Embedding the MLOps Lifecycle into OT Reference Models
Abstract
Machine Learning Operations (MLOps) practices are increas- ingly adopted in industrial settings, yet their integration with Opera- tional Technology (OT) systems presents significant challenges. This pa- per analyzes the fundamental obstacles in combining MLOps with OT en- vironments and proposes a systematic approach to embed MLOps prac- tices into established OT reference models. We evaluate the suitability of the Reference Architectural Model for Industry 4.0 (RAMI 4.0) and the International Society of Automation Standard 95 (ISA-95) for MLOps integration and present a detailed mapping of MLOps lifecycle compo- nents to RAMI 4.0 exemplified by a real-world use case. Our findings demonstrate that while standard MLOps practices cannot be directly transplanted to OT environments, structured adaptation using existing reference models can provide a pathway for successful integration.
Cite
@article{arxiv.2510.20590,
title = {Embedding the MLOps Lifecycle into OT Reference Models},
author = {Simon Schindler and Christoph Binder and Lukas Lürzer and Stefan Huber},
journal= {arXiv preprint arXiv:2510.20590},
year = {2025}
}