Digital replica design involves creating digital equivalents of real objects, processes, or systems. These replicas are created using specialised software and data collected from sensors and monitoring systems to accurately replicate the structure, dynamics, and behaviour of the real object. Digital replicas are used to simulate, analyse and optimise processes and to assess the performance and condition of objects.
Designing Digital Replicas of Physical Objects, Processes, and Systems
Type of technology
Description of the technology
Basic elements
- CAD models: Digital representations of the geometry and structure of objects.
- Simulation systems: Tools for reproducing the dynamic behaviour of objects.
- IoT data integration: Sensor data used to update replicas in real time.
- Analytics software: Performance and efficiency analysis tools.
- Visualisation platforms: Environments for interactive viewing and editing of replicas.
Industry usage
- Aviation industry: Design of replica aircraft and engines.
- Construction: Simulation of building structure behaviour.
- Automotive industry: Creation of digital copies of vehicles to test new components.
- Urban infrastructure: Monitoring the technical condition of bridges and buildings.
- Energy: Simulation of power grid behaviour.
Importance for the economy
Digital replica design enables optimisation of engineering designs and more effective product life cycle management. Companies can predict failures, simulate various scenarios, and improve production processes. This gives them greater flexibility, reduces operating costs, and minimises the risk of failure or design errors.
Related technologies
Virtual Reality
Interactive visualisation of replicas in a virtual and augmented reality environment.
Mechanism of action
- The process of designing digital replicas begins with gathering data about the real object, such as dimensions, materials, movement dynamics, and other properties. The data is then processed in simulation software to create a digital copy. The model is updated based on sensor data, which enables simulation of the object’s behaviour under different operating conditions and analysis of its performance.
Advantages
- Project optimisation: Better design and optimisation of new products.
- Predicting behaviour: Simulation of the behaviour of objects under different conditions.
- Cost reduction: Reduction of costs of physical testing.
- Reduction of development time: Faster implementation of new technological solutions.
- Life cycle management: Monitoring and optimisation of the entire product life cycle.
Disadvantages
- Data quality issues: Incorrect input can lead to inaccurate replicas.
- High implementation costs: Significant software and hardware acquisition costs.
- Complexity of models: Difficulties in creating and managing complex replicas.
- Data security: Risk of theft of data on critical systems.
- Lack of standardisation: Difficulties in integrating replicas with other systems.
Implementation of the technology
Required resources
- CAD models: Tools for designing geometric models of objects.
- Simulation software: Tools for dynamic simulation of object behaviour.
- Computing servers: High-performance servers for Big Data processing.
- Simulation specialists: Experts in creating digital copies of real objects.
- Integration systems: Platforms for combining data from different sources.
Required competences
- Systems engineering: Design and optimisation of technical systems.
- Computer simulation: Creating simulation models.
- Programming: Ability to implement simulation algorithms.
- Project management: Organisation and coordination of implementation projects.
- Cybersecurity: Protecting digital replica data from attacks.
Environmental aspects
- Energy consumption: High energy demand of computing systems.
- Waste generated: Problems with recycling decommissioned equipment.
- Emissions of pollutants: Indirect emissions from electricity consumption.
- Raw material consumption: High demand for electronic components.
- Recycling: Problems with recovering materials from complex computing devices.
Legal conditions
- Data protection: Regulations for the processing of sensitive data.
- Engineering design regulations: Industry standards and certifications.
- Intellectual property: Patents for methods of creating digital replicas.
- Data security: Regulations for the protection of data from unauthorised access.
- Export regulations: Export control of simulation technologies.