Efficient Rollout of a Dynamic Optimization Algorithm

Philipp Neuhauser, Rudolf Cihal, Stefan Wagner, Harald Flößholzer

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

Abstract

A successful deployment process of a complex software solution, such as optimization algorithms in a dynamic production environment is an extremely complicated and time-consuming task. Over this, the acceptance by those employees where the software solution is to be used later should not be underestimated; it is essential to involve them in the entire development process, as they can be game changers. This paper summarizes some best practices and lessons learned about the full integration of an optimization algorithm in the dynamic steelmaking environment of voestalpine Stahl GmbH. The focus is on the development of a practical test strategy and ultimately a generally valid rollout concept for an arbitrary complex software system for every conceivable industry. Over that, emerging gaps between theory and practice are highlighted, an attempt is made to justify their cause, and, as a result, possible solutions to tackle those challenges are presented.
Translated title of the contributionEffiziente Ausrollung eines dynamischen Optimierungsalgorithmus
Original languageEnglish
Title of host publication5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023
PublisherElsevier
Number of pages10
Publication statusPublished - 2023
Event5th International Conference on
Industry 4.0 and Smart Manufacturing
- University Institute of Lisbon, Lissabon, Portugal
Duration: 22 Nov 202324 Nov 2023
https://www.msc-les.org/ism2023/

Publication series

NameProcedia Computer Science

Conference

Conference5th International Conference on
Industry 4.0 and Smart Manufacturing
Abbreviated titleISM 2023
Country/TerritoryPortugal
CityLissabon
Period22.11.202324.11.2023
Internet address

Keywords

  • Software Rollout Strategy
  • Efficient Software Deployment
  • Dynamic Optimization Algorithm
  • Innovation Gap

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