Imagination at work.

Mario Testino – ServiTecnoCorrado Giussani – GE Digital

GE DigitalIndustrial Internet of Things, Data Collection and Historian Analitycs for Quality and Leakage Management in Urban Water Distribution Networks

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Presentation Details

• How to better manage water resources• Transforming data into information• The Insights• The MM Project

How to better manage water resources

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Enable the smart operatorto better manage water resources

Water Safety Plan e Water Leakage ManagementOne of the pivotal points in the model to be adopted in order to harmonize bothquality and service supply continuity is the proper monitoring of the pressurepoints in the water supply distribution network so you can build a working model atdifferent times of day and in different seasons of the year, also in consideration ofpossible changes of population, climate, and trend of rainfall data.

International Water Association (IWA)

Los Angeles Department of Water & PowerThe largest municipal utility in the US, servicing an area of over 1205 square kilometers

GE iFIX helps: • Maintain more than 11.600 km of

water pipelines

• Monitor more than 100 Reservoirs and Tanks, 400 Regulator Stations, 70 Pump Stations and 30 Treatment Stations

• Deliver almost 2 billion gallons of clean water every day to more than 4 million people

Efficient HMI at LADWP*

Three levels of Screens:High Performance HMI Screens

• Help Operators visualize a process

• Quickly determine an abnormal situation

Topographical HMIs• Help Operators visualize system areas

• Important when moving wateracross a large city

Schematic Process Style HMIs• Help Operators find the root cause

and isolate issues in the field

• Important when workingwith many different typesof facilities

*Los Angeles Department of Water & Power

Transforming data into information

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The role of GE Historianthe foundation for Industrial Internet

Collect, Archive and Distribute Production information, at maximum Speed andReliability

What is Historian?

• GE Digital’s APM edge-based data historian to collect, store and normalize time series sensor data from industrial equipment and processes

• Proprietary and patented data archiving and compression technique

• Native collectors and APIs to easily get data in and out

• Native Methods to move data to HDFS & Predix

• Foundational element to IoT Analytic capability*

Collect

• Time series process data

• Native collectors & toolkit

Store

• Millions of tags

• High Availability

• Data compression

Distribute

• HTML5 client• S95 Model

Support• Native API• Big data on-

ramp

Forrester Tech Radar Internet of Things 2016

GE Historian: the modules

• CSV• XML

• Proficy Historian

• OSI PI• Calculations

• iFIX• CIMPLICITY• OPC DA• OPC A&E• OPC UA (1)• Simulation

Storage Distribution

ProcessData

ServerData

Files

• Proficy Historian Analysis

• ProficyVision

• iFIX• CIMPLICIT

Y• Admin• Excel• OLE DB• Rest API• API & SDK

Web based

Client based

• Data Hierarchy• Compression• Security• Redundancy &

Fault Tolerance

Stores & Archives

Collection

• High write/read rate• High compression• Data integrity

The Insights

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GE Historian Analysis

Data Exploration & Analysis

Analysis

• Historian tag trending

• Run-time Python Expressions

Model

• ISA95 hierarchy

• Tag/asset searching

Collaboration

• Favorites• Alarm

Analysis

Drives Outcomes:• Visibility of sensor data

anywhere, anytime• Immediate insight• Enables collaboration• Supports ad hoc and

repeatable analysis• Puts data into context• Offers advanced analysis tools

in a simple to use framework• One click Report Generation

Analyze tags and expressions in a variety of chart types

Time-based trends

XY

Scatterplots

Multiple

AreaBox plots

Historian Query Modes

Historian Alarm & Event Viewer

Expand, analyze, collaborate through alarm notes

“Historian is the most efficient storage model for time series data on the planet”

Eric Pool, Consulting Engineer & Chief Architect, Atlanta M&D Center

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The MM project

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Performance, Quality and Leakage Management in Urban Water Distribution & Treatment Networks:The Metropolitana Milanese (MM) project

Emilio Attilio Lanfranchi - MM

Marco Grossale – MM

Mario Testino - ServiTecno

The MM ScenarioThe Milan Water Works (the figures):

� 2.400 Km of pipes

� 25.000 valves

� 31 lifting pumping stations

� 30 waste water pumping stations

� 1 water purification plant (San Rocco)

� 548 Wells

� 50.000 Users

� 250 million cubic meters of drinking water provided

� 1 Main control center «Super Centro Pilota»

� 4 Control Sub-centers The Aqueduct ensures the water supply of the wholeMilan city getting the 100% of need from undergroundwater. The pumping stations use a double lifting systemproviding the proper quantity of water to the users.

Pumping Stations

Water Purification Plant (San Rocco)

The MM project

Pumps Station SCADAs

Water Treatment SCADAs

HistorianHistorian Analysis

More than 20.000 points controlled!

PLCsOptical Fiber

RTUs

Optical FiberPLCs

Waste waterSCADAs

GSM

Internet

Collecting and archiving data from the differentplants, sensors and technologies in order toachieve a single interface and a powerful toolto aggregate data into information.

More than 10.000 points archived!

Waste Water lifting Stations

Main project objectives

Water balance key performance indicators definition & monitoring

• Quantity & Volume

• Quality

• Efficiency & Leakage

• Process analysis (water purification)

Energy management

• Energy control

• Energy saving

Improve water qualityImprove service continuity

Reduce wastes & supply costs