MLOps Challenges in Industry 4.0
Leonhard Faubel, Klaus Schmid, Holger Eichelberger
Abstract
Abstract An important part of the Industry 4.0 vision is the use of machine learning (ML) techniques to create novel capabilities and flexibility in industrial production processes. Currently, there is a strong emphasis on MLOps as an enabling collection of practices, techniques, and tools to integrate ML into industrial practice. However, while MLOps is often discussed in the context of pure software systems, Industry 4.0 systems received much less attention. So far, there is only little research focusing on MLOps for Industry 4.0. In this paper, we discuss whether MLOps in Industry 4.0 leads to significantly different challenges compared to typical Internet systems. We provide an initial analysis of MLOps approaches and identify both context-independent MLOps challenges (general challenges) as well as challenges particular to Industry 4.0 (specific challenges) and conclude that MLOps works very similarly in Industry 4.0 systems to pure software systems. This indicates that existing tools and approaches are also mostly suited for the Industry 4.0 context.