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Area of Science:

  • Logistics and Supply Chain Management
  • Operations Research
  • Computer Science/Digital Twins

Background:

  • Current logistics systems lack real-time visibility into container arrangements within composite containers.
  • Manual tracking is inefficient and prone to errors, impacting supply chain operations.
  • The need for dynamic, accessible information about container placement is critical for efficient logistics.

Purpose of the Study:

  • To develop a method for creating a real-time digital twin of container arrangements.
  • To integrate container proximity data into a novel packing problem model.
  • To validate the feasibility of obtaining a digital twin for dynamic container management.

Main Methods:

  • Utilizing sensor nodes embedded in containers to collect neighborhood information.
  • Developing a new mathematical model that incorporates proximity constraints and container instrumentation.
  • Implementing and testing the proposed model on various test cases with numerical analysis.

Main Results:

  • Demonstrated the ability to generate a digital twin representing the real-time arrangement of containers.
  • Numerical results indicate successful reconstruction of container positions under specific conditions.
  • The digital twin provides continuous, accessible information throughout the logistics chain.

Conclusions:

  • The proposed digital twin approach offers a viable solution for real-time container arrangement monitoring.
  • This method enhances logistics efficiency by enabling accurate load verification and container location.
  • Further research will focus on refining the model and exploring its application in complex logistical scenarios.