Presented at the IndicThreads.com Software Development Conference 2016 held in Pune, India. More at http://www.IndicThreads.com and http://Pune16.IndicThreads.com --

1. Real-world IoT for
Enterprises
Abhimanyu Prabhavalkar
VP, PaaS Development, Oracle
abhimanyu.prabhavalkar@oracle.com

2. Internet of Things is Here
(and everywhere)

3. The Opportunity is Big …..
Especially in Manufacturing, Logistics/Transportation, Healthcare, Utilities etc.
$3
Trillion
Market
50
Billion
Devices
8
Zeta
bytes of
data
By 2020
By 2018
Today

4. Service Based Economy
Ownership ServiceBreak/Fix Preventative
Central
Service
Self/Guided
Service
Static
Analytics
Real-time
Analytics
Today TomorrowToday

5. Business Impact of IoT on Service &
Warranty
WARRANTY
COSTS
REMOTE
SERVICE
MANAGEMENT

6. Let’s consider a news story

7. Challenges in delivering IoT Solutions
7

8. The OT-IT Chasm
Business
Applications
IoT Devices
Manufacturing,Supply Chain, Asset Mgmt
Customer Relationship Mgmt, Sales, Servic
Vertical Apps – Utilities, Healthcare, Retail
Current processes
Today, many conditions are
manually detected, and then
manually entered in the business
applications
Manual
Processing
Reactive
Controls
8

9. Lack of Clarity in Value Generation
• Plenty of offerings without clear value
• Smart light switch, smart appliance etc.
• Mere Remote Control?
• Digitize the building, Energy
savings/design improvement – Much
Greater Value

10. Lack of interoperability
• Proprietary platforms
• Works best when confined to
a limited set of data sources
• Costs money and long term
engagement with vendor
• Open platforms
• Free
• Need effort for developing all
the inter-operation on your
own

11. How do I collect data from intelligent devices?
Abstract complexity associated with device connectivity
Standardize integration of devices with enterprise
Building an IoT application - Key Challenges
How do I analyze IoT data?
Reduce noise and detect business events at real-time
Enable historical big-data analysis
How do I integrate IoT data & events with enterprise infrastructure?
Make enterprise processes IoT friendly
Allow enterprise & mobile applications to control devices
11

12. Best Practices
12

13. Opportunity for the IoT Ecosystem
DEVICE OEM
SYSTEM
INTEGRATOR
SOLUTION
PROVIDER
ISV SERVICE
PROVIDER
CUSTOMER
13

14. • Understand your horizon
but pick a sandbox
• Where to start? -
Predictive Maintenance
OR Where are my assets?
Start small, think big…
14

15. Asset Tracking Application
Dashboard that shows asset
locations, performance KPIs and
Incidents
Asset Diagnostics
Operational Monitoring
• Equipment Health and Diagnostics
• Asset Utilization
• Location Tracking

16. IoT Deployment Phases
1
BusinessValue
Time to Value
Connected Assets
• Remote monitoring
• Business validation
0-3 Months
Predictive
Analytics
• Proactive decisions
• Improved products
3-6 Months
Service
Excellence
• IoT blended into
enterprise
applications
• Differentiation
through customer
experience
6-12 Months

17. • IoT is the ultimate Big Data
• Data in Motion and Data at
Rest are necessary to drive
business applications
• Easy aggregation and
visualization
• Identify patterns to enable
predictive decisions
Analytics, analytics, analytics…
17

18. • Man
• Who was operating Machines when faulty
treadmills were produced?
• Were they trained appropriately?
• Machine
• Which robots were used in production of
these treadmills?
• Were these machines operating properly?
• Method
• What inspections were performed on
these treadmills?
• Were appropriate SOP procedures
followed?
• Materials
• Which raw material batches were used
during the production?
• Which suppliers were used?
• Measurements
• What were the test results?
• Were the machines calibrated?
Man Machine
Method
Materials
Measurements
CAUSE
The 5-Ms Analysis

19. • Man
• Who was operating the machines on
which faulty treadmills were produced?
• Were they trained appropriately?
• Machine
• Which robots were used in production
of these treadmills?
• Were these machines operating
properly?
• Method
• What inspections were performed on
these treadmills?
• Were appropriate SOP procedures
followed?
• Materials
• Which raw material batches were used
during the production?
• Which Suppliers were used?
• Measurements
• What were the test results?
• Were the machines calibrated?
Man Machine
Method
Materials
Measurements
CAUSE
Reactive Analysis
IoT Data
Data in Motion
IoT Data
Data in Motion
Big Data
Data at Rest
Big Data
Data at Rest
Big Data
Data at Rest
Both Data in Motion and Data at Rest are necessary

20. Predictive Analytics

21. Time for IoT Opportunities in Mfg
Are there patterns of events that cause the equipment to fail ?
Is there a correlation between machine parameters and
product quality ?
What are the top factors/influencers that affect product yield ?
Can we predict the likelihood of certain product defects ?
What’s the downstream impact of yield change or defective
parts ?

22. Manufacturing Use Case
The 3 voices that need to be heard…

23. Solution for BestFitnessEquipments

24. An alternative news story

25. • Think distributed
• Architect for open-ness
• Empower the edge
Embrace intelligence at the edge…
25

26. Integrate don’t isolate…
Business
Applications
IoT Devices
Manufacturing, SCM, EAM
CRM, Sales, Service
Vertical Apps – Utilities,
Healthcare, Retail
IoT Cloud Service
Connect Analyze Integrate/Act

27. Embrace synergies from digital…
27

28. Architecture
28

29. Connected Assets

30. Predictive and Preventive Analytics

31. Service Excellence

32. Field Service Use Case

33. Smart Asset Maintenance with ERP

34. Smart Asset Maintenance with ERP

35. 3

36. 3

37. 3

38. 3

39. 3

40. 4

41. 42
World-wide leading manufacturer of valves,
automation components and other products
for high-tech process industry
Challenges
• Increase lifetime and reliability of components
used in safety and health-critical chemical
processes
Solution components
• Real-time filtering and processing of events
from equipment deployed worldwide
• Integration with CRM and service ticket system
Benefit
• Proactive and timely parts replacement avoids
production downtime
• Increased knowledge of product usage
improves product quality and functionality

42. Summary
• Identify use cases that drive business value
• Data in Motion and Data at Rest are necessary to drive
Business applications
• Analytics and Enterprise Integration are key to realizing
value of IoT data
• Embark on a phased approach

43. Real-world IoT for
Enterprises
Abhimanyu Prabhavalkar
VP, PaaS Development, Oracle
abhimanyu.prabhavalkar@oracle.com