AI and MLOps in MRO and SCM - MLOps in RCM for DoD Three-Level MRO

This paper delves deeper into the application of MLOps in RCM for each level of DoD MRO. It outlines how MLOps can support data collection, predictive modeling, model deployment, process optimization, and decision support, providing specific examples for each level.Integri, LLC uses AI and MLOps to improve operational efficiency and security, especially in Aerospace and Defense. A key application is in Reliability Centered Maintenance (RCM) for the DoD.

MLOps enhances RCM through:

• Data-driven insights: Centralizing, cleaning, and standardizing data.

• Predictive modeling: Predicting failures, optimizing maintenance, and forecasting parts.

• Real-time predictions: Deploying models for real-time recommendations.

• Continuous improvement: Monitoring and retraining models.

• RCM optimization: Prioritizing tasks and allocating resources.

• Decision support: Providing interactive dashboards and recommendations.

Specific applications for the DoD's three-level MRO:

• Organizational level: Predicting component failures and optimizing maintenance.

• Intermediate level: Developing predictive models for overhauls and optimizing spare parts.

• Depot level: Analyzing failure data to improve designs and processes.

By integrating MLOps into RCM, the DoD can improve reliability, reduce costs, and enhance readiness. Integri emphasizes data-driven decisions, modern tech, and integrated systems. Our mission is to deploy cutting-edge AI to improve predictive maintenance and reduce long-term costs.

https://www.integrillc.com/s/MLOps-in-RCM-for-DoD-Three-Level-MRO-03242025.pdf

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