AI and MLOps in MRO and SCM - Advanced AI Techniques and Challenges in Demand Forecasting
This paper focuses on advanced AI techniques in demand forecasting, outlining data integration, feature engineering, model selection, and deployment. It discusses challenges like data quality and dynamic market conditions while highlighting best practices for effective implementation.
Integri, LLC specializes in using advanced AI and MLOps to improve demand forecasting, particularly for high-stakes sectors like Aerospace and Defense. We focus on:
Data integration and preparation, efficiently handling diverse data.
Feature engineering to identify relevant patterns.
Model selection and training, using various AI models.
Model deployment and monitoring, ensuring continuous performance.
Advanced AI techniques employed include deep learning, reinforcement learning, generative adversarial networks (GANs), and ensemble methods. Integri addresses challenges like data quality, market dynamics, and supply chain disruptions. Our best practices include a data-driven approach and explainable AI. We advocate for modernizing DoD MRO with AI and integrated systems for data-driven decisions. Integri's expertise covers AI, cloud engineering, and cybersecurity.
#Integri #DoD #MRO #Maintenance #MLOps #AI #RCM #ReliabilityCenteredMaintenance #PredictiveMaintenance #DataDrivenDecisions #DigitalTransformation #AerospaceAndDefense #OperationalEfficiency #SparePartsForecasting #ModelDeployment #RealTimePredictions #TaskPrioritization #ResourceAllocation #InteractiveDashboards #PrescriptiveAnalytics #CloudBasedSolutions #IntegratedSystems #DLAsupport #NAVSUPsupport #3PL #SupplyChainManagement #SupplyChainVisibility #RiskManagement #LogisticsOptimization #DemandForecasting #InventoryManagement
