This document discusses how industrial companies can leverage big data and advanced analytics. It argues that applying data science approaches to industrial sectors like power, aviation, and manufacturing can yield large efficiency gains and cost savings estimated at over $276 billion across various industries. The key is taking an "industrial data science" approach that combines domain expertise in engineering and physics with techniques like machine learning, predictive analytics, and software-defined machines. This will transform how industrial equipment is monitored and optimized to extract more value. The document provides examples of how rules-based systems can be improved using machine learning on operational data combined with outcomes. It also discusses using physical models to generate new predictive features for machine learning models.
Energy Data Analytics | Energy Efficiency | IndiaUmesh Bhutoria
This white paper/forward looking note focuses on the role that energy data analytics can play in driving energy efficiency practices and investments, especially in the Indian context. It’s based on extensive desk research and supported by an online survey conducted on industry personnel and other experts
Sustainable computing is a new pathway in the research field. because it is clear the growth of ICT industries globally is rapidly poisoning our environment. So ultimately we need to give attention to this for more Sustainable computing solutions.
Energy Data Analytics | Energy Efficiency | IndiaUmesh Bhutoria
This white paper/forward looking note focuses on the role that energy data analytics can play in driving energy efficiency practices and investments, especially in the Indian context. It’s based on extensive desk research and supported by an online survey conducted on industry personnel and other experts
Sustainable computing is a new pathway in the research field. because it is clear the growth of ICT industries globally is rapidly poisoning our environment. So ultimately we need to give attention to this for more Sustainable computing solutions.
From grid infrastructure analytics to consumer analytics, the true power of data is starting to be realized. Greentech Media Co-Founder and President, Rick Thompson, sets the stage for the days presentations and panels.
[GE Innovation Forum 2015] The Industrial Internet by Bill RuhGE코리아
[GE Innovation Forum 2015] The Industrial Internet by Bill Ruh
The Industrial Internet by Bill Ruh
GE의 산업인터넷: 제 3차 산업혁명
GE글로벌소프트웨어 총괄 빌 루 부사장
GE’s Industrial Internet: the 3rd Industrial Revolution
by Bill Ruh, Vice President, GE Global Software
GE코리아 뉴스레터를 구독하세요! http://goo.gl/IE8WS8
GE코리아 YouTube 채널을 구독하세요! http://goo.gl/M2gc8m
상상을 현실로 만듭니다. Imagination at work.
GE가 꿈꾸는 가치입니다. 아니, GE는 단지 꿈만 꾸고 있는 것이 아닙니다. 상상을 현실로 만들기 위해, 불가능했던 것을 가능하게 만들기 위해 쉬지 않고 움직이고 있습니다. GE는 에너지, 의료, 항공, 수송, 금융 등의 여러 분야에서 고객과 인류사회의 진보를 위해 더 편리하고 빠르며 친환경적인 솔루션을 찾아냅니다.
Connect with GE Online:
GE코리아 웹사이트: http://www.ge.com/kr/
GE리포트코리아: http://www.gereports.kr/
GE코리아 페이스북 페이지: hhttps://www.facebook.com/GEKorea
GE코리아 슬라이드쉐어: http://www.slideshare.net/GEKorea
A “Smart” Approach to Big Data in the Energy IndustrySAP Analytics
http://spr.ly/AA_Utilities - Most companies in the oil and gas (O&G), utilities and chemical process industries benefit significantly from global markets; however, they also face pressures that demand instant response to fast-paced international events. Energy companies are using real-time data and analytics to solve key challenges in hotly competitive global markets.
-Bloomberg Businessweek Research
Green Computing is a way of study of ending reutilizing and rebuilding of computers and electronic devices is overall analysis. The goal of green computing is to reduce the dangerous material increasing the utilization of energy. Green computing implies to practices and ways of utilizing computing resources in an ecofriendly way while maintaining overall computing .green IT refers to computer and information system and IT applications and predominant strategy to help save and enrich an environment, an increase in the eco logical sustainability in today times. Green computing is under consideration of all the business organization and leading companies with the advancement of new technologies and its varieties of applications. In yester years, especially during last 10 years, computer and IT industries realized the importance of going green an addressing the major concern relating to environment and also to minimize the cost which has led to sharp drift in strategy and policy to IT industry. The importance behind this change arise from computing demand and emerging cost of energy, global warning issues ,this paper present ecofriendly initiatives under way in IT industry and in brief covers the main research challenges which are still gazing to meet green computing requirements. Ms. Amritpal Kaur | Ms. Saravjit Kaur "Green Computing: Emerging Issues in IT" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25311.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/25311/green-computing-emerging-issues-in-it/ms-amritpal-kaur
What are big data in the contacts of energy & utilities, and how/where can the utilities find value in the data. In this C-level presentation we discussed the three prime areas: grid operations, smart metering and asset & workforce management. A section on cognitive computing for utilities have been omitted from the presentation due to confidentiality - but I tell you - it is mind-blowing perspectives on how IBM Watson will help utilities plan and optimize their operations in the near future!
See more on http://www.ibmbigdatahub.com/industry/energy-utilities
Data Science for Energy Efficiency (Dmytro Mindra Technology Stream)IT Arena
Lviv IT Arena is a conference specially designed for programmers, designers, developers, top managers, inverstors, entrepreneurs and startuppers. Annually it takes place at the beginning of October in Lviv at Arena Lviv stadium. In 2016 the conference gathered more than 1800 participants and over 100 speakers from companies like Microsoft, Philips, Twitter, UBER and IBM. More details about the conference at itarena.lviv.ua.
Learn more about BISTel and our comprehensive product portfolio for collecting and managing big data, monitoring the health of equipment, optimizing process flows, analyzing large data and quickly identify root cause failures, which helps businesses drive transformative business results for customers around the world. Strengthened by 20 years long domain experiences and leading machine-learning technology, check out our corporate overview brochure to understand how we can help you optimize your factory towards smart connected factory.
From grid infrastructure analytics to consumer analytics, the true power of data is starting to be realized. Greentech Media Co-Founder and President, Rick Thompson, sets the stage for the days presentations and panels.
[GE Innovation Forum 2015] The Industrial Internet by Bill RuhGE코리아
[GE Innovation Forum 2015] The Industrial Internet by Bill Ruh
The Industrial Internet by Bill Ruh
GE의 산업인터넷: 제 3차 산업혁명
GE글로벌소프트웨어 총괄 빌 루 부사장
GE’s Industrial Internet: the 3rd Industrial Revolution
by Bill Ruh, Vice President, GE Global Software
GE코리아 뉴스레터를 구독하세요! http://goo.gl/IE8WS8
GE코리아 YouTube 채널을 구독하세요! http://goo.gl/M2gc8m
상상을 현실로 만듭니다. Imagination at work.
GE가 꿈꾸는 가치입니다. 아니, GE는 단지 꿈만 꾸고 있는 것이 아닙니다. 상상을 현실로 만들기 위해, 불가능했던 것을 가능하게 만들기 위해 쉬지 않고 움직이고 있습니다. GE는 에너지, 의료, 항공, 수송, 금융 등의 여러 분야에서 고객과 인류사회의 진보를 위해 더 편리하고 빠르며 친환경적인 솔루션을 찾아냅니다.
Connect with GE Online:
GE코리아 웹사이트: http://www.ge.com/kr/
GE리포트코리아: http://www.gereports.kr/
GE코리아 페이스북 페이지: hhttps://www.facebook.com/GEKorea
GE코리아 슬라이드쉐어: http://www.slideshare.net/GEKorea
A “Smart” Approach to Big Data in the Energy IndustrySAP Analytics
http://spr.ly/AA_Utilities - Most companies in the oil and gas (O&G), utilities and chemical process industries benefit significantly from global markets; however, they also face pressures that demand instant response to fast-paced international events. Energy companies are using real-time data and analytics to solve key challenges in hotly competitive global markets.
-Bloomberg Businessweek Research
Green Computing is a way of study of ending reutilizing and rebuilding of computers and electronic devices is overall analysis. The goal of green computing is to reduce the dangerous material increasing the utilization of energy. Green computing implies to practices and ways of utilizing computing resources in an ecofriendly way while maintaining overall computing .green IT refers to computer and information system and IT applications and predominant strategy to help save and enrich an environment, an increase in the eco logical sustainability in today times. Green computing is under consideration of all the business organization and leading companies with the advancement of new technologies and its varieties of applications. In yester years, especially during last 10 years, computer and IT industries realized the importance of going green an addressing the major concern relating to environment and also to minimize the cost which has led to sharp drift in strategy and policy to IT industry. The importance behind this change arise from computing demand and emerging cost of energy, global warning issues ,this paper present ecofriendly initiatives under way in IT industry and in brief covers the main research challenges which are still gazing to meet green computing requirements. Ms. Amritpal Kaur | Ms. Saravjit Kaur "Green Computing: Emerging Issues in IT" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25311.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/25311/green-computing-emerging-issues-in-it/ms-amritpal-kaur
What are big data in the contacts of energy & utilities, and how/where can the utilities find value in the data. In this C-level presentation we discussed the three prime areas: grid operations, smart metering and asset & workforce management. A section on cognitive computing for utilities have been omitted from the presentation due to confidentiality - but I tell you - it is mind-blowing perspectives on how IBM Watson will help utilities plan and optimize their operations in the near future!
See more on http://www.ibmbigdatahub.com/industry/energy-utilities
Data Science for Energy Efficiency (Dmytro Mindra Technology Stream)IT Arena
Lviv IT Arena is a conference specially designed for programmers, designers, developers, top managers, inverstors, entrepreneurs and startuppers. Annually it takes place at the beginning of October in Lviv at Arena Lviv stadium. In 2016 the conference gathered more than 1800 participants and over 100 speakers from companies like Microsoft, Philips, Twitter, UBER and IBM. More details about the conference at itarena.lviv.ua.
Learn more about BISTel and our comprehensive product portfolio for collecting and managing big data, monitoring the health of equipment, optimizing process flows, analyzing large data and quickly identify root cause failures, which helps businesses drive transformative business results for customers around the world. Strengthened by 20 years long domain experiences and leading machine-learning technology, check out our corporate overview brochure to understand how we can help you optimize your factory towards smart connected factory.
Industrial Internet, Should I be Interested?ionSign Oy
The Industrial Internet of Things - or the Smart Connected Products - are emerging and transforming both competition and companies. What's it all about and why should I care?
Machine learning’s impact on utilities webinarSparkCognition
Navigant Research estimates that utility companies will spend almost $50 billion on asset management and grid monitoring technology by 2023. Today many organizations are facing budgetary challenges in order to increase reliability, uptime and safety within their facilities.
The industry is adapting to new technologies including utilization of advanced sensors and sensor fusion, edge devices, artificial intelligence, and machine learning to create the maintenance center of the future.
Bernie Cook, former Director of Maintenance and Diagnostics at Duke Energy and now VP of Woyshner Service consulting, will join us to provide practical guidance and examples of how utilities can begin adapting these next generation technologies within their facilities to drive significant reduction in maintenance costs.
Following Bernie, Stuart Gillen, Director of Business Development at SparkCognition, will give examples of how machine learning technologies are augmenting current practices that make maintenance engineers more efficient at predicting critical asset failure.
Join this webinar to learn about:
- Real examples of ways utilities are moving to more advanced monitoring and diagnostic capabilities and the technologies involved.
- How machine learning can improve equipment reliability and performance, and reduce operational and maintenance costs.
- How machine learning can augment or even supplement human subject matter experts by providing significant advance notice of asset performance issues.
The Science of Predictive Maintenance: IBM's Predictive Analytics SolutionSenturus
Overview of IBM’s Predictive Maintenance and Quality (PMQ) solution. View the webinar video recording and download this deck: http://www.senturus.com/resources/science-predictive-maintenance/.
We show you the PMQ solution can keep manufacturing processes, infrastructure and field equipment running to maximize use and performance, while minimizing costs.
We show how you can use powerful analytics and data integration to help: Anticipate asset maintenance and product quality problems, Reduce unscheduled asset downtime, Spend less time solving production machinery and field asset problems, Improve asset productivity and process quality, Monitor how assets are performing in real-time and predict what will happen next.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
Unlocking the Power of Data: Data Driven Product Engineering, Evren Eryurek, ...Zinnov
We live in a data-rich world - almost everything we do is being captured and stored somewhere. There are algorithms crunching the data every millisecond and conveying unknown and untapped information. At an enterprise level, data analytics provides us a 360-degree view of our customers, products and the business landscape to make effective, smart decisions. This presentation delves into how the traditional business philosophy of ‘proximity to customer’ will lose its significance and how data will drive product decisions.
IBM Solutions Connect 2013 - Getting started with Big DataIBM Software India
You've heard of Big Data for sure. But what are the implications of this for your organisation? Can your organisation leverage Big Data too? If you decide to go ahead with your Big Data implementation where do you start? If these questions sound familiar to you then you've stumbled upon the right presentation. Go through the presentation to:
a. Learn more on Big data
b. How Big data can help you outperform in your marketplace.
c. How to proactively manage security and risk
d. How to create IT agility to underpin the business
Also, learn about IBM's superior Big Data technologies and how they are helping today's organisations take smarter decisions and actions.
A technical Introduction to Big Data AnalyticsPethuru Raj PhD
This presentation gives the details about the sources for big data, the value of big data, what to do with big data, the platforms, the infrastructures and the architectures for big data analytics
Accelerating Data Science and Real Time Analytics at ScaleHortonworks
Gaining business advantages from big data is moving beyond just the efficient storage and deep analytics on diverse data sources to using AI methods and analytics on streaming data to catch insights and take action at the edge of the network.
https://hortonworks.com/webinar/accelerating-data-science-real-time-analytics-scale/
PreScouter + GE Healthcare: How will the Internet of Things Impact your Indus...PreScouter
PreScouter and GE Healthcare partnered to analyze how they are researching Internet of Things technology. The presentation begins with a note from Dr. Ashish Basuray, Chief Scientist at PreScouter, Inc., an innovation consulting firm. Basuray addresses a fundamental question: why do we care to learn about new ideas, disruptive ideas like the Internet of Things? Following Basuray's introduction, Bill Shingleton, Ph.D., Technical Lead at GE Healthcare presented on the Industrial Internet of Things and how it impacts several industries. But, then he narrowed in on healthcare and GE's solution, Predix. This is the slide deck of the presentation for PreScouter's IoT Summit on October 6, 2016, from 5 -8 pm at the Schreiber Center in downtown Chicago.
For more information on disruptive technology, please visit: www.prescouter.com.
Infographic - Digitizing Energy: Unlocking business value with digital techno...Accenture the Netherlands
The energy industry is undergoing an unprecedented period of transition. How can digital technologies help companies disrupt existing markets and penetrate new ones?
Is your big data journey stalling? Take the Leap with Capgemini and ClouderaCloudera, Inc.
Transitioning to a Big Data architecture is a big step; and the complexity of moving existing analytical services onto modern platforms like Cloudera, can seem overwhelming.
This talk gives an introduction about Healthcare Use cases - The AI ladder and Lifestyle AI at Scale Themes The iterative nature of the workflow and some of the important components to be aware in developing AI health care solutions were being discussed. The different types of algorithms and when machine learning might be more appropriate in deep learning or the other way will also be discussed. Use cases in terms of examples are also shared as part of this presentation .
Keynote presentation from IBM Solutions Connect 2013 covering topics such as changing business world today and how technologies can help organisations cope with this change and move forward.
Similar to Compounding Business Value Through Big Data & Advanced Analytics, v2 (20)
2. What’s this all about? "
Industries that are all about
data & IT see outsized
productivity & performance
gains!
• Telecom, financial srvcs,…!
2
Making industrials all about data
& IT will transform how the world
works!
• Power, water, aviation, rail, mining, oil
& gas, manufacturing, …!
And Big Data + Physics is the enabler!
3. 3 GESoftware.com | @GESoftware |
#IndustrialInternet
The Value to Customers is Huge!
Efficiency and cost savings, new customer services, risk
avoidance – 1% improvements cuts $276B in waste across
industries!
Aviation
Power
Healthcare
Rail
Oil and Gas
Industry Segment Type of savings
Estimated value
over 15 years
$66B
$30B
$63B
$27B
$90B
Commercial
Gas-fired
generation
System-wide
Freight
1% fuel savings
Exploration and
development
1% fuel savings
1% reduction in
system inefficiency
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
5. 5 GESoftware.com | @GESoftware |
#IndustrialInternet
Internet"
of things!1SW-defined !
machines! 2 Big Data &
Analytics!3Deep domain
capability! 4Active network"
of machines, data,"
and people!
Adaptable nodes
to enable system
flexibility. !
Employing deep
physics, engineering,
and expert models to
understand the data
and build actionable
models. !
Scaling and
dramatically
accelerating time to
value. !
Critical ingredients:!
“Industrial Data Science”!
6. Cornerstone of the Transformation is
Software-Defined Machines (SDM’s)"
!
! CONSUMER"
COMMERCIAL &
INDUSTRIAL"
Device behavior has to be adaptable!
10. 10
Three basic components of Industrial Data
Science"
Physics/engineering-based models"
• Need much less data!
• Powerful, but difficult to maintain and scale!
!
Empirical, heuristic rules & insights"
• Straightforward to understand !
• Captures accumulated knowledge of your experts!
!
Data-driven techniques – machine learning,
statistics, optimization, advanced visualization, …"
• Often not enough data in the industrial domain!
• Bias: limited to regions of parameter space traversed
in normal operation!
• But easiest to maintain and scale !
!
11. 11
Industrial Example: improving rule based systems!
Many equipment operators have a system something like this, with rules
derived based on experience and intuition.
Rule sets
implemented in
Analytics Engine
Produce alerts
Low-latency
operational
data
Alerts
12. 12
Industrial Example: improving rule based systems!
Rule sets
implemented in
Analytics Engine
Produce alerts
Low-latency
operational
data
Pattern, sequence,
association mining, etc.
Outcome
data
Combine ML plus rule-based
alerts with outcome data to
produce better alerts
More
actionable
alerts
13. 13
Sensor Data
Another Industrial Example: use advanced physical
models to create new features for ML approaches!
Predicted Values
and Δs"
Variety of Machine
Learning
Techniques
Outcome
data
Using as ML features the:
1. Deviations from
expected physics, &
2. Inferred or hidden
parameter estimates
provides much richer and
effectively less noisy
data, resulting in much
stronger predictions and
models.
14. 14
Capability / Impact Ramp"
Data completeness, breadth, quality
DataScienceComplexity
Basic
Reporting
Advanced
Reporting
Anomaly
Detection
Rules
augmentation
Predictive
analytics
Prescriptive
analytics
Operational
optimization
Alerts
Highly-
actionable
management
info
High-value
guidance
Sophisticated, optimized
management of business
operations
15. Optimizes the design &
operations of complex
business and physical
systems, extracting more
value at lower risk
Broad range of deep Data Science capabilities
needed
Innovates new ways of
performing reliability
analysis, statistical
modeling of large data,
biomarker discovery and
financial risk management
Focuses on developing
algorithms and systems for
real time video analysis
Research in algorithms and
software systems that analyze &
understand images to produce
actionable insights
Develop scalable and cross-
disciplinary machine learning
& predictive capabilities to
derive actionable insights from
big data
Modeling complex system and
noise processes to detect subtle
deviations and estimate critical
system parameters
Employing deep physical and
engineering understanding of
equipment and processes to
generate normative models.
Sensor &
Signal
Analytics!
Delivering data and
knowledge-driven decision
support via semantic
technologies and big data
systems research
Knowledge!
Discovery!
Applied
Statistics!
Physics &
expert-
based
Modeling!
Machine!
Learning!
Computer!
Vision!
Image
Analytics!
Optimization &
Management
Science!
15
Industrial
Data
Science
16. 16
“Industrial Data Science” "
Outcome-oriented application of mathematical & physics-based
analysis & models to real-world problems in industrial operations. !
Tools & processes needed to do that continually & at scale. !
Improve the performance of industrial operations, e.g.,"
• Higher equipment uptime, utilization, !
• Lower maintenance/shop costs, longer component life!
• Fleet level optimization & trade-offs!
• Business optimization (linking to financial & customer data)!
Combination of :"
• Physical & expert modeling experience & depth!
• Installed base of industrial equipment and data. !
• Big Data, Machine Learning, and statistical capabilities!
What
is it? "
Why do
we do it!
What’s
needed"
Industrial
Data
Science