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Jeff Immelt, GE Chairman & CEO
The real opportunity for change… surpassing the magnitude of the consumer Internet… is the Industrial Internet, an open, global network that connects people, data, and machines.
The vision is clear
“ “
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A living network of machines, data, and people
Forces shaping the Industrial Internet
Internet of things 1
Increasing system intelligence through embedded software
Transforming massive volumes of information into intelligence
4 Analytics
Generating data-driven insights and enhancing asset performance
Intelligent machines 2 3 Big Data
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Picture Here
The ability to model and understand the physical world makes it easier to optimize assets and processes
Data and the insights it provides will enable new customer services and business models
Increased visibility and control help address environmental, health, and human safety issues
Efficiency and cost savings
New customer services Risk avoidance
Industrial Internet: business value
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GESoftware.com | @GESoftware | #IndustrialInternet 5 GE Confidential GESoftware.com | @GESoftware | #IndustrialInternet
The value to customers is huge Connected machines could eliminate up to $150 billion in waste across industries
Segment Type of savings
Estimated value over 15 years
(Billion nominal US dollars)
$30B
$27B
$90B
Commercial
Freight
1% fuel savings
Exploration and development
1% reduction in system inefficiency
1% reduction in capital expenditures
Note: Illustrative examples based on potential one percent savings applied across specific global industry sectors. Source: GE estimates
Industry
$63B System-wide 1% reduction in system inefficiency
$66B Gas-fired generation 1% fuel savings
Aviation
Power
Rail
Healthcare
Oil and Gas
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Max. twitter usage in 2013 (ca. 500 Mio. tweets/day)
130 GB/Day*
Monitoring a gas turbine (200+ sensors)
588 GB/Day
Big Data More Information - More Innovation
1 1 1 0 1 0 1 1 0 0 1 0 1 1 1 1
Key: Generating actionable insight from „Big Data“ securely in real-time at every level from local to global and at industrial scale
* Quelle: wewillraakyou.com / average 280 byte/tweet (140 letters at 2 byte)
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Cloud Agnostic Cloud Everything
in-between Micro
Analytic requirements of industrial companies
FREQUENCY OF ANALYTIC
Minutes+
Seconds
Milliseconds
1,000,000’s +
Enterprise data +
Exogenous data
1,000’s
100’s
LOCATION OF ANALYTIC Wind Mining Aviation Rail
Machine Turbine Grinding circuit Engine
Plant Wind farm Mine site Aircraft Locomotive
Enterprise Distribution center Mining company Airline Railroad
INDUSTRIAL DATA Asset & process
Interaction
Orchestration
Analytics
Data collection and aggregation
Control systems
Machine Cloud
Decision support
Modular and extensible
ENTERPRISE DATA
Supply chain, finance, etc.
EXOGENOUS DATA
Market, weather, etc.
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Industrial Big Data – fast and vast
*Source: IDC
50B Machines will be connected on the internet by 2020
2X Industrial data growth within next 10 years
*Source: IDC
CRM, ERP, etc. Logs
Social network
data Geo-location
data
In practice only
3% of potentially useful
data is tagged and even less is analyzed*
9MM Data points
per hour for each locomotive
500GB Data per blade
by gas turbines
Sensor data
Content (images, videos, manuals, etc.)
Historian data
Machine data
35GB Data per day
from each Smart Meter
50X Data growth in healthcare (2012 – 2020)
1TB Data per
flight
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80% of an analytics project typically involves gathering and then preparing the data for analysis*
Today’s approaches are not prepared for onslaught of Industrial Big Data
*Source: IDC
Too slow
Too rigid
Too expensive
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Data governance
Analytics and operations
Data collection
Data ingestion
New way Current situation
Data loading
Add semantic metadata
Replica of source data
A day in the life – data management
Agility Data
scientist
Rigid
Field operations
Business analyst
INDUSTRIAL DATA LAKE
Agile
Data scientist
Field operations
Business analyst
Cost
Data collection
Data ingestion
Data governance
Analytics and operations
Cost
CRM, ERP, etc.
Logs Geo-location data
Social network data
INDUSTRIAL DATA LAKE
Real-time ingestion
Replica of source data
Add semantic metadata
Data collection
Data ingestion
Data governance
Analytics and operations
Time
Time to analyze
Data scientist
Field operations
Business analyst
Data scientist
Field operations
Business analyst
CRM, ERP, etc.
Logs, click
streams
Geo- location
data
Social network
data
Sensor data
Content (images, videos, manuals, etc.)
Machine data
Historian data
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Industrial Data Lake
Data scientist Business
analyst
Data governance and federation
Fast ingestion, storage and
compute
High performance
analysis
Optimized for mission-critical
workloads
Field operations
Industrial Data Lake
Sensor data
Content (images, videos, manuals, etc.)
Historian data
Machine data
CRM, ERP, etc. Logs
Social network data
Geo-location data
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Case study – GE Aviation Asset productivity, minimize disruptions, improved forecasting
25 Airlines
3.4M Flights
340TB Data
10X Cost reduction
7 days Time-to-market for new analytic app
2000X Performance improvement
ü Isolate root causes ü Identify sub-optimal
performance parts
ü Minimize disruptions
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Many industries, many solutions – one platform
GE Aviation
GE Healthcare
GE Manufacturing
GE Rail
GE Water
GE Oil & Gas
GE Power
Generation
GE Mining
GE Power
Distribution
GE Wind
Solutions for industrial asset and operation optimization
Predictivity™
GE Predictivity™ solutions Predix™ platform
Common architecture for machine, network, server and UX
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GE Predictivity™ solutions
GE Aviation Fuel performance, risk insight, navigation insight and fight synchronization
GE Healthcare Asset management, patient safety, patience flow, collaboration across networks
GE Oil & Gas Total equipment reliability, sub-sea inspection system optimization, field production and pipeline insights
GE Manufacturing Manufacturing process, food safety assurance
GE Mining Concentrator insights and efficiency – maximum mine production
GE Power Distribution Grid delivery optimization – advanced meter insights
GE Power Generation Turbine power flexibility and performance, maximizing asset lifetime
GE Wind Wind turbine performance, total wind farm output maximized
GE Water Connected controls for plant operations to increase efficiencies and reliability
GE Rail Locomotive Uptime, trip insights, maintenance and parts management
Predictivity™
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Shared capabilities portfolio Services
Commercial strategy
Cyber Security Cloud
Services
Development Advanced Research
Data Science Architecture
User Experience
Developing and deploying scalable
predictive solutions to enable Industrial Internet
programs
Defining new business and
delivery models for software and
services
Developing applications and solutions around
asset optimization and operations
optimization
Transforming raw data into insights and
opportunities, through descriptive, predictive,
and prescriptive analytics
Optimizing the software portfolio
to maximize market success
Focusing on security management
strategies to prevent, detect, and fix risks to
GE’s data, assets, and intellectual
property
Providing a unified, service-based solution on a
protected, fully-automated network
Driving revenue and growth by increasing adoption and demand
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GE Software’s evolving ecosystem
Guiding principles • Develop distinctive technologies • Pursue new markets • Work with the best • Share risk and reward
Ecosystem
GE is a founding member of the IIC
We collaborate to extend the reach of our Industrial Internet solutions
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Connect with us
GESoftware.com
@GESoftware
linkedin.com/ company/ge-software
youtube.com/gesoftware
19 GESoftware.com | @GESoftware | #IndustrialInternet
Taleris Objectives • Help airlines maximize aircraft utilization • Minimize the impact of maintenance • Go from diagnostics to root cause analysis
Results • Advanced prognostic algorithm allows
airlines to detect issues before they cause downtime/expense
• Monitors 10,000 independent parameters, transmits wirelessly
• Integrates with airline’s enterprise systems • Platform-agnostic solution can be installed
on any make/model, providing continuity among entire fleet
Example Use Case
Asset Management + Analytics + Experience
GE Confidential
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Field force automation
Predix FFI application examples • Locate, monitor, configure, maintain and
assess machine data (on site or off site) • Get machine info: warranty, operational
status, history, manuals • Facilitate collaboration among support
personnel • Manage work preparation, crew mark-up
and material allocation • Create/collect work orders from ERP
(Enterprise Resource Planning), OMS (Operations Management Software) and CIS (Customer Information Systems)
Right field worker. Right skills/parts.
Right location. Right time.
Example Use Case
Machine +
Experience
GE Confidential
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Rail optimization
The GE RailConnect Transportation Management System and Movement Planner System help railroads analyze critical information in real time. Customer estimate: every 1-mph increase in rail network speed saves $200M in annual capital and operating expenses
Example Use Case
Asset Management + Analytics + Experience
GE Confidential
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Power Grid – Digital Energy The Digital Industries team marshaled new technologies to enhance the operator effectiveness in running a state-of–the-art combined cycle plant. This gives engineers a visual overview of the power grid so they can identify where problems are most likely to occur and take action to prevent them, compiling the latest UX research from Power, Aviation, and Consumer Electronics.
Experience
Example Use Case
GE Confidential
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