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Mark logic Industrialize Your Data IOT Berlin Sept 2019

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Data is a big part of the Industry 4.0 conversation but it’s not often a topic in its own right. IOT devices and sensors are creating more data than ever, digital twins need accurate data to impact operations, and the digital thread requires integrated and accessible data. These concepts are all key to industrial organizations being able to improve their products and services, better navigate increasingly complex business environments, and transform for the future. And they all need data to succeed.

But getting value from all that data isn’t easy. Many traditional data approaches fall far short of being able to manage the complexity and variability of today’s industrial data and, critically, being able to make that data securely and operationally available.

This talk will focus on how leading industrial organizations like Airbus, Eaton, Siemens, Chevron and Boeing are tackling these challenges head on with a new, data-centric approach called the Data Hub. These organizations are “industrializing their data” – investing in data as an asset that’s as essential as the people, processes and materials powering it. With the Data Hub, their projects are creating efficiency, improving quality and safety, and enabling workers today while building a foundation of data across their organizations.

Join this session to learn how you too can industrialize your data and hear about the leaders delivering on the vision of Industry 4.0!

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Mark logic Industrialize Your Data IOT Berlin Sept 2019

  1. 1. 17 September 2019© MARKLOGIC CORPORATION Industrialize Your Data and Deliver Industry 4.0 Matt Turner CSO Manufacturing Matt.turner@marklogic.com @Matt_turner_nyc #MarkLogic
  2. 2. The Importance of Data
  3. 3. Isaac Sacolick President, StarCIO 2019 Bad data is like manure … it gets everywhere! Key to Digital Transformation is knowing where data comes from and how you can use it Susan Lauda Director, Global Advanced Technology AGCO Corp 2019
  4. 4. Isaac Sacolick President, StarCIO 2019 Bad Data is Like Manure … it gets everywhere! Key to Digital Transformation is knowing where data comes from and how you can use it Susan Lauda Director, Global Advanced Technology AGCO Corp
  5. 5. 2014
  6. 6. Alan Morrison Senior Research Fellow PWC, 2018 IOT and Digital Twin are Here
  7. 7. Alan Morrison Senior Research Fellow PWC, 2018
  8. 8. Alan Morrison Senior Research Fellow PWC
  9. 9. What Does This Mean For Us?
  10. 10. Manufacturers Need a 360° View Create better products Navigate complex business Transform for the future 360° view Unified Actionable Real-time Governed
  11. 11. Impact of Integrating Data Better Products Connected technology will enable innovative new offerings Simplification Business environments are more and more complex Future Ready Digital transformation is just getting started 59activities could be automated 22B# of active IoT devices 2025 2 % MFG 3 INDUSTRY 4. 0 | Interconnectivity, automation, machine learning, and real-time data improved efficiency 30% i4.0 adopters
  12. 12. Guido Jouret Chief Digital Officer ABB Digital Twins: Two of a Kind Digital Engineering 24/7 7.5billion Potential digital twins
  13. 13. “An important factor in realizing the value of [digital] twins is an accurate and complete picture of the part, component, product, assembly line and even worker skillset” Matt Turner MarkLogic Digital Twins: Two of a Kind Digital Engineering 24/7 Industry 4.0: How to Navigate Digitization of the Manufacturing Sector McKinsey & Co. April 2015
  14. 14. What Should We Do?
  15. 15. The Answer: Michel de Ru MarkLogic, 2018 Industrialize your data!
  16. 16. Industrialize Your Data Means • Invest in data • Treat data as a first class asset • Make data universally accessible
  17. 17. Traditional Approach = Fixed Usage Define everything in rows and columns  Narrow use to specific purpose  Creates complexity for multiple complex types Fix categories into hierarchies  Define single view of product or part Result: Inflexible data can’t be used across all parts of the business Part Design Category Source Specs Piston AutoC 542 Power MFG Line 195 64mm|1 8mm|58 Air Sensor CADs HY98f Control Partner 345 5874h/I Caliper ACD404 Braking Archive CF5 Category Control Power Braking Steering Navigation Sensors … Combustion Engine Electric Intake Exhaust Sensors … Battery Rotor Sensors …
  18. 18. Schema Flexibility and Semantics! Part Name Spec Lineage Production System Source Dates Security <component> Car Model1 <Model> 2018 <production line> braking <system> Car Make <product> Caliper <part> is used in used in used in Is part ofis part of control <system> Used in
  19. 19. Data Hub Pattern 360 VIEW OF INDUSTRY ____________________________________ INDUSTRIALIZE YOUR DATA  Improve Products  Navigate Complexity  Prepare for the future SUPPLY CHAIN, PARTS, COMPONENTS ASSET MANAGMENT DOCUMENTATION AND RESEARCH ERP, HR, SECURITY AND OTHER ENTERPRISE DATA MANUFACTURING SYSTEMS HARMONIZATION SMART MASTERING GOVERNANCE SECURITY CLOUD READY DOCUMENTATION PORTALS BUSINESS ANALYSIS TOOLS OTHER APPS INDUSTRIAL DATA
  20. 20. Industrialize Your Data in Action
  21. 21. Flight Test Data Hub for Analytics and Parts Lineage  Greater data efficiency for complex analysis across 600,000 parameters all stored in different silos  Agility to address new requirements in hours, not days  Faster plane delivery with no compromise on safety
  22. 22. Graph of Events (temporal patterns) Unstructured text Structured data TEST A/C Flight Crew Report Sensor data Indexing algorithm Test Meta-data + Avionic configuration Text index of Context & Snags Rich Metadata boolean index Storage and processing DEA: Multisource search For Aircraft / test / time zones May 2019 DEA presentation
  23. 23. Multiple output format Ready to be integrated in an analytic workflow
  24. 24. Refinery Data Hub for a 360º View of Assets  Built app 4x faster than with Oracle  Savings of $5M per year  Real-time data access for safer, better decisions “Maintenance and inspections involve huge amounts of narrative context. It’s not a traditional transaction and it’s coming from multiple sources. MarkLogic does a really good job analyzing all that data.” IT Manager, Upstream New Capabilities Delivery CHEVRON
  25. 25. ERP Integration for a 360º View of the Business  Integrated 210 ERP systems (Oracle, SAP, NetSuite)  5x faster delivery time compared to Oracle Exadata  Single source of truth to make informed decisions “As you figure out your requirements, you can add and adjust your data…you don’t break anything.” Architect EATON
  26. 26. 12© 2018 Eaton. All rights reserved.. MarkLogic – Technical Advantages Benefits: • Flexible data model • Envelopes: conformed and and local data • Data model versioning Benefit: • Business transform logic all in one spot Benefit: • EL is much simpler than ETL • MarkLogic offers several technical advantages over traditional tools • Deployment Simplicity • Clustered Architecture • MarkLogic capabilities extend the Data Hub’s flexibility • Semantics • Search • Many APIs – or build your own
  27. 27. Industrialize Your Data! Leading Industrial Organizations Delivering Industry 4.0 COMPLEX MANUFACTURING Discrete, Heavy Industry ENERGY + CHEMICAL Process manufacturing INDUSTRIAL DATA Industry 4.0 Focused Organizations PRASA DHL SOLUTIONS
  28. 28. Industrialize Your Data @ Booth #13 Industry 4.0 Needs Modern Data Solutions. We’ve built a site to show you how to use data to deliver on the promise of industry 4.0. Check it out! www.marklogic.com/industry4.0 Visit us at Booth 13
  29. 29. Thank you Matt Turner, MarkLogic CSO Manufacturing Matt.turner@marklogic.com @matt_turner_nyc #MarkLogic
  30. 30. Resources • Importance of Data • Rich Data, Poor Data, Shelly Palmer: https://www.shellypalmer.com/2016/05/ri ch-data-poor-data-data-rich-data-poor- data-middle-class-not/ • Industrialze your Data:, Michel de Ru: https://www.slideshare.net/MicheldeRu/i ndustrializing-data • Semantic Data Layer • Alan Morrison Keynote - https://www.slideshare.net/AlanMorri son/collapsing-the-it-stack-clearing- a-path-for-ai- adoption?from_action=save • Plus recording of the talk (+18min) -> https://www.facebook.com/fhstp/vide os/308669336596727/ Digital Twins Digital Twins Two of a Kind: https://www.digitalengineering247.co m/article/two-of-a-kind/Digital-Twin McKinsey Industry 4.0: https://www.mckinsey.com/business- functions/operations/our- insights/industry-four-point-o-how- to-navigae-the-digitization-of-the- manufacturing-sector

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