data science for iot - prabal acharyya, osisoft internet of things world sf 2015

Empowering Business in Real-Time. © Copyright 2015 OSIsoft, LLC© Copyright 2015 OSIsoft, LLC

Prabal Acharyya

WW Director, IoT

[email protected]

Connected OrganizationsApplying advanced cloud-based data science for

operationalized predictive analysis in real-time

mailto:[email protected]

© Copyright 2015 OSIsoft, LLC

Agenda

Empowering Business in Real-Time. © Copyright 2015 OSIsoft, LLC

Connected Rig

NuGreen Drilling by

Well Well

Drilling Rig Drilling Rig

Well

SCADA 1 Omron SCADA

PI System PI System

ON

-PR

EM

ISE

PI System / PI Analytics on Azure

PI Coresight Azure ML PowerBI

PI Integrator for Azure

Azure SQL Database

SCADA 2

PI Cloud Services (Azure) via Connected Services

Collect real-time and historical data from the rigs

Create Event Frames for events like stick-slip and cloud-based Power BI Dashboard for performance analysis

1

2

Provide warnings of non-desirable events before they happen to prevent unplanned downtime

3

Stick-Slip Prevention• Rapid changes in drill torque can cause damage to drill bit

• Requires unplanned drill string removal & maintenance

• Live monitoring allows operators to preempt delays

Rate of

Penetration

(ROP)

Stick-slip

(Down)

Allows to store and analyze past

/ present /

future/predicted data

Allows to operationalize R

code as a web-service

Runs predictive analysis every 15 sec to

monitor for stick-slips

Analysis is tied to PI Asset Analytics & Notification Center

Predicts possible stick-slip events

Makes just-in-time changes to the operation

Increases the average ROP

http://tinyurl.com/Maradrill

http://tinyurl.com/Maradrill


Connected Wind Farm

© Copyright 2014 OSIsoft, LLC 16

http://tinyurl.com/UC-SF-IOT-UpWind

http://tinyurl.com/UC-SF-IOT-UpWind


Connected Airport


OSIsoft | Microsoft | Qualcomm

Infrastructure for IoT for Industrial use-cases

http://youtu.be/vZ8oshylJUg

http://youtu.be/vZ8oshylJUg


24

AllJoyn Devices

Field gateway IPQ8064 / AP148(Linux)

Event Hub

PI/AF/EF

Analytics

on IaaS

Azure ML

Power BI for

O365

PowerBI.com

ML API

Custom Code to write predictions

Back to PI 2015 as future data

by OSIsoft

Po

we

r

Qu

ery

PI

CA

ST

Connected

Airport


Connected Facilities & Campuses

Case Study: http://bit.ly/1kcqxAA

Connected

Facilities &

Campuses

Fault Detection and Diagnostic (Predictive Maintenance)

Power BI for O365

Temperature and Energy Prediction

OSIsoft PI Coresight


About OSIsoft


For over 30 years OSIsoft has:

• Infrastructure for consolidation and centralization of

sensor based data

• Open infrastructure to support best of breed

ecosystems

• Scalability from small deployments to enterprise

deployments

• Infrastructure for change

• Infrastructure for empowering people

+

A Unique and Proven Vision


400+

Pulp &

Paper sites deployed

worldwide

91%

100%

of the Global

Fortune Top 10

Metals &

Mining companies

37 of 50

of the World’s

Largest

Chemical &

Petro-

Chemicalcompanies

9 / 10

of the Global

Fortune Top 10

Pharmacompanies

Over

1,000

of the world’s

leading

Power &

Utilities companies

95%

of the Global

Fortune Top 40

Oil & Gas companies

OSIsoft is trusted by the world’s leading companies

The Power of Data


What is the PI System?


Rolled-up quality data for

supervisors

• Creating islands of systems

• Demanding we connect data, to systems, to people, to actions

• Availability and accessibility of this data is critical

Real-time Operations Data is being created everywhere

Empowering Business in Real-Time. © Copyright 2015 OSIsoft, LLC 36Customer

Use Case

Directly connects to more data

sources than any other

operational data collection system

Customer

Use Case

Customer

Use Case

Pervasive ConnectivityPI Interfaces

http://www.osisoft.com/resources/case_studies/Case_Studies.aspx




AAI, ABB, ACS, ADACS, AdvaInform, AECL, AIM, Alerton, Alfa, Allen, Alstom, Amersham, Ametek, Andover,

AnnotationArray, Aprol, APT, Arbiter, Areva, ARGA, ARL, ArrayData, AspenTech, Automated, AutoMax,

Automess, BACnet, Bailey, Barber, Basler, Batch, Baytek, Beckman, Beckwith, Bently, BitMask, Bitronics,

Bliss, Bristol, Bruker, Campbell, CANbus, Carrier, Caterpillar, Chessel, Chessell, Chicago, Cincinnati,

CircularBuffer, Cisco, Citect, Cognex, Columbia, Contec, ControlLogix, ControlNet, Controlotron, Cooper,

CSI, Cybectec, Data, DaVinci, Davis, dBase, DDE, Delta, Digital, DLSM, DMC, DMC4, DMC5, DNP, DS,

Dukane, Dynamic, Echelon, ECHO, Electro, Elutions, Emerson, EnergyLine, Enraf,Environmental, EPIC,

ERFDADS, ESC8816, ESCA, Eurotherm, Event, Field, Fischer-Porter, Fisher, Fisher-Rosemount, FLS,

Fluke, Forney, Forry, Forte, Foxboro, Freelance, Fuji, GE, GE/Harris, GE/Multilin, GEM, Generic, Gensym,

Geomation, GSE, Harmony, HART, Hartmann, Hathaway, Hitachi, Honeywell, Hsiang, HTML, Hunter, Husky,

Hyprotech,IBM, ICCP, IEC, IFS, Impact, Inductive, InStep, Intellution, Invensys, IP, Itron, Johnson, Jova, K,

Kajaani, Kaye, L, LabVantage, LabWare, Land, Landis, Leco, Leeds, MAX, Maximo, Measurex, Message,

Metso, Micro, Microsoft, Microtrac, Mitsubishi, Modbus, Modcomp, Modicon, Moore, Motherwell, Motorola,

National, NDC, Neles, Nexus, Nulec, Omni, Omron, OPC, Open, Opto22, Oregon, ORSI, PacketCapture,

Parr, Perkin, Philips, PI, Ping, Power, PowerCom, Profibus, PSE, Qualitrol, Queue, Quindar, Real, Relational,

Reliance, Reliatronics, Rockwell, Rosemont, Sartorius, SATEC, Scanivalve, Schlumberger/SEME,

Schneider, Scientech, SecondWind, SEL, Sequencia, Serck, Shell, Siemens, Simca, SIMRAD/Albatross,

SISCO, SNC-Lavalin, SNMP, SOCCS, SOLAR, Spectrum, SQ-D/Telemecanique, SquareD, Supervisory,

Suzlon, Syslog, Taylor, TCP, Teledyne, Telegyr, Telog, Telvent, Thermoteknix, TimestampClamping, Toshiba,

Trane, Triconex, Universal, VAREC, Vestas, VG-Instruments, VIM, Vitria, Weigh-Tronix, Weschler,

Westinghouse, Westronic, WinLinx, WMI, Wonderware, Woodward, XML, Yokogawa, ZIV…


SCADA 1

LIMS

CBM

Instrument

ERPAsset

Reliability

PLC2

PLC1

IPC 1

IPC 2

CAPA

Instrument

SCADA 2

Controller EMS

Learning Mgmt.

Planning and

Scheduling

Traditional

Strategy

PAT 1

PAT 2

Historian

Silos to Standards / Complexity to Simplicity

Excel


SCADA 1

Instrument

PLC2

PLC1

IPC 1

IPC 2

Instrument

SCADA 2

Controllers

PAT 1

PAT 2

LIMS

ERP

Asset Reliability

Learning Mgmt.

Co

llect

En

han

ce

Deliv

er

Silos to Standards / Complexity to Simplicity


Enterprise

Infrastructure

An Infrastructure Connects the Enterprise

QualitySafety &

Security

Energy

Utilization

Process

EfficiencyRegulatory

PerformanceAsset Health

Assets Assets Assets Assets Assets Assets


Infrastructure context joins Enterprise data

OT IT

Infrastructure

ERP PLM

Esri

SCADA MES

HMI

User

Inte

rfaces

User In

terfa

ces

Operational

Intelligence

Business

Intelligence

Relat.

DB

Big

Data

Unstr.

DB

Data

/ A

sset D

ata

/ Asset

SCADA

PLCLIMS

PI Data

Arch.


Data Science &Predictive Insights

with OSIsoft PI


Operational

IntelligenceReal time

Insight

Customer

PI Data

PI Data

Historical

Insight

Predictive

Insights

PI 2015

Future Data


PI Asset-based Analytics - Future Data Support

• Use future data as analysis input

• Trigger analysis as future events become current*

45


PI In

teg

rato

r

(Fu

ture

)

OD

ata

OD

BC

Azure Data Factory (ADF)

SQL AzurePI RDBMS Interface

PI 2015

Future Data


https://customers.microsoft.com/Pages

/CustomerStory.aspx?recid=20391

Case Study

Azure Service Fabric and OSIsoft

http://azure.microsoft.com/en-

us/documentation/videos/service-fabric-

overview-with-osisoft/

https://customers.microsoft.com/Pages/CustomerStory.aspx?recid=20391

http://azure.microsoft.com/en-us/documentation/videos/service-fabric-overview-with-osisoft/


Thank You

51

Prabal Acharyya

WW Director, IoT

[email protected]

mailto:[email protected]

data science for iot - prabal acharyya, osisoft internet of things world sf 2015

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