Memex Inc. · OTC:MENXF
Memex — MTConnect Conference 2014
21 slides from Memex's conference presentation, 2014
Slide 1: Manufacturing and Scaling Big Data
Manufacturing and Scaling Big Data Dave Edstrom CEO/CTO Virtual Photons Electrons Former President & Chairman of the Board MTConnect Institute
Slide 2: What Is Big Data?
What Is Big Data? • Big Data is like teenage sex: –Everyone talks about it –Nobody really knows how to do it –So, everybody claims they ARE doing it Dave Edstrom: Manufacturing and Scaling Big Data
Slide 3: The Future Is Not What It Used To Be
The Future Is Not What It Used To Be • “Dave, I need to know what Sun will be selling 10 years from now, can you tell me?” • “Yes, I can. Just one question for you, what are the game-changing technologies that will be invented in the next 10 years? Dave Edstrom: Manufacturing and Scaling Big Data
Slide 4: Dave Edstrom: Manufacturing and Scaling Big Data
Dave Edstrom: Manufacturing and Scaling Big Data
Slide 5: Mike O'Dell's Laws
Mike O’Dell’s Laws • Scaling is ALWAYS THE problem • If you’re not afraid, you simply do NOT understand Image above is from John Meyer’s 2013 keynote Dave Edstrom: Manufacturing and Scaling Big Data
Slide 6: Cramming More Components onto Integrated Circuits
Cramming More Components onto Integrated Circuits • Published in Electronics magazine on April 19, 1965 • This article has turned into the moral equivalent of Moses coming down from the mountaintop carrying the Ten Commandments of Electronics • The author basically stated the number of circuits on a
Slide 7: 100,000 Libraries of Congress
100,000 Libraries of Congress • The amount of printed material at the Library of Congress is 10TB – A petabyte is 1,000 TB • An exabyte (EB) – The prefix exa means one billion billion, or one quintillion – 1,152,921,504,606,846,976 bytes – 1,000 petabytes, or a million TBs or a billion gigabytes – 6
Slide 8: 340 undecillion: IPv6 addressing
340,282,366,920,938,463,463,374, 607,431,768,211,456 • That’s 340 undecillion • aka IPv6 addressing – 128 bit addresses • If we took every single atom on planet Earth, we would be able to give each and every atom 100 IPv6 addresses • IPv4 was too small at 4,294,967,296 • That’s 4 billion • That’s 32
Slide 9: Neil Groundwater's Law
Neil Groundwater’s Law • /* You are not expected to understand this */ • Everything you know is wrong • How do the little electrons know? – Monster cables versus Home Depot wire • Do the math – Sun Net Manager’s Two Questions • Can be summarized as, “stop, and think through this problem.” Dave Edstr
Slide 10: Metcalfe's Law
Metcalfe’s Law • The value of any network is the number of nodes squared •N2 Dave Edstrom: Manufacturing and Scaling Big Data
Slide 11: Edstrom's MTConnect Law
Edstrom’s MTConnect Law • The value of any manufacturing network is the number of MTConnect enabled systems plus the number of software systems that are integrated with that MTConnect data squared • [MTConnect + Integrated Software ]2 Dave Edstrom: Manufacturing and Scaling Big Data
Slide 12: John Meyer's 2013 Keynote
John Meyer’s 2013 Keynote Businesses are “dying of thirst in an ocean of data” 90% 80% 1 Trillion of the world’s data of the world’s data connected devices was created in the today is generate 2.5 last two years unstructured quintillion bytes data / day 1 in 2 83% 2.2X business leaders don’t have of
Slide 13: Big Data – Seas of Manufacturing Sensors
Big Data – Seas of Manufacturing Sensors 100 9000 8000 Percentage of uncertain data Sensors 80 Percent of uncertain data & Devices Volume in Exabytes 7000 60 6000 Social 5000 Media 40 You are here 4000 VoIP 20 3000 Enterprise Data 0 2010 2015 Source: John Meyer’s [MC]2 2013 Keytnote IBM Global Techn
Slide 14: 2025 Manufacturing and Scaling Big Data
2025 Manufacturing and Scaling Big Data • 256 exabytes of data will be created in the year 2025 • A large percent of that data will be sensor data • 300 zettabytes – 300,000 exabytes of total storage around the globe • You will be carrying the equivalent of 64 of today’s iPhones in your pocket – A 4
Slide 15: So what?
It Begs The Obvious Question….. So what? Dave Edstrom: Manufacturing and Scaling Big Data
Slide 16: Karl versus Nate
Karl versus Nate Just increasing the size of your haystack does not help you find the needle Dave Edstrom: Manufacturing and Scaling Big Data
Slide 17: Moneyball's Billy Beane
Moneyball’s Billy Beane • Who saw the movie with Brad Pitt and Jonah Hill? • Groundwater’s Law – Everything You Know is Wrong – Scouts have been drowning in baseball’s Sea of Statistics for over a hundred years – Predicting how well a player will perform in the future is very different than measurin
Slide 18: What Do The Following Have In Common?
What Do The Following Have In Common? • National Security Agency • Doug Woods • Dr. Dean Bartles • An appreciation of metadata? – First, what is metadata? Data about data • NSA example phone records example • YES, all three have an appreciation of metadata AND separating the signals from all the noi
Slide 19: Edstrom Issues D2 MTCorrect Challenge
Edstrom Issues D2 MTCorrect Challenge • How do you build Doug Woods and Dr. Dean Bartles MTCorrect app? – Answers the question, “What is the best way to build this part using the right material with the equipment and the people that I have?” • This is the suggestion I have made to every single machi
Slide 20: Manufacturing and Scaling Big Data
Manufacturing and Scaling Big Data • Manufacturing means accessing and creating the RIGHT data and the right metadata • Scaling means using the right metrics and algorithms to separate the signals from all the noise • It’s not the size of your data, it’s what you do with it. Dave Edstrom: Manufactur
Slide 21: Thanks!
Thanks! • Thanks to MTConnect Community • Thanks to MTConnect Technical Advisory Group (MTCTAG) • Thanks to MTConnect Board of Directors • Thanks to AMT • Thanks to Doug Woods Dave Edstrom: Manufacturing and Scaling Big Data