From a session at OMEP's Manufacturing the Future Summit, January 14, 2014. By: Katie Moore Global Industry Manager – Food & Beverage GE Intelligent Platforms
Branding Your Start-Up: Talk from Barcamp Portland 2012
The New Age of the Industrial Internet
1. The New Age of the
Industrial Internet
Katie Moore
Global Industry Manager – Food & Beverage
GE Intelligent Platforms
Imagination at work.
2. Forces Shaping The Industrial Internet
Setting the stage for true business transformation
1
Internet
of Things
A living network
of machines data
and people
2
Intelligent
Machines
Increasing system
intelligence through
embedded software
3
Big Data
Transforming
massive volumes
of information
into intelligence
4
Analytics
Generating
data-driven insights,
enhancing asset
performance by
detecting and
predicting
3. In the next five years…
%
40
50b #1
of skilled
manufacturing
workers will
retire1
machines will
connect to the
Internet2
Priority of CIOs
is to drive
more business
insight3
A new generation of workers expects
answers at their fingertips.
Sources: 1. Wall Street Journal, 11/2/11; 2. More than 50 billion connected devices, ERICSSON, 2011; 3. The Essential CIO, IBM, 2011
4. Automation is a very conservative
industry … for all the right reasons
…and pressed to evolve
5. Machine Builders Face An Evolving Market
Ship it & Support it
Smartphone
experience
Here today, gone…
Long-term
relationship
Required focus on
form and function
Accelerating rate of
technology change
6. Enabling Technologies
SOFTWARE
The integration of traditional
industries and IT technology reshapes
the competitive landscape …
CONSUMER ELECTRONICS
New levels of computing power and
networking enable solutions that are
more accessible, simple, and powerful
Examples
Examples
Amazon,
Trip Advisor
CONNECTIVITY
Secure, trusted and high-performance
connectivity on public networks
Examples
Skype,
CrashPlan
Smartphones
Navigation systems
COLLABORATION FRAMEWORKS
Cloud-based platforms provide faster routes
to solutions, higher quality content & better
manageability than traditional equivalents …
with better financials for all
Examples: Wikipedia, Salesforce, Topcoder
7. Common Threads
• Self-assembling networks of nodes integrating
into ecosystems
• Secure, efficient and high performance
communication protocols enabling
3rd party device connectivity
• Scalable computing power,
available on demand
• Collaboration platforms
with published interfaces
as enablers for content
creators and consumers
8. The Industrial Internet
Brilliant
Machines
Advanced
Analytics
Connect machines,
facilities, fleets and
networks with advanced
sensors, controls and
software applications
Combine the power of
physics-based analytics,
predictive algorithms, and
deep domain expertise
People At Work
Connect people at work any
place, any time for intelligent
operations
9. Trans.
Aero
Thermal
Rail
Signaling Battery Mining Industrial
XD
Pow. Conv.
Marine
Pow. Conv.
Drives
Pow. Conv.
Dynamic
Positioning
Digital
Energy
Gas
Engines
Nuclear
Water
Controls are
pervasive
across GE
Wind
Solar
Control
Solutions
M&C
Intelligent
Platforms
Xinhua
Bently
Ultrasound
F&PT
MR
Sensing
CT
Commercial
Military Systems LED
Aviation
Out
Indoor door
Light
Art.
Lift
Turbo
Hydril
Subsea
= Platform, Sensor, or Actuator products business
GE Engineers are the brains behind our products,
Controls are the brains on our products
10. Connected Controls Architecture
It starts with a platform architecture
built for a connect world
Capabilities
CREATING BRILLIANT MACHINES
Technologies
Smart,
powerful
connections
ENABLING ADVANCED ANALYTICS
SINGLE
INTEGRATED
ARCHITECTURE
Cloud based
automation
POWERING PEOPLE AT WORK
High
Performance
Platforms
ProfiNet
networked I/O
14. GE Equipment
Monitored for reliability and performance
200,000+ assets connected
21,000
aircraft engines
10,000
gas & steam turbines
15,000
wind turbines
110,000
medical equipment
12,500
locomotives
Plus…
Power transformers
Motors
Water treatment
Pumps, Valves
Turbo Machinery
Compressors
Millions of analytics
run daily
“Process Industry stores more data than any
other sector — close to 2 Exabyte's(1018) of
new data stored in 2010.”
- McKinsey & Company
15. Big Data for the industrial sector
How does data get ‘Big’?
Data generated from one of many machines at one of many
plants producing a specific personal care product.
16. Forces Shaping The Industrial Internet
Setting the stage for true business transformation
1
Internet
of Things
A living network
of machines data
and people
2
Intelligent
Machines
Increasing system
intelligence through
embedded software
3
Big Data
Transforming
massive volumes
of information
into intelligence
4
Analytics
Generating
data-driven insights,
enhancing asset
performance by
detecting and
predicting
17. A view to what we are doing about DATA
Plant
• Data w /Model Content
• Scales with hardware
• Centralized
administration
Machine
•
•
•
•
152k samples/sec
Embedded Controls
Ultra High Speed Writes
Small footprint
Enterprise
• Multiple plants consolidated to
single historian
• Common Configuration
Industrial Big Data
Enabling Big Analytics & Visualization
30-2-1 Large Query Performance
Unlimited data
Unlimited clients
Cloud-enabled
18. It’s not just a Big Data challenge
Data diversity is equally challenging
Field
Shop
Image
Event
Design
End
Of Life
Maint.
Run my machine better
Run my fleet better
Run my business better
19. A Predictive Science Evolution
What’s the best the can happen?
Predictive Modeling
Competitive Advantage
Optimization
What will happen next?
Analytics
Forecasting/extrapolation
What if these trends continue?
Statistical analysis
Why is this happening?
Alerts
What actions are needed?
Query/drill down
What exactly is the problem?
Ad hoc reports
How many, how often, where?
Standard reports
What happened?
Degree of Intelligence
Source: Competing on Analytics, Davenport/Harris, 2007
Access and
reporting
21. To the right place at the right time … RTOI
Role Based - GEO Awareness
Mobility - Integrated Analytics
Trusted Sources
•
•
•
•
Connectivity
Provisioning
Exception based
Cloud to Site
service delivery
Industrial Mobility
Advanced Information
Collaboration
HHA
HA
Temperature
L Dev
S Dev
Setpoint
S Dev
L Dev
LA
LLA
Time
High High Alarm
High Alarm
Low Alarm
Low Low Alarm
Small Deviation
Large Deviation
From data everywhere to actionable knowledge at the right place, right time & right person
22. Analytics at Industrial Scale
Ingest
diverse and
distributed
data
Advanced
Insight from
analysis
across
Machine,
Operational,
and
Financial
Data.
Requirement
Support for multiple
data formats
Model discovery and
multi-model fusion
Faster path
to superior
models
Cloud
resources for
sharing and
scale
compute
Capabilities
Elastic compute for
massively-parallel
simulation and
machine learning
Features
23. Global Pet Food Processor Improves
Quality and Yield
CHALLENGES
• Lack of tools to
the
Applicableunderstand what was happening on logsplant floor
• Quality data entered on spreadsheets and operator
leading to
information gaps and errors
photo
• Opportunity to improve system quality and efficiency
RESULTS
• Operators able to make decisions based on real-time data and
input information at the point of production
• Increased uptime, reliability and productivity
• Visibility to quality data by SKU enabled formula adjustments
that resulted in cost savings of $0.01 per case on one SKU
The ability to make data driven process adjustments
resulted in a cost reduction of more than $200,000 per
year on one SKU in one plant.
24. Starting the Journey to the
Industrial Internet …
1
Do you collect meaningful data ?
2
Do you have a strategy to store and access the data you collect ?
3
• Asset Data from Sensors
• Process Data
• Manufacturing Data
• Historian at the line, plant, enterprise level ?
• Visualization strategy that puts the right information in the right hands at the right time
Have you Prioritized the outcomes you desire ?
•
•
•
•
•
•
Higher throughput
Less Waste
Less Energy usage
Higher Quality
Better asset life
No unscheduled downtime
WE CAN HELP RIGHT NOW !