Industrial internet of things-driven storage location assignment and order picking in a resource synchronization and sharing-based robotic mobile fulfillment system

K. L. Keung, C. K.M. Lee (Corresponding Author), P. Ji

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In this paper, we intend to address the value creation of utilizing the Industrial Internet of Things (IIoT)-driven resource synchronization and sharing-based robotic mobile fulfillment system (RMFS) to enhance the overall operational effectiveness and efficiencies during information transfer and synchronization of resources. With the advent of IIoT, a graph theory-based heuristic under the multi-deep RMFS is used for computing the shortest path. A-star, Dijkstra, and genetic heuristic algorithms are applied for comparison. A simulation with a consideration of the different types of collisions is conducted for different algorithms. By providing a new three-tier IIoT architecture which includes the suppliers, RMFS, and the disposal center, a model is developed with different storage location assignment rules and strategies under the particular parties to minimize the operation costs. IIoT enables resource synchronization and information sharing, and the path will be generated under different order scenarios with different algorithms. The results show that different storage assignment rules and strategies may lead to 30% cost differences compared to the company's current practice with random storage.

Original languageEnglish
Article number101540
JournalAdvanced Engineering Informatics
Volume52
DOIs
Publication statusPublished - Apr 2022

Keywords

  • Industrial internet of things
  • Internet of things
  • Robotic mobile fulfillment system
  • Storage location assignment
  • Warehouse management

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence

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