1 / 23

Rob Risany Aviana Global

Real World Requirements Gathering and Project Prioritization in the Era of Big Data and Analytics. Rob Risany Aviana Global. David Roscoe Doe Run. Let’s Talk About What Kind of Systems Exist. Analytics Is One of The First Business Applications. Your Modern Computer in 1959.

neve-wagner
Télécharger la présentation

Rob Risany Aviana Global

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Real World Requirements Gathering and Project Prioritization in the Era of Big Data and Analytics Rob Risany Aviana Global David Roscoe Doe Run

  2. Let’s Talk About What Kind of Systems Exist

  3. Analytics Is One of The First Business Applications Your Modern Computer in 1959 Fully transistorized! Available with Up to 16K Memory! New ExcitingCapability for Reporting in the IBM 1401:Calculated Fields on Reports!

  4. Analytics in the Modern Era…. All information, all people, all perspectives, all decisions…. All information Transaction data Application data Machine data Social data Enterprise content All perspectives Past (historical, aggregated) Present (real time) Future (predictive) All people All departments Experts and nonexperts Executives and employees Partners and customers All decisions Major and minor Strategic and tactical Routine and exceptions Manual and automated

  5. How do analytics support decision making? Analytics guides strategy and policy making -- INSIGHT We should do this! Analytics helps people (or systems!) Do the Right Thing -- ACTION What should I do Now??? DO THIS!

  6. About Doe Run – All things Lead! Mine! Recycle! Mill!

  7. Key Functional Areas where Data and Analytics Could Make an Impact • Battery Recycling Business • Underground Equipment Maintenance and Monitoring • Supply Chain Optimization • Mill Optimization Tell us a little about how you came up with these areas?

  8. Our Use Case: Getting the Lead Out How does the process provide value to the business?

  9. Let’s take a tour through the Brushy Creek Crushing Circuit Ore from Underground Reclaim Ore Oversize Ore Through Crusher Screen Vibratory Feeder Secondary Crusher Fine Ore (minus 5/8”) Fine Ore (minus 5/8”) To Rod Mill Fines Chute Rod Mill

  10. Grinding Secondary Crusher Let’s take a tour through the Brushy Creek Grinding Circuit Xanthate Zinc Sulfate Cyanide Rod Mill Rod Mill Feed Belt Water Scale R.M. Solids Ball Mill 5 Overflow to Lead Roughers Discharge 4 Cyclones Density Meter Underflow to Ball Mill Water A Cyclone Feed Sump Controls Lead Roughers Feed Upper Discharge to Cyclones Cyclone Feed Pump

  11. Pb Let’s take a tour through the Brushy Creek Lead Circuit A Xanthate – Rod Mill Feed Cyclone O.F. B A Zinc Sulfate – Rod Mill Feed A B C C Cyanide – Rod Mill Feed Roughers D MIBC – Head of Roughers D E Feed Cyanide – 1st. Cleaner * Upper Tail Lower * As Needed B Froth to 1st. Clnr. Rougher Tail to Zinc Cond. 2nd. (Final) Cleaner 1st. Cleaner E Feed Tail Feed 2 Zinc Conditioner Tail 1 Tail Froth (Bulk Conc.) To Cu Absorber Froth to 2nd. Clnr. Tail back to Rougher C Copper Absorber

  12. The Current User Experience for Managing the Mill Who Uses the system? What are the limitations of the the current system?

  13. User Experience Problem – How do you know what to do? Initial Assays (Mill Feed) • Attributes of the most experienced Operator: • Monitors the initial feed • Makes changes early to impact downstream • Intuitively knows the relationship between the numbers because they’ve seen it many times

  14. The Data: A Lot of It Where does the data come from? What does it mean?

  15. Data Problem #1 • The mill process is highly time lagged • Data about the “current process” is actually reflecting different ore at each stage of a 45 minute process

  16. Another Problem– Data Noise Is Always There Like the static on the radio, data noise is the stuff that interferes with the signal. Rocks are not well organized We have to design an approach that can handle the noise Xray Sensors are very tempermental

  17. Applying some business principles to the problem • Who can tell me something about the concepts of LEAN? Too much Performance over time Optimal Too Little

  18. Applying a Business Concept to the Logic of how a system would work: Drive between the lines Operators use their instinct to do as well as they can… BEFORE No guidance Analytics tells the operator what the lines are. With better insight the operator can do a better job AFTER With guidance

  19. Why not just get rid of the operator?

  20. The concept of the system • Account for the data challenges • Create rolling averages in the data • Segment (group) mill feed into ore types • Generate recipes for good & poor recovery • Generate rules for Lower half (poor recovery) • Generate rules of upper half (good recovery) • Give the good recipes as guidance to the mill operators! • Track ongoing change

  21. Project ROI Based on Optimizing Lead, Zinc and Copper Recovery Four Mills over time

  22. Conclusion: Some takeaways • It starts with the business context: Understand the current process • Understand the limitations of the current approach • Bad Data Will Always Be With You. Plan for it! • Design a practical system, not a perfect one • It ends with business context: What is the return?

  23. Thank you for listening…robr@avianaglobal.comdroscoe@doerun.com

More Related