Method, Apparatus, and Procedures for Multi-Layered Digital Twin Construction and Adaptation in Complex Systems

A novel method, apparatus, and procedure for creating scalable and adaptive models for complex systems through multi-layered digital twins



With unprecedented evolution of communication and computing technologies, modern industrial systems are becoming increasingly complex due to their growing scale, involvement of heterogeneous machines, and frequent interactions among connected objects across the Internet. Such complex systems are encountered in different industry sectors such as telecommunications, industrial Internet of Things, intelligent transportation, smart grids, and environment monitoring. Operating these complex systems effectively in dynamic conditions poses huge challenges, mainly due to the overwhelming complexity in achieving real-time collaboration and coordination among the geographically distributed connected objects. Effectively modelling the spatial-temporal dynamics of complex system in real-time with reduced complexity become essential in improving the overall operation of complex systems in varying operating environments.

Technology Overview

Western University researchers have developed a novel method, apparatus, and procedure for constructing scalable and adaptive models of complex systems through multi-layered digital twins.

With the invented multi-layered digital twin modeling approach and operational goal-driven problem identification method, the challenging problem of the complex system operation can be decomposed as a set of concurrent and solvable sub-problems, leading to the significantly reduced overall complexity and enhanced operational effectiveness.

Specifically, the invention streamlines adaptive system-wide data collection, processing, and digital twin by rapidly evaluating the real-time system situation according to the system operational goals, which can support objective-driven digital twin formation and problem-solving. Moreover, the methodology incorporates a decomposition strategy that breaks down the complex system into manageable subsystems based on operational goals, functionality, and interdependencies. This results in a multi-layered digital twin architecture that allows for focused modeling and targeted problem-solving for problematic subsystems, with prioritized resource allocation.


The main benefits of the invention on multi-layered digital twin construction include the dramatically reduced complexity associated with complex system operation under fast-changing conditions, while substantially enhancing the system operational effectiveness.

With the innovative approach, we can achieve the following:

  • Efficient evaluation of real-time situations of complex systems.
  • Quick identification of critical problems within the complex systems and response to the system situations in real-time.
  • Accurate generation of actionable decisions to promptly address the corresponding issues.
  • Overall improved system performance and reduced resource consumption.


The invention offers significant potential for a variety of complex systems grappling with inherent operational and management challenges. We envision our innovative method playing an increasingly pivotal role in the following complex system management.

  • Communication infrastructure management: This method optimizes communication infrastructure management with enhanced efficiency and accuracy. By unleashing the power of fast system evaluation and problem identification, this invention can better support resource allocation, user association, and traffic engineering.
  • Advanced manufacturing: This method revolutionizes advanced manufacturing by implementing adaptive multi-layered digital twin modeling and operational goal-driven problem solving. Real-time evaluation, rapid issue identification, and accurate decision-making can facilitate reliable and cost-effective manufacturing outcomes across diverse sectors.
  • Supply chain management/logistics: The adaptive multi-layered digital twin modeling and goal-driven problem identification method optimizes supply chain management and logistics. Relevant organizations can enhance their transportation scheduling, warehousing, inventory management, and order fulfillment.
  • Smart grids: The proposed method can enhance the reliability and efficiency of smart grid operations. By evaluating the real-time situation of the power grid systems, operators can quickly identify critical issues and make accurate decisions to address them promptly.
  • Intelligent transportation: The new method can revolutionize transportation by enhancing mobility, reducing congestion, and maximizing efficiency while promoting sustainability. Problematic subsystems, like congested areas and crossroads, can be efficiently identified and managed by real-time system evaluation.


  • Licensing
  • Collaborative research


  • Development partner
  • Commercial partner
  • Licensing
  • University spin out
  • Seeking investment

Contact Us and Learn More

Souzan Armstrong

Executive Director


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