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© Copyright 2014 OSIsoft, LLC. Presented by Integrating Predictive Models and Microsoft BI A New Age in Analytics Curt Hertler, Partner Solutions Architect

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© Copyr i gh t 2014 O SIs o f t , LLC .

Presented by

Integrating

Predictive Models

and Microsoft BI

A New Age in Analytics

Curt Hertler, Partner Solutions Architect

© Copyr i gh t 2014 O SIs o f t , LLC .

E&P

Well Production Forecasting

Equipment/Asset/System Performance

Midstream

Equipment/Unit/System Performance

Reliability & Integrity

Hydrocarbon Processing

Planning & Forecasting

Equipment/Unit/System Performance

Models for Safe, Reliable, & Profitable Operations

© Copyr i gh t 2014 O SIs o f t , LLC .3

Continuous Improvement Process

Model

Business Needs• Profitability

• Production

• Reliability

Operational Capabilities• Current conditions

• Process behavior

• Safety & Environmental

Predictions

& Goal

Setting

Reporting &

Feedback

Analysis &

Feedback

OperationPlan Execution Model Accuracy

© Copyr i gh t 2014 O SIs o f t , LLC .

Conceptual Data Flow

4

Predictive Model

Future Data

Real Time Data

Historical Data Set

UFL or RDBS

Interface(s)

Interface(s)

PI Data Archive 2014R2

PI Asset Framework

Data Abstraction Layer

© Copyr i gh t 2014 O SIs o f t , LLC .5

“KPI Laboratory” Template

“KPI Total” Template

Reporting to Scale – PI AF

• Plant

• Process

• KPI

Asset

Hierarchy

© Copyr i gh t 2014 O SIs o f t , LLC .6

Plan Execution Reporting

© Copyr i gh t 2014 O SIs o f t , LLC .

Model Accuracy Analysis

PI Data Archive 2014 R2

Model Improvement Opportunity

© Copyr i gh t 2014 O SIs o f t , LLC .

Leveraging Real Time Data for Prediction Improvement

Actual

& Predicted

Prediction

Error

Affecting

Conditions

© Copyr i gh t 2014 O SIs o f t , LLC . 9

PI Analytics 2014

© Copyr i gh t 2014 O SIs o f t , LLC .

Power Query for Excel 2013

10

Free Add-In for Excel 2010 or 2013

• Access to useful data sources

• OData Feeds, like the PI OData feature of the

PI Web API

• Shape datasets for Power View analysis

• Remove columns and filter rows

• Insert calculated columns

• Reformat text and numeric data

• Append and merge

© Copyr i gh t 2014 O SIs o f t , LLC .

PI Web API’s OData Feature

11

CTP available on vCampus

• Connect to PI AF by URL

• Easy navigation to AF

attribute data by element

template

• Dataset types

• Snapshot

• Archive

• Interpolated

• Summaries

http://localhost/PIOData/WindFarms/T

© Copyr i gh t 2014 O SIs o f t , LLC . 12

Analyzing Model Accuracy

© Copyr i gh t 2014 O SIs o f t , LLC .

PI Data Archive 2014 R2 “DeLorean”

13

September 2013

Sneak peak, user validation

December 2013

Programming Hackathon

Demos & developer feedback

© Copyr i gh t 2014 O SIs o f t , LLC .

PI Data Archive 2014 R2 “DeLorean”

14

2014

Q2: vCampus CTP

• storage preview

Q3: Beta Program

• storage feature complete

Release

© Copyr i gh t 2014 O SIs o f t , LLC .

System-Wide Future Data

15

• PI Interfaces/Connectors

– Data In/Out

• PI Server

– AF and Analytics

• Programmatic Access

– PI AF SDK, Web API, …

• Clients

– PI DataLink, PI Coresight, …

© Copyr i gh t 2014 O SIs o f t , LLC .

Curt Hertler

[email protected]

Partner Solutions Architect

OSIsoft, LLC

16

© Copyr i gh t 2014 O SIs o f t , LLC .

Brought to you by

© Copyr i gh t 2014 O SIs o f t , LLC .

Agenda

• The What and Why of Future Data?

• What are sources and uses of Future Data?

• Examples in Predictive Analytics

• Closing Comments

• Q&A

© Copyr i gh t 2014 O SIs o f t , LLC . 19

Adding the 4th Dimension to the Cube..

Time *

Time *-1

Future Time * +1

© Copyr i gh t 2014 O SIs o f t , LLC .

More Examples of PvA BI

20

© Copyr i gh t 2014 O SIs o f t , LLC .

Closing Comments

• Future Data Enabled Predictive Analytics

• Xxxx

• Xxxx

• Xxxx

• Participation in Beta Test – “opportunity to help

shape the Future of Future Data”

21

© Copyr i gh t 2014 O SIs o f t , LLC .

Name: Stan Prosowski

Role: Sr. Plant Operator

Name: Aaron Tucker

Role: Maintenance Engineer

Name: Lalit Subramaniam

Role: Process Engineer

“As a plant operator or manager,

I want to record and visualize forecast data with our PI System,

so we can see how we are doing against our actual production numbers

and anticipate both risks and opportunities.”

“As a maintenance engineer,

I want to manage our equipment service schedule in our PI System,

so that we operate our facility at maximum efficiency and safety,

while minimizing equipment failures and downtimes.”

“As a process or lab engineer,

I want to use predictive analytics with all data from our PI System,

in order to generate and optimize our process models,

while researching future products and production techniques.”

BETTER DECISIONS

HIGHER EFFICIENCY

DEEPER INSIGHTSFU

TU

RE

DA

TA

© Copyr i gh t 2014 O SIs o f t , LLC .

Conceptual Data Flow

23

Predictive Model

Future Data

Real Time Data

Historical Data Set

UFL or RDBS

Interface(s)

Interface(s)

PI Data Archive 2014R2

PI Asset Framework

Data Abstraction Layer