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Speaker: Ales Soudek, Global Solutions Architect, OSIsoft

Date: December 13, 2017

Best practices:

Machine Learning & Data Sciencewith the PI System

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Agenda

Hello, thanks for joining us today! A few housekeeping notes:

• Webinar is being recorded!

• Check your audio connection.

• Submit questions using Webex Q&A pane at any time.

• Participate in polling questions.

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Speaker Bio

Ales Soudek • Global Solutions Architect• 23 yrs. with OSIsoft• Based in Houston, TX• Significant experience with PI AF/EF in support of sales and

customers, simulation of reactor models

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Agenda• Session Goals

• Analytics – what does it mean

• Best Practices for Analytics in PI

• Machine Learning and Data Science

• Takeaways

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Session Goals

• Demystify the hype

• Improve your ability to position the PI System

• Best Practice Steps

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Analytics

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Beware Shiny Objects

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The Hype Cycle

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Layers of Analytics• Human• Real-time• Historical• Tactical• Strategic• Edge

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Defining, Rationalization & Distribution of “Analytics”……“Layers of Analytics”

Real-time Streaming Analytics –

Tactical Machine Learning/Big Data/Advanced Analytics

Strategic Machine Learning/Big Data/Advanced Analytics

Analytics & Predictions for :- Coker Hotspot - Hydro treater sulfur in product- Hydro treater cloud point- Bromine Index Benzene- Coke drum filling & removal

Analytics and Predictions for:- Corrosion analytics (HTHA, chlorides, etc.) - Natural gas & electrical peak exceedances- CBM – exchangers, rotating equipment, etc.- Environmental Limit predictions.

Human AnalyticsEnablement of:- Data Based Decisions- Real-time situational awareness- Management by exception

Analytics and Predictions for :- Dynamic or “smart” IOW/targets/APM/PSM- “How do you “smooth” operations?- How do you optimize the yields?- How do we optimize the fuels value chain?

Integrated Control & Safety Systems

Excel Files

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Best Practices – Analyzing Data in PI

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Which of the below is your company currently using? (AF == Asset Framework)

A. AF with no Asset Analytics

B. AF Asset Analytics

C. AF Asset Analytics with Event Frames

D. AF Asset Analytics with Notifications

E. None of the above

Polling Questions

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Step 0• Define Initiative

Purpose Delivery

• Create Context – PI AF Focus on Initiative

• Analysis Type? Define needed Analyses

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Step 1• Flow chart – story board• Interaction with other Analytics• Reporting/Visualization/Applications

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Step 2• Create Calculations• Build Smart Objects

PI AF Analytics Event Frames

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Step 3• Validate calculations• Backfill• Integrate

Non-PI Analytics

• Deliver

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Upcoming Asset Analytics (2018)• Integration with R and Matlab

Looping/Iterative Simulations Statistics

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Demo

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Machine Learning &

Data Science

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Polling Questions

How many Machine Learning/Data Science initiatives is your company currently actively engaged in?

A. 0

B. 1 to 5

C. > 5

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Machine Learning

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Data Science

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Correlation

“A mutual relationship between two or more things.”

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Correlation is Not CausationCorrelation: 0.993796

Correlation: 0.998386

Correlation: 0.992835

• Correlation Coefficient 0.0 – 0.19 Very Weak

0.2 – 0.39 Weak

0.4 – 0.59 Moderate

0.6 – 0.79 Strong

0.8 – 1.0 Very Strong

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Data Science and Machine Learning• Find complex patterns

• Do not perform in a vacuum

• Must get process SMEs involved

• Understand the Algorithms

• Integrate

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Self Service BI

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What Business Intelligence Application are you using?

A. Power BI

B. Tableau

C. Spotfire

D. Other

Polling Questions

If other, please tell us.

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Some Tools in the Market• Watson

• Power BI

• Tableau

• Spotfire

• Sisense

• Domo

• Google Analytics

• SAP Analytics Cloud

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Self-Service BI Benefits• “Dynamic” reports

• Multi-dimensional analysis

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PI to Self-Service BI and Machine Learning• PI Integrator for Business Analytics

Cleanse Operational Data

Augment

Shape

Transmit

• Link from PI to External Analyses

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Takeaways

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Lessons Learned

• Layers of Analytics

• DS/ML – do not perform in a vaccuum

• Best Practices

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Questionsand

Answers

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FINAL and LAST Polling Questions3. Any feedback on how to improve our webinar is highly appreciated.A. Too technical

B. Just right

C. Needs more depth

1. How was the presentation?

A. Yes

B. No

4. Would you like to speak to OSIsoft Account Manager?

2. Is there a PI System related topic you would like to hear in our future webinar?

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Next• Stayed tuned for follow-up email

o Link to OSIsoft On-Demand webinars

o Visit PI Square

• Have conversation with Ales

Email: ASoudek@osisoft.com

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Chalk Talk Presented by:Ales Soudek

Date: December 13, 2017

Best practices in analyzing your data with PI System in the world of Machine

Learning and Data Science

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