Pervasive Digital Twin for PI-Containers: A New Packing Problem.

Patrick Charpentier,Nicolas Krommenacker,Frédéric Chaxel,Vincent Bombardier,Fabian Seguel

doi:10.3390/s21237999

Abstract

The idea defended in this paper consists in finding, at any time and everywhere, the arrangement of containers within a composite container. The digital image of the real arrangement obtained defines its digital twin. This image evolves at the same time as its real twin. It can be used throughout the logistics chain during loading/unloading phases in hubs, to check the completeness of a load, to find the particular position of a container, etc. This digital twin is obtained through the collection of neighborhood information from the sensor nodes embedded on each container. This embedded solution allows accessibility to this information everywhere. This proximity information and the instrumentation of the containers define new types of constraints and a new version of a packing problem. We propose here a model integrating them. This model is implemented and tested on different test cases, and numerical results are provided. These show that, under certain conditions that will be presented, it is possible to obtain the digital twin of the real arrangement.

Highlights

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
The problem addressed in this paper consists in establishing a 3D model of a real composite container in which various parallelepipedic items have been arranged in the physical world
Different coverage radius has been tested over a range from 0.1 to 5.4, with a spatial sampling of 0.1

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The pervasive digital twin of PI-container, that means available anywhere and at anytime, is a potential solution to this synchronization problem In this context, the virtualization of containers necessarily involves a step to collect data. The different nodes of this network can communicate within a certain coverage radius (adjustable parameter of each node by adjusting the radio transmission power) and are able to generate a list of their neighbors (nodes present inside the coverage radius). This information makes it possible to establish a global neighborhood graph (or proximity graph) between all the containers.

Objectives

Results

Discussion

Conclusion