Embedding the MLOps Lifecycle into OT Reference Models

2025-10-23

AI Summary

Deep integration of MLOps with industrial Operational Technology (OT) systems remains challenging due to conceptual and architectural misalignment between AI/ML engineering practices and established OT frameworks. Method: This paper proposes a systematic embedding methodology that, for the first time, maps core MLOps lifecycle components onto mainstream OT reference models—specifically RAMI 4.0 and ISA-95—establishing a layered, use-case-driven adaptation pathway that transcends the limitations of conventional “direct transplantation” approaches. The methodology is validated through architecture-level mapping and empirical evaluation in real-world industrial settings. Contribution/Results: Results demonstrate RAMI 4.0’s strong compatibility with MLOps integration, yielding a reusable, scalable, and standardized implementation framework. This work bridges a critical theoretical and practical gap in structured MLOps deployment within OT environments, providing a cross-domain benchmark pathway and engineering foundation for industrial AI operations.

Technology Category

• Machine Learning: Scalability of ML Systems
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

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.

Problem

• Integrating MLOps practices with Operational Technology systems
• Analyzing obstacles in combining MLOps with OT environments
• Mapping MLOps lifecycle components to industrial reference models

Innovation

• Embedding MLOps into OT reference models
• Mapping MLOps lifecycle to RAMI 4.0 framework
• Adapting MLOps practices for OT environments