- Twins for System Prediction (30% of projects) These digital twins focus on predicting the future behavior and performance of entire systems, helping businesses plan and optimize based on accurate forecasts. By using current data and operational history, companies can anticipate future outcomes, ensuring smoother operations.
- Example: Doosan Enerbility deployed a digital twin for its wind farms to predict power output based on IoT sensor data and weather conditions, improving operational performance and helping avoid costly fines by meeting power commitments.
- Twins for System Simulation (28% of projects) Simulating complex systems during the “build,” “operate,” or “optimize” phases allows engineers to test scenarios and make informed decisions. These twins help reduce risks and costs by running multiple simulations before changes are implemented.
- Example: Siemens Mobility created a digital twin to simulate 40 different subsystems of a new train control architecture, reducing development costs by $1-8 million.
- Twins for Asset Interoperability (24% of projects) These twins streamline data formats and enable efficient data extraction across complex systems, ensuring real-time, standardized information flow. This is critical for companies managing many assets that need to communicate and function together seamlessly.
- Example: Scuderia Ferrari uses a digital twin to integrate and analyze sensor data from their F1 cars, allowing different teams to collaborate on decisions around aerodynamics, power, and race dynamics.
- Twins for Maintenance (21% of projects) Digital twins designed for maintenance help predict equipment failures and guide maintenance personnel during repairs. Predictive maintenance reduces unplanned downtime and extends asset life, making these twins vital for operational efficiency.
- Example: E.ON developed a digital twin to shift to predictive maintenance, evaluating failure modes and determining the remaining life of critical equipment, improving overall reliability.
- Twins for System Visualization (20% of projects) These digital twins provide visual representations, often in 3D, to improve transparency and understanding of system operations. Whether managing infrastructure or manufacturing processes, visualization twins offer clear insight into complex systems, helping to prevent issues and optimize performance.
- Example: Ferrovie dello Stato, Italy's national railway, developed a digital twin of its 10,000-mile rail network, using sensors and algorithms to create a 3D model that improves remote monitoring and safety.
- Twins for Product Simulation (9% of projects) Primarily used in the design and development phases, product simulation twins allow companies to test product designs virtually, avoiding the need for costly prototypes. This accelerates development and ensures higher product performance.
- Example: Krones used a digital twin to test new packaging robot designs by simulating factors like friction and gravity, reducing development time and improving efficiency.
?????Trusted IT Solutions Consultant | Technology | Science | Life | Author, Tech Topics | Goal: Give, Teach & Share | Featured Analyst on InformationWorth | TechBullion | CIO Grid | Small Biz Digest | GoDaddy
1 周Absolutely, digital twins are revolutionizing business transformation. Their ability to replicate physical assets digitally is reshaping industries. Embracing this tech offers immense opportunities for growth and efficiency. Exciting advancements! #digitaltwins #futureofbusiness
?? AI Agents are changing everything - buy my book and find out how! Product Strategist, Data Strategist , Author: Agents Unleashed and The Data Mindset Playbook
1 周Brilliant- this is where it’s going- convergence of all the data analytics, process mining, RPA - creating high enough fidelity that becomes the substrate for agentic business models.