Real-Time Digital Twin & Artificial Intelligence (AI)

Maintain resilient and self-sustainable structural systems by improving efficiency, reducing downtime, and optimizing performance.

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Our AI technologies include

Reduce-Order Models (ROMs)
Machine Learning
Neural Networks
Artificial Intelligence

About Real-time Digital twin & AI

A digital twin serves as a virtual embodiment of a physical process or product, functioning as a tool for comprehending the underlying physical entity and forecasting its performance attributes. Through an amalgamation of multi physics simulation, data analytics, and machine learning prowess, digital twins unveil the consequences of diverse scenarios, environmental circumstances, and other factors. Venturing even further, a real time digital twin integrates the potency of high fidelity numerical models extracted from digital twins (e g live data gleaned from sensors). This synergy enables the detection and analysis of impairments or modifications in the structure in real time, prophecies regarding future performance, and the early identification of potential breakdowns. This capability empowers continuous oversight of a product, addressing issues in the here and now.

The pinnacle of this technology currently lies in the Reduced Order Model (ROM) technique ROMs represent a streamlined variant of a high fidelity, stationary, or dynamic numerical model, conserving crucial behaviors, paramount influences, and fidelity, while circumventing the need for extensive computational resources. The objective is to drastically curtail computational costs, enabling the calculation of physical parameters within exceptionally confined timeframes, potentially even instantaneously.

Benefits of Real-time Digital Twins

1

Make faster, informed, and more accurate decisions.

2

Detect potential issues before they occur.

3

Optimize processes and reduce downtime.

4

Provide a personalized and responsive customer experience.

5

Optimize resource utilization and reduce waste.

It’s important to note that adopting digital twins requires considerable investment, collaboration, and sustained commitment from all business functions affected. From revising criteria, workflows and feedback loops to tackling data-sharing, security and governance, leaders need to actively ensure that they’re making the best use of the technology. However, if done well, the long-term benefits are invaluable.

Industry applications of Real-time Digital Twins & AI

Manufacturing

Simulate and optimize the production process, allowing manufacturers to improve efficiency, reduce costs, and increase quality.

Smart Cities

Monitor and manage the infrastructure and services in a city, including transportation systems, energy networks, and water supply.

Healthcare

Monitor the health of patients, track the efficacy of treatments, and support the development of personalized medicine.

Automotive

Optimize the design, testing, and manufacturing of vehicles, and to monitor the performance of vehicles in real-world conditions.

Civil Infrastructure

Simulation of crashworthiness, vibration analysis, and noise, vibration, and harshness (NVH) analysis.

Aerospace

Monitor the health of aircraft, including the wings, fuselage, and other critical components, to ensure safe operation and to identify potential problems before they become critical.