Innovation around the PI System: Paris Water Supply. Copyr i ght 2014 O SIs oft, LLC.

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1 Innovation around the PI System: Paris Water Supply Presented by Mahyar SEPEHR

2 Major Transformation Program (A few initial objectives) Design Next Generation Smart Services Water Traceability Smart Metering Leaks Detection Reduce environmental impact Reduce electricity consumption Reduction CO2 emission ISO

3 Major Transformation Program Allow more data exchange Production Un-compartmentalize Risk Management Distribution Promote transparency To create synergy between processes Allow Real Time Decision-making Reporting Water Quality Continuous improvement strategies Customer Relationship Management Better monitoring capabilities 3

4 When we started the project, we asked ourselves: Who are we? What can we do to enhance our user experience? How can we do it better than anyone else? 4

5 1. Who are we? 5

6 We serve water 3 water treatment plants kilometers of pipeline cubic meters of water pumped daily! 5 million customers 6

7 But who are we really? 7

8 In this conference today We come from different industries We all have different operations, but We all have the same needs! What we all have in common : Data It might come from anywhere in many forms We need to manage it, secure it, store, add context, analyse, monitor the data The key factor is the Volume Our subject is about Big Data - but why Big Data? 8

9 Every day, we process in our workflow: 7 Gigabytes of data 8.4 Million text lines 20 types of sources in real-time! 9

10 Who uses our data? Production Field Engineers Water Engineers Data Scientists IT Department Managers Risk Management Reporting And most importantly: people who consume water Create synergy Customer Relationship Management Distribution Quality 10

11 2. What can we do to enhance our user experience? 11

12 We needed to build something Fast yet flexible Smart yet simple Effective yet intuitive 12

13 To allow Real-time integration of large volumes of data from a variety of sources Actionable Information with bulk calculations across various data sets Real-time decision-making provided at any time and anywhere with mobile and web applications 13

14 3. How can we do it better than anyone else? 14

15 REAL-TIME DECISION MAKING PROPAGATE VISUALIZE ANALYZE CONTEXTUALIZE AGGREGATE Analysis Archive Information Service DataViz WEB API Real Time Big Data Search Interface Management Context GIS Continuous Improvement Data Sources Risk Quality Plant Distribution Customer OpenData 15

16 Monitoring Integration Analysis Delivery 16

17 Monitoring Integration Analysis Integration : custom interfaces to provide high-performing volume data integration from a variety of sources Delivery 17

18 Monitoring Datasource Interface Datastore Integration Analysis Flow1 PI AF SDK Custom Interface Bulk Insertion Bulk Insertion PI AF Server Delivery PI UFL PI Data Archive Flow 2 18

19 Monitoring Integration Analysis Analysis : large-scale calculations to transform data into actionable information Delivery 19

20 Monitoring Analysis Scheduler Integration Analysis Load Data Monitoring & Alerts Delivery Step1 Step2 Step3 Step4 Reporting Interfaces Analysis Engine Calculation steps 20

21 Monitoring Integration Analysis Delivery : relevant information delivered across platforms to allow for real-time decision-making Delivery 21

22 Monitorin g Datastore Interfaces Interactive Applications Integration Analysis PI AF SDK Web Services Delivery PI AF Server RESTful JSON PI Data Archive PI DataLink PI AF Builder Excel 22

23 Monitoring Integration Analysis Delivery Monitoring : Technical and functional supervision Centralized Logging strategies Traceability across process workflows Alerting for all Facilities 23

24 Monitoring Integration Analysis Delivery 24

25 4. How does it all come together? 25

26 Tool for The Monitoring and the Optimization Energy consumption monitoring to reduce costs Key indicators monitored across the water supply chain Correlation between hydraulic configuration and energy consumption to pre-empt issues Baseline for pattern detection 26

27 PI System and Real Time Data Analysis Leak Detection on demand + 7% Detection of Leak between 2012 and 2013 Analyze sensors in real-time Exchange with SQC & Scilab Process the signals to determine the best location of leaks 27

28 New ways are now possible! Access data with simple RESTful API HTML JavaScript! With a full text search, navigate through your data, compare charts 28

29 29

30 GIS an intuitive interface to access multiple data Blending data from a variety of sources while providing better context and readability Bird s eye view across the distribution grid Intuitive! 30

31 Web application with Google Maps Integrate your data into Google Maps 31

32 New ways of Mobility Send your data everywhere 32

33 Data at your fingertips! 34

34 LESSONS from our TRANSFORMATION What has changed? Depth of data inventory What used to be a burden (historical data) is now a valuable asset Users can now make real-time decisions anytime, anywhere 35

35 Mahyar Sepehr Ysance 36

36 Questions Please wait for the microphone before asking your questions State your name & company 37

37 Brought to you by

38 Please don t forget to Complete the online survey for this session eventmobi.com/emeauc14 Share with your friends #UC2014

39 Supervision ZABBIX PI API / PI SDK PI DATALINK Software Architecture 1 ESRI ESB 3 3D PI Data Access DataViz (HTML5/JS) WS REST SharePoint Excel Services PI Datalink Server BigData Solution with the PI System Administration PI System PI SMT Explorer Core PI Data Archive PI AF Builder PI EF Builder PI Asset Framework PI SQC PI SQC 2 Analysis Custom Analysis PI Event Frames PI Asset Based Analytics Data Science Scilab Scilab call api CEP Buffering Custom Interface Buffering PI to PI Other PI Environn ement Buffering PI RDBMS Buffering PI RDBMS BDD EDF EDF FIILE Buffering PI UFL Quality Data from laboratory Energetical CSV XML etc Sensor SCADA 3 Water Works 40

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