Publikation - Einzelansicht

@article {42069,
author={Leonhard Faubel and Klaus Schmid and Holger Eichelberger},
title={MLOps Challenges in Industry 4.0},
journal={SN Computer Science},
year={2023},
month={August},
pages={11},
abstract={<p><p>An important part of the Industry 4.0 vision is the use of machine learning (ML) techniques to create novel capabilitiesand flexibility in industrial production processes. Currently, there is a strong emphasis on MLOps as an enabling collectionof practices, techniques, and tools to integrate ML into industrial practice. However, while MLOps is often discussed inthe context of pure software systems, Industry 4.0 systems received much less attention. So far, there is only little researchfocusing on MLOps for Industry 4.0. In this paper, we discuss whether MLOps in Industry 4.0 leads to significantly dif-ferent challenges compared to typical Internet systems. We provide an initial analysis of MLOps approaches and identifyboth context-independent MLOps challenges (general challenges) as well as challenges particular to Industry 4.0 (specificchallenges) and conclude that MLOps works very similarly in Industry 4.0 systems to pure software systems. This indicatesthat existing tools and approaches are also mostly suited for the Industry 4.0 context.</p></p>}
}