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Autonomous Haulage Trucks - the new way to mine. John A. Meech University of British Columbia The Norman B. Keevil Institute for Mining Engineering The Centre for Environmental Research in Minerals, Metals, and Materials Vancouver, British Columbia, V6T 1Z4 .
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Autonomous Haulage Trucks - the new way to mine John A. Meech University of British Columbia The Norman B. Keevil Institute for Mining Engineering The Centre for Environmental Research in Minerals, Metals, and Materials Vancouver, British Columbia, V6T 1Z4
"…only 10-15% of mine sites currently 'leverage technology well'...what we’re moving...toward ...with...autonomy is a factory-type environment, ...and that’s going to require...a more clinical and more managed environment. If you look at a [fully-automated] factory,...they are very sterile, very structured environments. If you have robots operating ...the floor can’t be dirty, it can’t be scattered with empty boxes... " - Carl Hendricks, CAT Mining Solutions Region Manager for Australia
"A haul road in a modern mine running autonomy …[has] ...the same issues. You can’t have poorly constructed… roads ...Some [automation] ...we use is sensitive to dust ...[which will]...cause the vehicle to sense...an obstacle...that really isn’t there. [T]hat’s going to hinder operation of the machine. There... [must]...be a new level of discipline in how we maintain that environment – just like a factory. These are...things...we should be doing,...the sorts of the things...modern processing plants do. They maintain their environment and operate with rigour." - Carl Hendricks, CAT Mining Solutions Region Manager for Australia
Outline • Automation and Sustainability • The "New" Mining Engineer • Autonomous Open Pit Haulage Systems (AHS) • Who is in the Game? • Goals (safety, fuel use, tire wear, productivity) • ETF Trucks • Modeling AHS
Motivation behind Automation Safety (removal of people from danger) Lack of skilled personnel (training costs) Loss of equipment and availability Decreased energy use (fuel savings) Decreased wear, maintenance, and replacement Increased productivity More consistent operations
Mining Truck Accidents Somewhere in the World every year at least two to three truck drivers are killed because of an accident from human error.
Batch versus Continuous (start-up/shut-down more relevant) Disturbances (environment, nature, human) Maintenance Issues Key Performance Indicators Supervisory Control vs. Autonomous Control Data and Process Integration ("Big" Data) Automation of Mining Operations
Batch Processes in Mining Drilling Loading Explosives Blasting Digging Loading Ore/Waste Hauling Ore/Waste Dumping Ore/Waste Maintenance Returning Empty
Disturbances Weather (rain, snow, mud, dust, wind, heat) Equipment failures (breakdowns, accidents) Maintenance issues (scheduled vs. failure) Ground conditions (diggability, sticky ore, rocks) Geology (hardness, rock size, mineralogy) Human breaks (shift changes, coffee/lunch) Driving behaviour (passive, normal, aggressive)
The "New" Mining Engineer Fuzzy Logic Control of a 1/10 scale Autonomous Vehicle http://www.jmeech.mining.ubc.ca/Mine432/eight_track.wmv
The "New" Mining Engineer • Understands the role of Automation • Enhance workplace safety • Reduce fuel use, GHG emissions, and tire wear • Increase life cycle time of mining equipment • Stabilize and Optimize (improve) • Improve production and productivity • Reduce haulage costs appreciable
DARPA Grand and Urban Challenges • 2004 and 2005 – Mojave Desert • 2007 - Victorville • Vehicles drove autonomously http://www.jmeech.mining.ubc.ca/Mine432/DPG_highlights1.wmv
Komatsu's AHS at the Gaby Mine, Chile www.youtube.com/watch?v=fsuRTvK3Nik
Basic Requirements • Localization – where am I? • Navigation – where do I want to go? • Obstacle Avoidance – what is in my path? • Condition Monitoring – how is my health?
Komatsu/Modular Mining Approach IEEE 802.11 n , ac , ad WLAN Computer hardware on-board Central data processing system Supervisory Software Front Runner Modular Mining Systems Modular Mining’s DISPATCH® fleet management system and MASTERLINK® communication system
Caterpillar's Approach IEEE 802.11 n , ac , ad WLAN Computer hardware on-board Central data processing system Supervisory Software COMMAND for hauling CAT’s MineStar System
Sensors – Localization and Navigation IEEE 802.11 Communication network Sensors for • Navigation >>> GPS and Radar • Object- Avoidance GPS accurate to 10 cm (D-GPS)
Sensors – Object Recognition and Avoidance IEEE 802.11 Communication network Sensors for • Navigation • Object- Avoidance >>> Radar and LIDAR Radar range to 80 m • Front LIDAR range to 20 m • Sides and Rear mm-wave Radar Obstacle Detection System
Sensors – Object Recognition and Avoidance IEEE 802.11 Communication network Sensors for • Navigation • Object- Avoidance >>> Radar and LIDAR Radar range to 80 m • Front LIDAR range to 20 m • Sides and Rear IBEO and SICK scanning laser instruments
Sensors – Object Recognition and Avoidance IEEE 802.11 Communication network Sensors for • Navigation • Object- Avoidance >>> Radar and LIDAR Radar range to 80 m • Front LIDAR range to 20 m • Sides and Rear CAT’s Radar and LIDAR-based Obstacle Detection System
Obstacle Detection - System Reliability Measure of Success << ^ ^ Goal
Elements of an Autonomous Haulage System Additional Sensors • Wheel Speed • Steering Angle • Road Edge Guidance Lasers • Payload Monitoring • Tire Temperatures (embedded in tread) • Status Lights
Requirements for Success • A Project Champion is essential at the highest levels • Long-term organization commitment based on benefits • Significant workplace culture change is needed • Revolutionary vs. Evolutionary • Small steps better than one large step • Develop new core competencies first • Engage with workforce personnel • Replace labour by attrition and promotion • Build-in system redundancies
Implementation of a Successful Project Manual Robotic Moonshot KPI (core) Replace KPI (core) 0 % Autonomous 100
Implementation of a Successful Project Manual Robotic ‘Baby’ steps KPI (core) Staged KPI (core) 0 % Autonomous 100
Implementation of a Successful Project Manual Robotic KPI (core) Integrate KPI (core) ? 0 % Autonomous 100
Implementation of a Successful Project • KPIs may decrease initially until full adaptation • Which plan is best? • Replace MHS with AHS in one step – no interaction • Isolate AHS from MHS : Separate routes, staged introduction • Integrate AHS with MHS: Significant safety concerns • Safety concerns require careful design and planning • Is a back-up or fall-back system necessary or desired?
Develop Core Competencies • Process Control fundamentals • Understanding control stability • Supervisory control hierarchies • Software algorithms • Artificial Intelligence methods • Managing large databases • Sensor knowledge and maintenance • Remote operation of equipment
Change Management Requirements • Mine Personnel Issues • Truck Drivers >>> Hardware/Software Maintenance • Introduce AHS with all affected personnel involved • Humans in-the-loop must be accounted for • Machine Issues • Monitoring health of sensors on regular basis • Soft-sensors to confirm operational effectiveness • Data Collection to integrate into planning/scheduling
Change Management Requirements • Mine Management Issues • Must be on-side with all decisions about the changes • New safety/traffic rules required (some are positive) • More maintenance / less operational activities • Drilling and Blasting practices must change • Headquarter Issues • Move to Central Control must be done with care • Initial focus on integrating massive data collections • Decisions must support local mine site personnel
Mines using AHS CodelcoRadomiroTomic, Chile Komatsu Cu 2005 Codelco Gabriela Mistral, Chile Komatsu Cu 2008 Rio Tinto West Angelas, Australia Komatsu Fe 2010 BHP-Billiton Navajo Coal, NM, USA CAT coal 2012 BHP-Billiton Jimblebar mine, Australia CAT Fe 2013 Fortescue Solomon mine, Australia CAT Fe 2013 StanwellMeandu mine, Australia Hitachi coal 2014
Komatsu – Codelco Radomiro Tomic mine - 2004
Komatsu – Codelco Radomiro Tomic mine - 2005
Komatsu – Codelco • In 2006: 5 AHS 930E trucks; 32,000 tpd; 256 days • Mechanical Availability: > 90% • Cost per tonne reduced from $1.36 to $0.50 • Est. maintenance reduction: 7 % • Est. depreciation reduction: 3 % • Gaby mine AHS trucks: 2008 – 11 2012 – 18 • Safety issues (accidents): 2006 – 0 2007 – 2
Komatsu – Codelco • AHS trucks operate in an "electronic bubble" • Each truck is aware of all other machines on site • Unknown machine in AHS area causes shutdown • Navigation is a hybrid of • High-precision GPS, and • Dead-reckoning IMU (accelerometers/gyroscopes)
Komatsu – Codelco • Change how mine operations are planned & implemented • Must consider all vehicles, not only AHS trucks • Complexity increases exponentially with number of trucks "There are hardware restrictions...Information exchanged between trucks and central control is enormous. At Gaby, 11 trucks and 30 pieces of equipment...limit...information transfer." – Jeffery Dawes, Komatsu Chile
Komatsu – Rio Tinto • Rio’s “Mine of the Future” concept • Began in 2008 at West Angelas Mine, Australia • First 24 months • 42,000,000 tonnes • 145,000 cycles (290 t) • Short haul distance ~1.5 km • 5 trucks – 25 min. cycles • Ave. Velocities (initial trial): • Loaded = 7-10 kph • Empty = 14-18 kph
Caterpillar - BHP-Billiton • Joint venture at 2 mines since 2007 • Mt. Keith Nickel Mine in Australia • Navajo Coal Mine in New Mexico • Initial 2 truck trial in Arizona and at Mt. Keith - 2010 • Planned a staged implementation from 5 > 55 > 150 • Plan was adjusted after 2008 Financial Crisis • Planning an Integrated Remote Operations Centre (IROC) in Perth to schedule/plan/control Pilbara mines http://milltongroup.blogspot.ca/2011/09/bhp-plans-autonomous-mining-operation.html
Caterpillar - Fortescue • MOU with Fortesque and WesTrac in 2011 • Solomon Iron Ore Mine in Australia • CAT MineStarTM system & Command for hauling • Initial fleet - 12 AHS 793F trucks – 2012 • At full capacity, 45 AHS trucks by 2015 http://www.miningmagazine.com/reports/cat-signs-haul-truck-deal-with-fmg
European Truck Factory – the next step? • Decoupling Maintenance from Operation • 95% Mechanical Availability http://www.etftrucks.eu