AI and MLOps in MRO and SCM - Implementing AI and MLOps into RCM for MRO
This paper outlines the process of integrating AI and MLOps into Reliability Centered Maintenance (RCM) for MRO. It details steps from data collection to monitoring, emphasizes data quality and domain expertise, and highlights the benefits of this integration.
Integri, LLC specializes in integrating AI and MLOps into Reliability Centered Maintenance (RCM) for Maintenance, Repair, and Overhaul (MRO), particularly in Aerospace and Defense. This involves a systematic approach:
Data Collection and Preparation: Identifying sources, cleaning data, and creating a centralized repository.
RCM Analysis and Modeling: Analyzing failure modes and developing ML models to predict failures and optimize maintenance.
MLOps Infrastructure Setup: Establishing pipelines for model deployment and monitoring.
Model Deployment and Integration: Integrating AI predictions into decision-making.
Continuous Monitoring and Refinement: Tracking performance and adapting models.
Key considerations include data quality, domain expertise, change management, ethics, and security. Benefits include improved reliability, optimized maintenance, and reduced costs. Integri advocates for modernizing MRO with AI, MLOps, and cloud solutions, emphasizing data-driven decisions and integrated systems. Our expertise includes AI, cloud engineering, and cybersecurity, and we work with industry partners to provide custom solutions.
https://www.integrillc.com/s/Implementing-AI-and-MLOps-into-RCM-for-MRO_03102025.pdf
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