0. MineSense Technologies Ltd.
Presentation to CMIC Mining Innovation Round Table: Shovel-based Mineral Telemetry Systems for Ore Routing Decision Support

1. Leading Resource Business Optimization Solution for Mining Industry
Bulk Sensing, Data Analytics and Decision Support in Mining
Reject Waste from Ore
Recover Ore from Waste
Decrease Operating Costs (25%), and Increase Revenues (15%)
Multi Billion $ Potential Market
Revenue Generating
Customer-Funded Pilots
Near-term Horizon
Raising Series B Funding
Completing Product Development
Increasing Market Penetration

2. Colossal Industry Large dollar flow: However: Low margins
+6 Billion Tonnes of Rock Moved
+$1.0 Trillion Revenue Base
+$100 Billion Capex Spend
+$150 Billion Energy Spend
However:
Low margins
Historically Low Levels of Automation
Labouring under misconceptions

3. And, Facing a Tough Future…
Therefore desperately seeks new efficiencies…
Refs: Walters et al, 2013; ABS CAT 5620; 2011

4. Opportunity: Unrecognized Heterogeneity within Ores & between Ore Types can be exploited to Create Value
Ore
Grade Heterogeneity exists within orebody…
…and within ore types from the same orebody.
Ore
Ore

5. The Solution
Sensors
High capacity, low cost
Low switching cost
Simple process integration
> Extraction > Recovery
Adds 15-50% to NPV depending on application
Opportunity
Shovel
Sense
SortOre
Product
Shovel
Bulk
(70T)
5000T/hr
Conveyor
Belt
Semi-Bulk
(<100kg)
2000T/hr
Conveyor Belt
Particle
(<1kg)
500T/hr
Location
Scale
Targeted
Capacity
Integration of Sensors & Data Analytics with Material Handling Suite Enables Smarter Production

6. Groundbreaking Sensor Tech Measures Value
Sensor Technologies:
HFEMS
Detects & Reports Metallic Content of Conductive, Magnetic Ore
Low-cost, high-capacity waste rejection
HSXRF
Proprietary algorithms for chemical analysis
Multi-stage, multi-sensor system
(Ni, Fe, Cu, Al…)
HFEMS coil, with mineral
* MineSense Patent
plus new modalities e.g. LIBS, NIR being added
Groundbreaking Sensor Tech Measures Value

7. Integration with Shovel Buckets – Sorting at the Rock Face
Armoured Control and Power
In-cheek Sensors
Current Status
70yd3 shovel system (500t/hr)
Field testing BHP 2014/15
Multi-Sensor telemetry integrates with mine planning/scheduling
Scalable to 5000 t/hr

8. And Integration of Bucket Measurements with Short Range Mine Planning & Dispatch Control System

9. With Resource Business Optimization Software at the Heart
Monitor
Evaluate
Decision
Support
Intervention
Optimization
VIASIM is a technoeconomic simulator for mine operations
Locally hosted or cloud-based
Models and simulates a wide variety of mine flowsheets and allows comparison of values with operational scenarios
Geared to add custom 3rd party process models over time
Connected to value telemetry via the www, VIASIM can be used to perform data analytics and provide decision support to mining customers
Big Data and Industrial Analytics Optimize the Process

10. BHP Pampa Norte Case Study
65,000 tpd open pit copper mine in Region IV, Atacama Chile
Reserves: Supergene & Transition 0.59% 0.4% Cu cutoff
Mine life = 8 years // hypogene zone uneconomic at current grade, ops cost & price
16 x 16m block model suggests some heterogeneity with grade ranges of 0.03% Cu > 3.6% Cu
Study Objectives:
Improve understanding of heterogeneity
Take samples & measurements of end-members
Input to MRM, Evaluate
Build & test pilot telemetry system
Build & test operating telemetry system
Integrate with MES
CuT
2.10
0.03
3.60
1.20
0.60

11. 1. Improve Understanding of Orebody Heterogeneity
16 x 16 block model 0.59% Cu
Broken down 12x12, 8x8, 5x5 down to 2m drillhole composites to understand variance
6 x 200kg samples taken of each ore type and analyzed by particle
New grade/tonnage distributions developed

12. Results – by block 15-30% value enhancement (grade and total contained Cu) revealed through re-classifying blocks at 2mx2m composite level
Head grade increases from 0.59% Cu to 0.65% Cu through enhanced 5m x 5m, even higher at 2x2
Cutoff Grade (CuT%)
CuT (%)
Tonnage (Mt)
5x5x5 model
20x20x15 model -
0.24
0.25
4,764
4,774
0.1
0.38
0.37
2,809
2,912
0.2
0.48
0.46
1,989
2,080
0.3
0.56
0.52
1,461
1,571
0.4
0.65
0.59
1,033
1,117
0.5
0.75
0.68
691
692
0.6
0.86
0.79
451
395
0.7
0.98
0.90
287
220
0.8
1.10
1.02
189
123
0.9
1.23
1.14
122 72
1.0
1.37
1.26 83 45
Thomas et al, 2012
Espinoza et al, 2011

13. Results – by particle 6 x 200hg samples taken overall
Average head grade of samples 0.3% – 1% Cu
500 particles weighed and scanned individually
60-80 individual assays to calibrate sensor results
Grade distribution % Cu
42-55% by mass below 0.3% Cu cutoff; 67-70% by mass below 0.4% Cu reserve cutoff
Represent end-members of block analysis

14. 2. Identification Phase – Economic Analysis
Reduce cutoff to 0.3% from 0.4%
Increase reserves by 300Mt
Separation of ore/waste at 5x5m scale with 80% efficiency
Head grade increases by 8%
Contained Cu remains constant, recovered Cu increases
$400M revenue increase
$25M capex (4 trucks & 2 FELS)
8% OPEX Increase ($75M)
$300M increase in NPV at Pampa Norte

15. 3. Trials – ShovelSense Mk0 Resilience Platform Deployed in Chile

16. Ultimate Vision: Shovel Systems Integrate with SMART IPCC® for Complete System:
To waste

17. 4. Next Steps
MkI trial at Pampa Norte: measurement and reporting at bucket scale
Integration of MkI system via mobile device to operator
Integration of MkI system with MIS (mine planning & fleet management systems)
Seek additional shovel trial customers
Seek underground system trial customers

18. Conclusion
Commercialization of Industrial-Scale Sensor-based Bulk Sorting Solutions for Mining Industry
Multi-billion $ Opportunity
Solution-, not technology-focused approach
Collaboration with End Users (BHP, others) for Product Development
Collaboration between MineSense and Shovel OEMS to deliver ShovelSense systems via Channel
Collaboration with OEMS (ABB, GE etc) for Pit:Port integration also being explored
Discussion and next steps?