introduction to analytics with the pi system · intro to asset monitoring and condition-based...

#PIWorld ©2019 OSIsoft, LLC

Introduction to Analytics with the PI System

Omar Siddiq, Systems Engineer

Landry Khounlavong, Product Marketing Manager

1


Where are we in the PI System Introduction

01 02 03 04

PI System & the Greater Operational Data Landscape

Landscape

Technical Crash Course on the PI System

Crash

Course Intro to Asset Monitoring and Condition-based Maintenance with the PI System

Asset

Monitoring

Introduction to Analytics with the PI System

Analytics


3

“Analytics” offer many choices…


4 4

Where do I start? or

Where are the quick wins?


Small projects propel success for a large project

5

Must-have project characteristics

• Subject matter expert included

• Sufficient business value

• Related to larger initiative

RO

I

time 3y


6

Plant Manager

“What is our current

capacity factor?”

Live KPIs for quick decisions Know availability for the grid Additional supporting data Asset-based data object Drill down for granularity Equipment-level visibility


7


8


9

Plant Operator

“What is occurring during

turbine curtailments?”

Self-service event

comparison

No waiting on a central team

Quick event comparisons

Find longest curtailment

Insights without coding

Just learn to drag-and-drop


10

Ad hoc event comparison inherits event & asset structure enabling easy event comparison


PI Interfaces

&

PI Connectors

Da

ta S

ou

rce

s

Store & Enhance

Asset

Framework

Asset Analytics

Event Frames

Collect

11

Visualization PI DataLink

PI Vision

Cloud Services

PI System Access

PI Manual Logger

PI ProcessBook

PI WebParts

Custom applications

Business systems

PI Cloud Connect

</>

Deliver

PI Integrators

Business Analytics

SAP HANA

Notifications

PI Server

Data

Archive


PI System Infrastructure

PI Data Archive

PI In

terf

ace

s &

PI

Connecto

rs

Collect


Analytics

PI Asset Framework

PI Data Archive

PI In

terf

ace

s &

PI

Connecto

rs

PI Server


Enhance &

Contextualize


1

4

BGE003 FI-111 02T100 AF_FLOW3 02:T103 AT401

ACEDemo.Unit1.Output

TI-178 B352_W778 0_CMP_SVLV_PCT

02F104 CD:F161

GE01_DT 409510395_Wind Speed QI-109 GE01_DT Cooling Fan-711.Feed Rate

1-8.Net

Volume 03LBA32CT0

01-2

DC.SJ.ITLoad.P

WR

TI-145 FR2001

TI-178

GE04_OS

FT9001

FT9001 FR5001

AF_NOISE

DC.SJ.PUE TI-102 DC.Zero DY-108 DC.SJ.C1.Z3.R3.PDU1.PF GE01_A_DT

GE04_Status

02:F101.C

FIC-144 02F100 fasttag

FI-151 0_ENG_AUX_STS

AQUA2-SI005.PV GE02_Energy 0_ENG_MODE_STS FI-151 02T103.Q DC.Z1R

0_CMP_HDR

GE05_Energy C1:14AT5 AC03.Air Flow FeedBin.Cmt Boiler Cold Reheat Pressure

B737_FG117 DC.TimeLoad

D-110.Tank Pressure.PV GE04_DT QI-121 GE03_V_WIN

DC.Rk07R DC.Srv06R GE04_Energy

TI-121 FT9001

FAC.OAK.Power-Kh-Val.PV

fic1001.C GE02_OT

02F102.1HR

AVG BGT001

PI-111 facility_output

DM-05:BW.R

DC.SJ.C1.Z1.R1.Rk06.S2.O03.PWR QI-111FinalProductBin.On

94:GRDIDX.ProdID Boiler-209.Fuel Gas Flow

GE01_A_DT

fic1001.C

02:F101.C

FR2001 TIC-121

Aso AT401 DC.Srv01R

TI-178

asset1_output Active Meters

GE01_A_DT aso AF_NOISE PI-115 DM-05:BW.R

FI-101 Volume

0_CLR_FINAL_OUT_B_TMP F506_E990 339511775_Clear Sky Global Horiz GE01_DT

FI-111

% CO2 GE05_ES T

GE01_CON AlarmTest.Input.

Float32.1

DC.NY.Actual.PWR.day.Tot

80-5.Net Volume GE01_A_DT

45-2.Net Volume

Boiler-209.Fuel Gas

Flow DC.Srv01R

94:GRDIDX.Tr

trigger

AC09.Power

403511195_Wind

Speed

DC.C2Z1.Pwr.Rippl

e GE01_A_DT

AF_NOISE

1-16.Net Volume CB1992_MS

0_CMP_FLOW_TOTAL

FT9001

fasttag

FeedBin.Cmt

DC.Zone1.Number

FT9001

AlarmTest.Input.Float32.1

FT9001

DC.Srv01R Boiler-

125.Fuel Gas

Volume

1-13.Net

Volume B045_FG978

AT401

Anacortes Refinery.Alkylation.Asset

Problems B210_FG005.KPIExcursion

D-110.Tank

Pressure.P

V Boiler Feed

Pump #1

94:BW.R TI-101 F723_E889

369512185-Temp Compressor-439.Feed Rate

DC.CH.DCE FIC-172:210

FI-121 AF_FLOW3

0_ENG_MODE_STS

GE03_Q

DY-131:166 GE01_TD

Boiler-334.Feed Rate

GE04_OSAsset1.Problems QI-122 FI-151

DC.SJ.SiteRealTim

eITLoad.PR FT9001

Weather

Conditions

Relative Humidity: 34%

Current Temp: 85 F

High: 92

Low: 57 F

Wind: 8 mph/N

Crude Furnace

Draft Pressure: -0.5 WC

Stack Temp: 316 F

Oxygen: 2.5%

Outlet Temp: 840 F

Cold Oil Velocity: 6 ft/sec

Crude Desalter

Operating Pressure: 110 psi

Charge Rate: 14 gph

Mix Valve Pressure: 8 psi

Water Rate: 8%

fic1001.C FR5001

AQUA2-TI-201.PV

TIC-181

BGE003 FI-111 02T100

AF_FLOW3 02:T103

ACEDemo.Unit1.Output

TI-178 B352_W778 0_CMP_SVLV_PCT

02F104 CD:F161

AQUA2-SI005.PV GE02_Energy

0_ENG_MODE_STS FI-151 02T103.Q

DC.Z1R 0_CMP_HDR_SUC_PRS

DM-05:BW.R

DC.SJ.C1.Z1.R1.R

k06.S2.O03.PWR

QI-111FinalProductBin.On

94:GRDIDX.ProdID Boiler-

209.Fuel Gas Flow

FI-101 bf5e1d1d-

39c9-4b5b-b3d3-

c2ce05fa3a26 DM-05:BW.R AT401

AT401

DailyTrigger FrqPrbCost_ER

GE01_DT 409510395_Wind Speed

QI-109 GE01_DT Cooling Fan


364511575-AC Power

DY-101 02:F101.C

0_CLR_FINAL_OUT_B_TMP F506_E990

339511775_Clear Sky Global

Horiz GE01_DT

80-13.Net

DY-131 DC.SJ.PUE


GE01_DT

FI-101 bf5e1d1d-39c9-

4b5b-b3d3-c2ce05fa3a26 DM-05:BW.R AT401

4-36.NetVolumeAC04.Air Flow

02T100 03LBB02CT001-2

DC.SJ.SiteRealTim

eITLoad.PR FT9001

02F102.1HRAVG BGT001

PI-111 facility_output

AQUA2-SI005.PV GE02_Energy

0_ENG_MODE_STS FI-151

02T103.Q DC.Z1R 0_CM P_ H D R _SU C _ PRS

403511195_Wind Speed

GE02_Energy

FI-101 bf5e1d1d-39c9- 4b5b-b3d3-c2ce05f

Map raw data to the physical world and normalize it across the enterprise


15

Status

Power

Overall Efficiency

Total Power

Unit % Uptime

Status

Power Power

Status

Make raw data decision-ready


PI Event Frames

Analytics

PI Asset Framework

PI Data Archive

PI In

terf

ace

s &

PI

Connecto

rs

PI Server



Identify discrete events within continuous data streams

17

Discover Event Interrelationships

Compare Assets

Compare Events

Simplify Data Analysis

Name Max

EF1 122.47

EF2 112.73

EF3 98.61

EF4 125.24

Downtime Running XYZ


PI Interfaces

&

PI Connectors

Da

ta S

ou

rce

s

Store & Enhance

PI Server

Notifications

Data

Archive

Asset

Framework

Asset Analytics

Event Frames

Collect

18

Visualization PI DataLink

PI Vision

Cloud Services

PI System Access

PI Manual Logger

PI ProcessBook

PI WebParts

Custom applications

Business systems

PI Cloud Connect

</>

Deliver

PI Integrators

Business Analytics

SAP HANA


BI Tools & Algorithms

expect time-aligned data

Data Scientists & Business Analysts

need that data contextualized

19


Time-series Data is Not Naturally Aligned or Contextualized

20


Advanced Analytics Workflows are Iterative and Need SMEs … use technology that support this approach

21

Discover Explore Implement


Data preparation capabilities that accelerate

training algorithms or creating views for BI

Tools:

• Common nomenclature

• Aligned data

• Normalized measurements across assets

• Complex filtering by

• Asset type

• Event type

Discover

22


Discover

23

Begin from common

nomenclature & hierarchy

Pick from measurements

that shape the model or view

Filter based on

similar assets


Discover

Various ways

to clean the

data


Discover

Select all data from a

particular event type

Quickly preview events

after applying filter

25


Discover

Include multiple

filters to clean

data


Operational data of an asset that is usable by

algorithms or BI Tools!!

• Asset Context

• Data Alignment

• Asset Normalization

• Filtered on a Curtailment Event Type

• Filtered for T > -273.15 C

Discover


Discover

Select where you

want to publish

One-time bulk or

incrementally

push

Benefit from native integration to

AWS, Azure, Hadoop, and SAP HANA

28


Advanced Analytics Workflows are Iterative and Need SMEs … use technology that support this approach

29

Discover Explore Implement


Explore

Adjust a new

view starting from

the previous view

30


PI System integrates to a variety of advanced analytics components

Automation Systems Assets

Edge Devices / Sensors IoT solutions

data

warehouse messaging

hub

data

lake

machine

learning

business

intelligence

tool

Enterprise Operations Infrastructure

train algorithm


32

Takeaways

• Obtain quick value by providing data to experts

• Start small to de-risk advanced analytics projects

• PI System enables you to accelerate your analytics with context and normalization layered on top of raw operational data

Data Scientist Investigate how

PI Integrators can

save you time

preparing data

Engineer/Operator See how PI Vision can

give a full view of your

processes and systems

General Manager Speak to our customers

about the value they

gain from PI System

and checkout industry

tracks on Wednesday


33


Contact us for more information…

34

Landry Khounlavong

[email protected]

Product Marketing Manager

OSIsoft, LLC

Omar Siddiqi

[email protected]

Systems Engineer

OSIsoft, LLC

mailto:[email protected]

mailto:[email protected]


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#PIWorld ©2019 OSIsoft, LLC 36

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INDUSTRY TRACKS TOMORROW


Tomorrow @ Parc 55

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introduction to analytics with the pi system · intro to asset monitoring and condition-based...

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