Did you know that the origins of the digital twin can be traced all the way back to 2010, although the concept was conceived much earlier? In fact, as far back as the 1960s. In the last few decades, technology has been moving at the quickly, and this is why it is only natural that the digital twin concept would evolve as well.
In this article, we look at the rise of this new and improved tech, how it impacts the manufacturing world, and what it holds in store for us.
Facilitating cross-company collaboration
Unlike a traditional digital twin, which focuses primarily on monitoring and analyzing a single asset, a collaborative twin facilitates interaction and cooperation between different digital twins across various systems and organizations.
Key elements of this are as follows:
Interconnectivity
Collaborative twins connect multiple digital twins from various sources, enabling data exchange and collaboration across teams and organizations.
They allow real-time updates and insights, empowering participants to make informed decisions based on current data.
Multi-stakeholder collaboration
Collaborative wins support teamwork across departments, including R&D and manufacturing, enhancing communication and alignment. Stakeholders can jointly analyze scenarios and outcomes, leading to more effective and informed decision-making.
Advanced simulation and analysis
Teams can conduct simulations and evaluate various scenarios, identifying potential improvements or risks in interconnected systems. By analyzing data from multiple sources, companies can optimize processes and resources more effectively.
Feedback loop
Continuous feedback from stakeholders enables iterative improvements in processes and systems based on real-world performance.
Cross-company and interdepartmental optimization of processes and products
The collaborative digital twin enables a range of applications in manufacturing that would not be possible without this cross-company, interdepartmental approach. Key applications are listed below.
Integrated product development
Teams can collaborate across departments such as design, engineering, and production, using a shared digital twin of a product. This allows for real-time feedback and iteration. It also accelerates product development cycles, shortens time-to-market, and enhances product quality through cross-functional insights.
Supply chain optimization
The collaborative twin can integrate data from suppliers, manufacturers, and distributors, providing a comprehensive view of the supply chain. This results in improved inventory transparency, demand forecasting, and logistics, leading to shorter lead times, reduced costs, and greater responsiveness to market changes.
Predictive maintenance
By combining data from various machines and sensors, collaborative digital twins offer insights into equipment condition and performance across the manufacturing floor. This information does not only benefit the machine operator but also the manufacturer, who can proactively replace defective parts, minimizing downtime.
Quality assurance and control
Data from various quality control points can be aggregated throughout the manufacturing process, enabling real-time monitoring. This improves the ability to detect errors early in the production process, leading to higher product quality and reduced waste.
Remote monitoring and support
Engineers and technicians can use collaborative digital twins to remotely monitor equipment and processes, providing expert support from anywhere in the world. This leads to faster response times for issues, lower travel costs, and improved collaboration among geographically dispersed teams.
Making a difference
In addition to all this, collaborative digital twins can be applied in various areas such as employee training and onboarding, energy management, and the customization and mass personalization of products.
Ultimately, this new evolution represents a significant advancement in the use of digital twins, enabling enhanced collaboration between multiple stakeholders and systems. By fostering real-time data exchange and collective analysis, this can drive innovation, efficiency, and improved outcomes in the manufacturing industry.
Want to learn more about collaborative digital twins and how this can make a difference in your business? Connect with me and let’s discuss.
