What is a Digital Twin?

A digital twin is a dynamic, virtual representation of a physical object, system, or process. This digital model is continuously updated with real-time data from its physical counterpart, enabling simulations, monitoring, and analysis to optimize performance and predict potential issues.

Originating from NASA’s need to improve spacecraft simulations, the concept has evolved to encompass various applications across industries, from manufacturing to urban planning.

What are the benefits of a digital twin strategy?

Improve product quality

Before investing in prototyping or physical development, test and validate your design, and your production processes. This new capability accelerates the development of better, more sustainable products by greatly improving risk assessment and ensuring production reliability.

Reduce time-to-market

By simulating and testing products virtually, digital twins significantly cut down the time required for physical prototyping and validation, speeding up the development process.

Target Sustainability

Reduce time waste, material usage, and energy consumption by ensuring optimal development and production processes ahead of time. Avoid unnecessary prototyping costs by continually monitoring real world usage and feeding information back into the innovation and design phases.

What are digital twins used for?

Digital twins provide a comprehensive, real-time view of physical assets. They enable manufacturers to simulate and test different scenarios without disrupting actual operations, leading to improved design, efficiency, and maintenance. For example, in the automotive sector, digital twins enable engineers to accurately predict the performance of novel vehicle models under diverse conditions, thereby reducing the necessity for physical prototypes and expediting the time to market.

Digital twins also help optimize production lines by identifying bottlenecks and inefficiencies. They can simulate the impact of changes in the production process, such as the introduction of new machinery or modifications in workflow, ensuring that these changes lead to desired outcomes.

They also help with predictive maintenance by collecting data from machine sensors. This helps predict problems and schedule repairs quickly, reducing downtime and increasing lifespans.

What's the best way to get started with a digital twin?

Data collection

Gather data from physical assets using sensors, IoT devices, and other data sources. This data includes parameters like temperature, pressure, and operational status.

Model development

Create a virtual model of the asset using digital twin software that accurately reflects its physical counterpart.

Integration and testing

Connect the digital twin to real-time data sources and validate its accuracy by comparing simulation results with actual performance data.

Optimization

Use the digital twin to analyze data, run simulations, and develop strategies for optimizing performance and maintenance.

Examples of digital twin projects

Performance-driven PLM at Koenigsegg

Using the concepts of digital twin and digital continuity, we’re supporting supercar manufacturer, Koenigsegg, as they step into the world of digital manufacturing – becoming more sustainable as they do so.

Digital twins: a strategic enabler for sustainability

Digital twins are gaining recognition and popularity as a solution for digitally representing a product, a building, or even a human being. This is enabling new opportunities to improve performance, operations, productivity, and quality of life.

A digital twin strategy to drive sustainability programs can be profoundly effective, offering significant benefits when planning, implementing, and realizing:

  • Reduced energy consumption
  • Reduced material consumption and the switch to more sustainable materials
  • Workforce activity optimization – travel, server usage, etc.
  • Automation and robotization of hazardous and/or repetitive tasks to improve working conditions and health.

Make an Enquiry