Agile Operational Behavior for the Control-Level Devices in Plug Produce Production Environments

Kirill Dorofeev, Stefan Profanter, Jose Cabral, Pedro Ferreira, Alois Zoitl

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

The ongoing manufacturing systems transformation from mass production towards mass customization requires more flexible engineering solutions than the existing ones. The recently proposed control architectures target, among other plug-and-produce features, a reduction of configuration times. This is relevant for building a new production line as well as for faster reconfiguration when adding new hardware and product variants to an existing manufacturing line. This paper identifies operational requirements for such reconfiguration scenarios and proposes a way to implement them using the concept of a device adapter. The device adapter contains a device description and constantly updates it following the reconfiguration changes happening in a manufacturing system. This allows not only to detect the changes in the hardware, which appear in the production system, using the device discovery mechanisms but also automatically adapt the software. Preliminary tests have been performed on a demonstrator that shows both virtual and physical executions combined in a single system. The proposed solution supports automatic hardware and software reconfiguration on-the-fly without a need to stop and restart the whole production system.
Original languageEnglish
Title of host publication2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Pages49-56
Number of pages8
DOIs
Publication statusPublished - 2019

Publication series

NameProceedings (IEEE International Conference on Emerging Technologies and Factory Automation)
ISSN (Print)1946-0740

Fields of science

  • 202017 Embedded systems
  • 102022 Software development
  • 102025 Distributed systems
  • 102029 Practical computer science
  • 202003 Automation
  • 202041 Computer engineering

JKU Focus areas

  • Digital Transformation

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