1. 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. 2 Let’s Talk About What Kind of Systems Exist

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

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

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

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

7. 7  Battery Recycling Business  Underground Equipment Maintenance and Monitoring  Supply Chain Optimization  Mill Optimization Key Functional Areas where Data and Analytics Could Make an Impact

8. 8 Our Use Case: Getting the Lead Out

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

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

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

12. 12 The Current User Experience for Managing the Mill 12

13. 13 % Co%Cu%Fe%Pb%Zn 0.0103140.0588342.0001872.8396081.575096 0.0117160.0028682.2547662.0307680.842406 0.0099940.0503321.9655512.8160481.625338 0.0073350.4415901.8143253.8873770.801270 0.0085260.0752241.9954803.3800651.364117 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. 14 The Data: A Lot of It 14

15. 15  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 Data Problem #1

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

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

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

19. 19 Why not just get rid of the operator?

20. 20 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 The concept of the system

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

22. 22  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? Conclusion: Some takeaways

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