2-7-Trevor Bloch-IoTDB 在工业大数据机器学习中的应用 — 高性能集群部署实践.pdf

1、IoTDB for Industrial Big Data Machine Learning High Performance Cluster DeploymentSpeaker：Trevor BlochCONTENTSIntroduction to VROC01VROCs Product Offerings02VROCs IoTDB Use Case03VROCs application to various industries04Customer success using this technology0501Introduction to VROCSolving data and A

2、I adoption challengesVROC transforms data collection and utilization for asset and process intensive industries,resolving adoption challenges.44%of data goes uncaptured56%of data iscaptured through operations43%remains largely unused68%of data goes unleveragedSource:The Seagate Rethink Data Survey.I

3、DC,2020 Fast deployment,quicker ROIDesigned for rapid deployment to enable our customers to start seeing benefits immediately Scalability and FlexibilityBuilt to scale as our customers operations grow.Allowing our customers to customize features and integrations to fit their specific needs.Cost effe

4、ctiveDesigned to be affordable without compromising on quality.VROC empowers asset operators and maintainersProcess IndustriesOil&GasMiningPrimary IndustriesDiscrete IndustriesRenewablesUtilitiesMaritimeSmart Cities/Smart FacilitiesBuildingsCities/CouncilsCampusesPredictive Maintenance:Identifies ti

5、me-to-failure of assets and the root cause of failure,enabling optimised maintenance planning.Process Optimisation:Identifies system anomalies and the root causes,enabling redesign of processes to optimise production.Performance&Remote Monitoring:Holistic view of plant equipment with drill-down capa

6、bility to monitor individual sensor contribution to asset performance.Control:systems and equipment anywhere/anytime.Digital Twin:Replicate the entire facility data with raw and calculated values to monitor real-time asset performance against basis of design.Optimizing Oil and Gas OperationsOutcomes