Multi-factory production planning using edge computing and IIoT platforms

Deepak Dhungana, Alois Haselböck, Sebastian Meixner, Daniel Schall, Johannes Schmid, Stefan Trabesinger, Stefan Wallner

Research output: Contribution to journalArticlepeer-review

Abstract

An important prerequisite for determining whether a certain product is producible in any given production facility is an accurate assessment of which production lines and/or the machines are able to execute the necessary production steps. Not only the static information about the capabilities of the machines, but also the conditions of machines and tools are significant for this analysis. Because of the deviation of machine capabilities with increasing deterioration and weary of the equipment, it is also necessary to continuously monitor the status of the machine and analyze the machine conditions. In this paper, we present an approach for generating production plans across multiple factories, considering both static information and dynamic data analysis. Edge devices constantly monitor high frequency machine data and report condensed machine states to an Industrial IoT platform (IIoT). A marketplace within the cloud-application MindSphere enables us to integrate the requirements of the products and the capabilities of the production sites. Customers are be able to evaluate these production plans based on duration, energy consumption, CO2 footprint etc.
Original languageEnglish
Article number111083
Pages (from-to)111083
Number of pages1
JournalJournal of Systems and Software
Volume182
DOIs
Publication statusPublished - 16 Sept 2021

Keywords

  • Deterioration
  • Edge computing
  • Energy utilization
  • Manufacture
  • Planning
  • Cloud Manufacturing
  • Condition
  • Edge analytic
  • Factory as a service
  • Industrie 4.0
  • Manufacturing ecosystem
  • Monitoring production
  • Production Planning
  • Production plans
  • Static information
  • Production control
  • Edge analytics
  • Manufacturing ecosystems
  • Cloud manufacturing

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