The convergence of machine and intelligent data is known as the Industrial Internet, and it's changing the way we work by improving efficiency and operations.
In the age of the Industrial Internet, the data center and its key components are evolving.
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3. Industrial Internet – The Next Big Wave
•
The Industrial Internet brings together the advances of two transformative revolutions:
the myriad machines, facilities, fleets and networks that arose from the Industrial
Revolution, and the more recent powerful advances in computing, information and
communication systems brought to the fore by the Internet Revolution
•
It is a wave of innovation that promises to change the way we do business and interact
with the world of industrial machines
Wave 1
Industrial
Revolution
Machines and
factories that
power economies
of scale and scope
Wave 2
Internet
Revolution
Computing
power and rise
of distributed
information
networks
Wave 3
Industrial
Internet
Machine-based
analytics: physics based,
deep domain
expertise, automated,
predictive
4. Industrial Internet – What is it comprised of?
Three essential elements embody the essence of Industrial Internet:
•
Intelligent Machines New ways of connecting the word’s myriad of machines, facilities,
fleets and networks with advanced sensors, controls and software applications
•
Advanced data analytics use physics-based analytics, predictive algorithms,
automation and deep domain expertise in material science, electrical engineering and
other key disciplines required to understand how machines and larger systems operate
Using advanced data analytics can improve fuel efficiency, help identify machinery
maintenance issues and make other operational improvements that could add up to
trillions of dollars in savings
•
People at work: connecting people, whether they be at work in industrial facilities,
offices, hospitals or on the move, at any time to support more intelligent design,
operations, maintenance as well as higher quality service and safety. Connecting and
combining these elements offers new opportunities across firms and economies.
7. Where does the data come from?
•
The Industrial Internet starts with embedding sensors and other advanced
instrumentation in an array of machines from the simple to the highly complex
•
This allows the collection and analysis of an enormous amount of data can be
used to improve machine performance, and inevitably the efficiency of the
systems and networks that link them
•
An essential component of GE’s Intelligent Platforms business is Control and
Communication Systems that comprises advanced data collection and
advanced analytics
•
The opportunity is huge considering the specific physical assets involved in
various parts of the industrial system.
8. How ‘BIG’ is this data?
•
The industrial system is comprised of huge numbers of machines and critical
systems
•
There are now millions of machines across the world ranging from simple electric
motors to highly advanced computed cosmography (CT scanners) used in the
delivery of health care
•
All of these pieces of equipment are associated with information (temperature,
pressure, vibration and other key indicators) and are valuable to understanding
performance of the unit itself and in relation to other machines and systems
•
Traditional statistical approaches use historical data gathering techniques where
often there is more separation between the data, the analysis, and decision making.
With advanced system monitoring, the ability to work with larger volumes of realtime data has been expanding
9. How ‘BIG’ is this data?
Commercial Jet Aircraft
• There are approximately 21,500 commercial jet aircraft and 43,000 jet engines in
service around the world in 2011*
•
Commercial jets are most commonly powered by a twin jet engine configuration.
These aircraft take approximately 3 departures per day, for a total of 23 million
departures annually.
•
Each jet engine contains many moving parts; however, there are three major pieces of
rotating equipment: a turbo fan, compressor, and turbine. Each of these components
will be instrumented and monitored separately. In total, there are approximately
129,000 major pieces of spinning equipment operating in the commercial fleet today
•
While it is probably impossible to know precisely how many machines and devices,
fleets, and networks exist within the world’s ever expanding industrial system, it is
possible to look at some specific segments to get a feel for the scale of the industrial
system
10. How ‘BIG’ is this data?
Turbo fan
21,500
commercial
jet aircraft
43,000
3 departures per day
23 million departures
annually
Compressor
3
Turbine
major pieces of
rotating
equipment in
each jet engine
jet engines
129,000 major pieces of spinning equipment operating in the
commercial fleet today
Each of these
components will
be instrumented
and monitored
separately
12. How Would This Data Help?
•
The Industrial Internet promises to have a range of benefits spanning machines,
facilities, fleets and industrial networks, which in turn influence the broader
economy
•
Intelligent instrumentation enables individual machine optimization, which
leads to better performance, lower costs and higher reliability
•
Intelligent decisioning will allow smart software to lock-in machine and systemlevel benefits
•
Further, the benefits of continued learning holds the key to the better design of
new products and services— leading to a virtuous cycle of increasingly better
products and services resulting in higher efficiencies and lower costs
15. Where does all this data sit?
•
Data collection is the first step in the process of transforming recorded data into
information
•
Most data centers now have to deal with the massively increasing volumes of
data collected from entities such as the industrial internet. For eg., data
collection at GE from jet engines in one year has been more than that collected
in 96 years!
•
By 2016, most new datacenters will be 40% smaller while supporting a 300%
increased workload
•
Data centers facilities must be cost-effective, but flexible enough to enable
virtualization, cloud computing, mobility, social media and collaboration
applications.
16. Managing Data Centers – Key Challenges
Key Challenges involved in managing data centers include:
Standalone subsystems
• Visibility into baseline infrastructure eg. paralleling switchgear, standby power generation,
alternative energy sources, automatic transfer switches, UPS systems and chillers which may not
easily integrate with each other, due to disparate systems, so failures have to be managed locally
• Identifying trends, uncovering root causes and implementing strategies for improvement cannot
happen due to difficulty to collect, correlate and analyze data from these systems
Inability to scale solution
• Scalability is a challenge with standalone . Adding redundancy eliminates single points of failure
and increases reliability, but also increases complexity and systemic risk, threatening reliability
altogether
• If a data center needs to scale its technology infrastructure, extensive reprogramming and
reconfiguration is often required, which also increases costs and time to solution
17. Managing Data Centers – Key Challenges
Proprietary technologies
• Systems that leverage proprietary technologies generally face a higher likelihood of failure
when these systems are interfaced with components from other manufacturers or software
from third-party suppliers
Integration of advanced hardware and software technologies can deliver insight through
information for the highest level of efficiency, reliability, and uptime — enabling a
sustainable competitive advantage
19. Key Components of a Holistic Data Center Strategy
•
As downtime costs continue to rise, forward-looking strategies must address
various infrastructure challenges and encompass both hardware and software
solutions that are scalable, open, and tightly integrated—working together as a
comprehensive system
•
Integrating existing infrastructures with high availability control and advanced
software capabilities such as monitoring or alarming can significantly increase
operational performance by reducing human error, improving system availability
and performance, and reducing energy consumption
•
Following are five key components that are critical to helping data centers shift
toward long-term maintainability, efficiency, and reliability for facility optimization
20. Key Components of a Holistic Data Center Strategy
1. High availability control
Availability control is at the core of data center performance and helps data centers ensure data
protection, continuous operations, and recovery, in the event of an outage
A high availability solution that synchronizes systems at the beginning and end of each logic
scan execution can keep all variable data the same—providing fast, full system synchronization
and bumpless switchover for maximized reliability
Why high availability control?
Reliability:
Performance:
Precision:
Insure consistent critical
control system availability
Quick response to
catastrophic failures
No loss of data during
system failover
Control system
malfunctions must not
impact uptime
Concurrent
maintainability
Eliminate single point of
failure
21. Key Components of a Holistic Data Center Strategy
2. Advanced data collection
• Continuous operation and performance improvements of all data center systems are
only as good as the runtime data collected for analysis and action from all the
infrastructure systems
A key challenge for many data centers today is the difficulty of integrating many disparate
hardware and software systems and standalone products into a common data collection and
management strategy
•
3. Advanced analytics
• With the data collected, advanced analytics can then help extract knowledge from the
data, which is critical to driving corrective action for maximized performance and
reliability
•
Advanced analytics can provide data centers with critical context to otherwise
static historical and real-time data, increasing data integrity and enabling
better decision making for improved facility management
and performance
22. Key Components of a Holistic Data Center Strategy
4. Critical alarm response
• Leveraging next-generation alarm response management software can help data
centers reduce costs and risk by ensuring the correct response to the small subset of
critical alarms—increasing system availability and reducing liability exposure and costs
•
Alarm response management software can help operators make better decisions by
providing information and guidance with the exact responses needed to address critical
alarms. It also helps track performance and allows managers to review results and
improve response instructions.
23. Key Components of a Holistic Data Center Strategy
Why advanced data collection, analytics and critical alarm response?
Reliability:
Insight:
Precision:
Measure and analyze
system performance
metrics
Quick response to
catastrophic failures
Data collection to assess
downtime events
Concurrent
maintainability
Eliminate human error
Energy optimization
Leverage redundancy
depth to detect and
repair failures while
maintaining continuous
system operation
24. Key Components of a Holistic Data Center Strategy
5. Integration of all systems
•
As improving efficiency of power supply systems is a key goal, it is only through an integrated,
holistic approach that data centers can gain real-time views across systems and global
comparative analytics for complete facility risk assessment
•
The selected technology for managing power supply systems and infrastructure should be open
and flexible for seamless integration with a data center’s current systems as well as its future
technologies because integration enables critical understanding into the overall state of the
facility
25. Key Components of a Holistic Data Center Strategy
Total System Integration
• High Availability Control
•Power
Generation
‐ Conventional
‐ Alternatives
‐ Back-up
•Power
Quality
‐ UPS
‐ Monitoring &
Optimization
•Electrical
Distribution
‐ Switchgear
‐ Intelligent
Control
‐ ATS
•Cooling:
IT & Facility
‐ HVAC
‐ Automation
‐ Drives
•Facilities
Infrastructure
‐ Security
‐ Lamps
‐ Lighting Control
• Facility Management
Integration, Data Acquisition, Analysis, Visualization, Optimize & Control
– Real-time views across systems
– Global comparative views & analysis
– Prioritized / dollarized analysis for improvement
decision making
– Advanced Control Strategies
•IT
Infrastructure
‐ Racks
‐ Servers
‐ Software
27. GE Data Center
Challenges
• 30,000 feet2 raised floor, 3,800 servers, 2/5MVA UPS
• Reducing water & electrical consumption
• Improving maintainability
• Cooling
• Disparate & overlapping hardware & software
systems for redundancy & reliability
• 11% energy savings
• 20% water savings
• 50% chemicals
reduction
Operational Results
• Complete facility visualization
• Insight into prioritized actions through
actionable data
• Automatic PUE & EPA compliance data
collection
• Multiple maintenance contracts eliminated
• High Availability control of data center
cooling system
28. Conclusion
•
Data centers need to capitalize on the real opportunity available to maximize their
system reliability for continuous operations by moving toward an integrated and
holistic technology approach
•
High availability redundant control, combined with a set of critical software
capabilities, allows data center users to precisely monitor and control all critical
systems; understand cross-functional synergies, constraints, and performance
and cost metrics; and immediately respond to critical events with corrective action
•
By implementing the right mix of enabling technologies that provide critical
capabilities, data centers can position themselves to attain the highest level of
reliability, availability, and operational efficiency—optimizing the management of
their facility for a sustainable competitive advantage