Intelligence & National Security Forum May 11, 2018

Transcription

1 Intelligence & National Security Forum May 11, 2018 This presentation is unclassified in its entirety

2 PI Integrators An Overview Dr. Rajesh Gomatam, Sr. Systems Engineer May 11, 2018

3 PI System Data is Used Across the Enterprise to Achieve Business Impacting Change Safety & Security Energy Utilization Process Efficiency Asset Health Quality Regulatory Performance Operators Craftsmen Supervisors Process Engineers Production Superintendents CoE Experts Location Managers Regional/Global Ops Enterprise Leadership

4 Utilizing PI System Data PI Vision Unified visualization infrastructure, your window into operational intelligence PI Integrators Blend operational data with business data for complex analyses

5 Modern Visualization for the Modern PI System Authoring Monitoring Manual Entry Ad Hoc Analysis Time Series Assets Events Analytics Notifications

6 Utilizing PI System Data PI Integrators Blend operational data with business data for complex analyses

7 Complexity C o p y r i g h t O S I s o f t, L L C Problem Complexity Drives the Need for Integrators Disparate assets or interacting one-by-one Monitoring Real-time visibility Process Optimization Real-time & historical view across any plant asset Interacting with common assets as a fleet Benchmarking Fleet-wide performance comparison System Optimization Large scale multi-variate analysis HMI PI ProcessBook PI V i s i o n PI Datalink BI App (i.e. Tableau, Spotfire, Lumira) PI Integrator for Business Analytics PI Integrator for S AP HANA Machine Learning (Azure ML, R) PI Integrator for Business Analytics PI Integrator for S AP HANA

8 Data Integration can Address Big Questions Mining Oil & Gas Wind Power Pharmaceuticals Transmission & Dist. What material is being hauled? Was it raining? Were there holes in the road? What is the grade of the hill? Was there scheduled downtime? Are there different driving behaviors? What is the status? Which well was being drilled? What angle was the drill bit? Is production related to drill conditions? Was wind gusty or steady? Was the maintenance planned? How long does this issue usually take to fix? What product is being made? When is the equipment empty? Where was the instrument when I took that measurement? How are renewables impacting equipment? Was there a voltage violation? What are the changes in weather?

9 Turbine 2 Turbine 1 Data Alignment Speed Torque Bearing Temp Oil Temp Manufacturer Last Service Different Archive Start Times Vestas June 20, 2013 Speed Additional Measure Torque Bearing Temp Bad Sensor Oil Temp Wear Factor Manufacturer Last Service Date Time Siemens February 5, 2015 Comm Failure Spike / Out of Range Uneven Spacing

10 Data Integration Projects are Challenging Time Expense Risk Data Prep & Cleaning Analysis Warning: Currently, data analysts spend 50-80% of their time merely collecting and preparing data 1 Warning: data integration often requires ongoing upkeep Warning: If why? for the project is not clearly communicated, business barriers will delay and risk the project 1

11 UC o Sp y Er i Rg h St 2 C0 1 O6 O NS I Fs o Ef t R, L EL C N E Prepare Your Data Model Temperature Weather Wind Speed Heat Index Cooling Degree Days Date & Time Context stored in PI System Month Day Hour Shift Off-Peak Partial Peak Peak Status Peak Show me the total energy cost 11 Time-series data stored in PI System

12 UC o Sp y Er i Rg h St 2 C0 1 O6 O NS I Fs o Ef t R, L EL C N E Prepare Your Data Model Temperature Weather Wind Speed Heat Index Cooling Degree Days Date & Time Context stored in PI System Month Day Hour Shift Off-Peak Partial Peak Peak Status Peak Show me the total energy cost For the first shift 12 Time-series data stored in PI System

13 UC o Sp y Er i Rg h St 2 C0 1 O6 O NS I Fs o Ef t R, L EL C N E Prepare Your Data Model Temperature Weather Wind Speed Heat Index Cooling Degree Days Date & Time Context stored in PI System Month Day Hour Shift Off-Peak Partial Peak Peak Status Peak Show me the total energy cost For the first shift During Peak Status 13 Time-series data stored in PI System

14 Prepare and Deliver Process Data CLEANSE to any Visualization Tool or Analysis database on the ODBC standard PULL AUGMENT SHAPE HARMONY TRANSMIT PUSH

15 Advanced Integrations: Supported Systems Visual Analytics Data Warehouse / Data Lake Streaming Analytics May 2018 IoT Hub Machine Learning Stream Analytics

16 Bridge IT and OT with a Process Data Warehouse

17 Operational Reporting & Analysis Architecture Visualization & Analytics Data Preparation and Integration Layer System of Record Tableau SAS Spotfire MSFT BI All BI tools that support ODBC PI Integrator for Business Analytics Business Intelligence Edition PI Server I want to analyze operations data stored in the PI System using modern BI tools

18 Enterprise Data Warehouse Architecture Common Operating Picture Visualization & Analytics Enterprise Data Warehouse / Data Mart / Data Lake Data Preparation and Integration Layer Tableau PI Integrator for Business Analytics Spotfire SAS Oracle DW, SQL Server, Teradata MSFT BI Custom Applications Hadoop Custom or 3 rd Party Data Management and ETL I need to fit operational data into my existing company IT information architecture System of Record PI Server CRM ERP CBM EAM

19 Oil Well Drilling - Example Optimize Well Drilling Times Operate Drilling Rigs efficiently (ROP) Avoid damaging events and costly maintenance

20 Drilling Optimization

21 Power BI

22 Oil and Gas Drilling and production comparisons Information Distribution Mining Route optimization Energy Reduction 300 haul trucks Renewables Energy Production 7 wind farms Outlier Analysis PI Integrator for Business Analytics 2015 usage today IT/ OT Integration Business Intelligence and Reporting Data Warehouse Integration Broad Platform Support Life Sciences Reactor Comparison Process Scale Up 1L, 3L, 10L, 1kL, 10kL Food and Beverage Utility Usage Process Analytics

23 Transform data PI Server(s) PI Integrator for Business Analytics: Data Warehouse Cloud On Premise

24 Customer Case Study

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26 Predictive Maintenance Barrick Gold The RCIP engagement provided the site with access to vehicle data like never before. The site had been totally dependent on the vendor for information but now has open access to data. Barrick is on the cutting edge of maintenance with predictive models that detect engine failures before they occur. David Luque, Control Engineer CHALLENGES Maintain large fleet of mining trucks with limited access to data Unplanned downtime creates a huge cost and ripple effect through operations The site was completely dependent on a vendor to provide truck information SOLUTION The RCIP team setup connectivity to VIMS data, developed models, and created analytics to detect 60+ different events Published Asset and Event data into the cloud, integrated with ERP, Dispatch, and Maintenance data Barrick and McKinsey developed Power BI reports and predictive models RESULTS Power BI reports providing detailed information on fleet performance, maintenance, and reliability Dashboards were included in Barrick s newly-developed asset health software application Predictive models now detect probability of engine component failure in the next 5 days

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28 Bridge IT and OT with a Esri ArcGIS for GeoSpatial Situational Awareness

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30 PJM Situational Awareness Shortens Time to Action With The PI System And DIMA at PJM Challenge Solution Results Combine weather, Provide its control asset, raw resource center dispatchers with availability and adequate situational transmission lines awareness to be able animated by SCADA to make the most data for quicker intelligent decisions. analysis. Geospatial Data Analytics improves situational awareness. Dispatch Operators have a single visualization tool that shortens time to action

31 PJM Multiple data source to manage the grid Real time PI System display is not geographically correct GIS display has assets but is static Live weather feed does not have assets or operational data

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33 DTE Energy Shortens Customer Outages With Wireless Sensors and Maps Challenge Solution Results Determining where to send crews during outages to minimize patrol times and reduce duration of outages. Install wireless sensors (5k) to help pinpoint fault locations. Leverage OSIsoft technology to collect and share this data across the enterprise. Expected to eliminate 6.6M customer outage minutes annually. Avoided spending $25M for equivalent SCADA solution.

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35 SoCal Gas: Real-Time GIS Gas and Weather Conditions for Public Consumption With The PI System and Esri ArcGIS Challenge Wanted the ability for the public to monitor gas level and weather information Source: KPHO/KTVK) Solution SCADA data is published to ArcGIS Online and SoCal gas developed a custom app for public to utilize to ascertain the current gas levels in there, along with weather and humidity. Also, its integrated with the ability to review the levels for the last 24 hrs Results Real-Time Geographical Operational Intelligence enables public to monitor current gas levels in their area, along with weather and humidity data. Also, has the ability to view the data for the last 24 hours.

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38 Power Factors projects 5-10x lower cost of locating operational performance issues With The PI System ArcGIS and Aerovironment Challenge Solution Results OpEx margins are very Dones employed to slim and labor costs Combination of Operational Data, map & build asset are very high in solar Geospatial and Aerial Thermography will model, then scan for industry. Decrease prove to be transformative for the cause of low cost of detection & operational industry. Forecast 50-10x reduction in location of small flaws performance labor costs. in a very large area

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40 Saved over $1MM through leak remediation White House Utility District Challenge Solution Results Locate and repair leaks to effectively reduce loss. Reduce the effort to gather data and calculate GPM at stake in each DMA zone Collect / store SCADA &IoT meter data in realtime. Calculate KPIs in realtime Automatically publish shape data to ArcGIS Saved over $900K in non-revenue water Saved over $200K through PI System integration with all time-series data sources Recovered $30K-40K per year in workflow optimization

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44 Questions Please wait for the microphone before asking your questions Please don t forget to Complete the Post Event Survey State your name & organization

45 Contact Information Rajesh Gomatam Ph.D. Sr. Systems Engineer OSIsoft LLC

46 Thank You REGIONAL 2018 Intelligence PROGRAM & National NAME Security HERE Forum 46