EMPOWER YOUR ANALYTICS WITH OPERATIONAL DATA … · Title: OSIsoft Corporate PowerPoint Template...

Organiser Co-host

Sam Pride, Technical Advisor

01/10/2019

Enabling IT/OT Convergence:

Operations Data and Advanced

Analytics

EMPOWER YOUR ANALYTICS WITH OPERATIONAL DATA

Introduction

• Wants to drive and enable operations

• Deep expertise in engineering

• Wants trusted, purpose built and reliable

• Deep expertise in info systems

• Focused on digital transformation

• Early adopter of new technology

DataManagement

&Integration

OT data is from a variety of

dynamic sources

✓The PI System standardizes &

normalizes OT data

OT data requires context to

compare fleets of assets

OT data is variable,

continuous and time based

✓ Data Management with AF/EF

& PI Integrator reduces time &

complexity of analysis

✓Operations data needs to be

prepared for use in IT tools

Time-series Data is Not Naturally Aligned or

Contextualized

Extending Your Opportunity Bring Operations Insights to the Enterprise

Insights

Operations

scientists

Expertise

ITOperations

An ERP is not suited to operate your plant,

a PI System is not suited to be your ERP

It’s a better together story…

Cloud Strategy

0 20 40 60 80 100 120 140 160

T H E P I S YS T E M

MI C R O S O F T A Z U R E

I D O N ' T K N OW

O T H E R

ESR I AR C G I S

H A D O O P

I B M W A T SO N

G O O G L E C L O U D P L A T F O R M

S P A R K / D A T A B R I C KS

What Technologies are Needed for Enterprise Analytics?

*OSIsoft survey to

214 customers

OSIsoft has a multi-cloud strategy designed for

repeatable patterns with major cloud vendors

It’s a better together story…

DataScience

Virtualized PI System

Architecting for IoT

An Enterprise Data Management & Integration strategy is necessary for success

WarehouseData

Business

Intelligence

PI Server

PI Integrator for Business Analytics

Streaming

Analytics

Primary Network ingress

Machine

Learning

Streaming &

ML Insights

DataScience

WarehouseData

Business

Intelligence

PI Server

Streaming

Analytics

Machine

Learning

Virtualized PI System

WarehouseData

Business

Intelligence

PI Server

Streaming

Analytics

Machine

Learning

IoT Devices

Secondary

Network

ingress

Architecting for IoT

Advanced Analytics

Success When Used to Augment Decisions

Greater Operational

Efficiency

Better Environmental

Protection

Enhanced Ability to

Prevent Costly Failures

Henkel (with pmOne) predict

when a transition occurs for

an exothermic reaction, saving

5% of process time.

United Utilities proved an ability

to accurately predict

combined sewer overflows 6

hours before an incident.

Invenergy (with SparkCognition)

predict catastrophic gearbox

failures at least one month in

advance.

Five Considerations Before Starting with Advanced Analytics

1. Gaps in data collection

2. Poor data quality

3. Low # of modes

4. Unknown relationships

5. Natural skepticism

How does the PI Integrator help you with these obstacles?

1. Gaps in data collection – filter or interpolate

2. Poor data quality – filter unreasonable values

3. Low # of modes – determine modes by indexing on events

4. Unknown relationships – work with data experts, no code needed

5. Natural skepticism – involve SME in iterative training without requiring

a lot of their time

How do you reduce

the uncertainty of

what can be achieved

with advanced analytics ?

Adopt Iterative Workflows that Include SMEs

Discover Explore Implement

… and use technology that support these workflows

Discover

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

Begin from common

nomenclature & hierarchy

Pick from measurements

that shape the model or view

Filter based on

similar assets

Discover

Select all data from a

particular event type

Quickly preview events

after applying filter

Discover

Include multiple

filters to clean

Discover

Find all operational data

associated with all curtailment events

Remove outliers

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

Select where you

want to publish

One-time bulk or

incrementally

Benefit from native integration to

AWS, Azure, Hadoop, and SAP HANA

Discover

What if you want to

analyze events

relative to each other?

Discover

Index views

of operational

data by

events

Compare

events on a

timescale

relative to

start of the

Explore

Adjust a new

view starting from

the previous view

Implement

Create a stream

of features for

your algorithm

Begin from the

shape of your

training data

Implement

Adjust object if

needed and

determine how it

updates

Pick a messaging

hub to stream to

Summary

Capabilities That Streamline

Advanced Analytics

• Context

• Normalization

• Event Marking

• Iterative Workflows

• Operationalization

Summary

• Advanced Analytics

– Start with a small project that involves SMEs

– Use an iterative approach to your projects

• PI Integrators

– Support analytics workflows with drag-and-drop data preparation for SMEs

– Provide native integration to a variety of advanced analytics platforms and BI Tools

– Sends curated data via bulk and incremental uploads and streams

PI System Accelerates and Operationalises Advanced

Analytics

Automation SystemsAssets Edge Devices / Sensors IoT solutions

data warehouse

stream

processor

data lake

machine learning

business

intelligence tool

Operational Data Infrastructure

push trained algorithm

110111010111110

EMPOWER YOUR ANALYTICS WITH OPERATIONAL DATA … · Title: OSIsoft Corporate PowerPoint Template...

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