machines and systems, significantly reducing the time and resources manufacturers typically invest in creating value from a virtual twin. By integrating this rich dataset into the virtual twin, manufacturers can achieve a more accurate and dynamic representation of their operations. This holistic approach empowers manufacturers to drive continuous improvement, reduce downtime, and optimize resource utilization across the entire production lifecycle. With Arch Systems’ solutions, manufacturers can enhance their virtual twin models, ensuring that they are not only reflective of the current state but are also predictive and prescriptive, allowing for proactive decision-making and superior operational outcomes.

Conclusion

The transformative impact of virtual twins on manufacturing operations is clear. As manufacturers navigate the complexities of modern production, the adoption of virtual twins will become increasingly essential. Not only do they provide the foundation for AI-driven innovation, but they also unlock new levels of efficiency, productivity, and sustainability. By integrating technology that preserves and enhances both digital and tacit knowledge, manufacturers can secure their operations today and lay the groundwork for a more efficient, AI-driven future.

Call to Action

To learn more about how virtual twins can revolutionize your manufacturing operations and set the stage for future AI applications, explore the cutting-edge solutions offered by Arch Systems and DELMIA.

In addition:

Register for our webinar: “Maximizing Manufacturing Efficiency with Real-Time Production Monitoring” Wednesday, September 25, 2024 at 1:00pm EDT