How an Industrial DataOps Solution Improves OEE With a Time Series Database
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An industrial dataOps solution using a time series database can improve overall equipment effectiveness (OEE) in three key ways: 1. It stores industrial time series data with important context like descriptions, locations, and measurement units that raw industrial data lacks. 2. It standardizes and normalizes inconsistent data points across devices to make the data usable outside of process controls. 3. HighByte Intelligence Hub is presented as an example solution that can collect, standardize, and publish industrial data in real-time to enable analytics and business improvements.
How an Industrial DataOps Solution Improves OEE With a Time Series Database
- 1. How an Industrial DataOps Solution Improves OEEWith aTime Series Database Aron Semle, HighByte CTO
- 2. Agenda HighByte’s approach to providing context to industrial data Intro to HighByte Intelligence Hub 01 Storing time series data with context 02 Enabling OEE 03 How to use Intelligence Hub and InfluxDB to store time series data with context How to use Fluxlang to quickly enable OEE (overall equipment effectiveness) applications 2
- 3. 3 We are on amission toprovide manufacturers with the critical datainfrastructure needed toachieve Industrial Transformation. Founded in August 2018 Headquartered inPortland, Maine
- 4. Manufacturing’sTechnology Landscape Has Changed Industrial data architectures have become exponentially more complex 4
- 5. 5 Designed andorganizedfor process controls Represents data points andstructures ofnative devices High number ofdevices anddata points Inconsistent data points across like devices Lacks standarddefinitions Units and units ofmeasure differ No context (descriptions, location, ranges, etc.) Requires correlation across machine, process, product Down sampling, filtering, andsummarizing Raw Industrial Data is Unusable Controls data tags lack context and uniformity
- 6. 6 Data Challenges areThreatening Industry 4.0 Success The existing data infrastructure does not support scale and broad adoption Business Problems ITsystemsusingindustrialdataarenotscaling scaling Infrastructureisnotresilient Securityisunknown Analyticsarenottrusted Businessimprovementsarenotachieved achieved Industry4.0hasdramaticallyincreasedthenumberofusers andsystemsthatwantaccesstoindustrialdata. Controlsdatatagslack contextanduniformity.Thedataisnot correlatedforuse outsideofprocesscontrol. Writingand maintainingcustomintegrationcode, preparing data,andredundantlymodelingdatain eachend application istime-consuming.
- 7. Data modeling andmanagement abstraction layer Standardizeandcontextualizeinformationmodels Manageinformationflows Designed for OT information accessibility Edge-native,on-premises Light-weight Web-based Systemagnostic Codelessinterface Flexible,sustainable,maintainable 7 Introducing HighByte Intelligence Hub The Industrial DataOps solution that streamlines your data integrations
- 8. 8 Built for Industrial Data Real-timedatacollectionandpublication OPCdatastandardization,normalization,and documentation DirectAPIsupport Integrationby target Built-inOPCUAandMQTTsecurity Designed for OT Platformandsystemagnostic Easilyembedded Deployedon-premises,nearindustrialdatasources Light-weight Code-freeconfiguration Ready toScale 10,000+dataflowssupportedwithnobuilt-inproduct limitations OPCUAaddressspacebrowsing Reusablemodels Fasttodeploy,easytomaintain Why HighByte Intelligence Hub Designed for OT to unlock the value of industrial data for the enterprise
- 9. 9 Join the trialprogram: highbyte.com/try-and-buy Contactsales@highbyte.com to request avirtual meeting andproduct demonstration Identify a pilotproject andgetstarted Next Steps Try the software for free in your unique environment Aron Semle Chief Technology Officer aron.semle@highbyte.com
- 10. We look forward to bringing together our community of developers to learn, interact and share tips and use cases. 10-11 May 2021 Hands-On Flux Training 18-19 May 2021 Virtual Experience www.influxdays.com/emea-2021-virtual-experience/