part 4 getting ahead in the digital age of mining · market trends (e.g. new age workforce, tech...
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Mining’s Next Horizon Webinar Series
Part 4 – Getting Ahead in the Digital Age of
Mining
Mining’s Next Horizon Series
Part 1: The Next Generation of Minerals – Powering Mining into the Future8 November 2018
Part 2: Disruptive Innovations Creating Smarter Mining20 November 2018
Part 3: Transforming Culture to Foster Innovation21 February 2019
Part 4: Getting Ahead in the Digital Age of Mining7 March 2019
Part 5: Mine Site Connectivity – Enabling the Digital Revolution16 April 2019
Part 6: The Small Footprint Mine of the Future2 May 2019
Part 3: Transforming Culture to Foster Innovation
• Innovation and culture are tricky concepts because they mean different things to different people.
• Innovation is about step changes or transformational changes and these rely on cultures that thrive on new thinking.
• Difficult to find the balance between production and innovation in mining, with many cultural impediments in the way.
• People are key to successful innovation and consultation is required through the steps of Adoption > Implementation > Sustaining.
• Millennials entering and attaining management positions in the mining industry is set to be a major driver for cultural change.
VIEW RECORDING
Today’s Speakers
Roy Pater, VP Marketing & Sales, Mineware
George Long, Digital Mining Lead, Accenture
Sam Oliver, Senior Applications Engineer,
MathWorks
DIGITAL IN MINING George Long
March 7, 2019
RESOURCES
DIGITAL TECHNOLOGY IS EVOLVING AT AN EXPONENTIAL PACE
1 MAINFRAME
2 CLIENT-SERVER AND PCS
3 WEB 1.0 ECOMMERCE
4 WEB 2.0, CLOUD, MOBILE
BIG DATA, ANALYTICS, VISUALIZATION5IOT AND SMART MACHINE6ARTIFICIAL INTELLIGENCE7QUANTUM COMPUTING8
TO
DA
Y1950 1960 1980 1990 20201970 2000 2010
2005: Web 2.0
Quantum
1964: System/360
Server/Host
1969: ARPANET
1990: System/390
1991: Public Internet
1994: Amazon
1977: PC
1972: SAP
1999: Salesforce.com
2006: AWS
2008: iPhone
1997: Big Data 1999: IoT, M2M
Public Cloud Mainstream
2010: Sales of PC Peak
2010: Self-driving Car
2007: IBM Deep Blue
AI
2014, IDC: 4.4 Zettabytes of Data
Technology waves …
Industries are seeing the transformational effects of “combinations” of technology waves
Copyright © 2019 Accenture. All rights reserved.
Technology to enable people to change processes and drive value –
Intelligent processes, enabled by digital technology, create A cycle of constant improvement driven by continuous feedback:
WHAT IS DIGITAL?
7
Transform data into insights through the use of analytics. Combine output with dynamic scheduling tools to enable agile operations.
Mine to market visualisation of the entire value chain. Process optimisation by putting the right information in the right hands at the right time. Value generated through better decision making – quicker.
Create a virtual environment to simulate, run, test and predict scenario’s across multiple time horizons. Understand the risk or opportunity. System recommends the next best action based on peak value across the length of the value chain.
Automate workflows and get the decision to the right place. Should a human be the barrier to value generation a business case is merited to automate a process or asset.
How will be interact with our data and how will our data interact back? Will we have a conversation with the data? How will quantum computing power change the way we use data?
VISUALISATION& ALERTS
ANALYTICS & DYNAMICSCHEDULING
DIGITALTWIN & NEXT BEST ACTION
INTEGRATEDAUTOMATION
COGNITIVEOPERATION
Copyright © 2019 Accenture. All rights reserved.
MINING OPERATIONS DASHBOARDUbiquitous information available in the operation or office that delivers a real-time holistic view of mining operations to visualize metrics, KPIs, alerts and analytics to decisions makers and the boardroom. Customised notifications & alerts per user
VIDEO ANALYTICSReal Time Integration with IP based cameras and CISCO VSOM server for RTSP streaming of video. Analytics to track safety and production procedures in the pit and processing plant with alerts to key supervisors and mangers
SAFETY AND FATIGUE MONITORINGReal-Time predictive analytics to monitor haul truck operators potential fatigue events and alert supervisors of potential fatigue events.
HEAVY EQUIPMENTTrucks, Shovels, Drills, Dozers, LoadersReal Time Integration with Heavy Equipment monitoring systems to track and analyze asset performance, GPs, maintenance and utilization with real-time alerting system designed to assist with root cause analysis, automated and user generated actions for faster problem resolutions.
CONNECTED WORKERSensors, communication devices, smart vest, gloves etc., control access to site and monitor to health, location, productivity of workers and their environment
NEXT BEST ACTIONUnderstand the next best course of action the whole operation should take in relation to present and predicted conditions and the critical
WEATHER MONITORINGIntegrates with weather monitoring system to alert workers of inclement weather with subsequent actions and updates to plan
PREDICTIVE MAINTENANCEReal Time analytics to drive effective asset utilization by shift, based on short term plans, lower operation costs and maintenance costs without compromising production targets.
MINE TO MARKET MINERAL CHARACTERIZATIONUse the “best information available” to understand the flow of material from mine to market. Inventory Accounting, 3D stockpile visualization and bucket by bucket analysis of material communicated to all operators and machines involved in the mining and processing or ore.
AUTOMATED TRAIN AND SHIP LOADINGMaximize the load in each wagon through radar and integrated automation solutions
EDW, SHAREPOINT, TELEMETRYReal Time Integration with business systems to aggregate multiple sources of data for real-time analytics and decision making.
CRUSHING / PROCESSING / SMELTING / REFININGAdvanced Process Control of processes aligned to divergences in plan and requirements from up and downstream processes. Maximize recovery and throughput of material from each process in line with another to increase value through reduced wastage, double handling and lack of line of sight from mine to market
INDUSTRIAL IOT SECURITYComprehensive set of security controls to enable communication and transmission of data
DIGITAL POC’S
SLOPE MONITORINGIntegrates with slope monitoring systems such as IBIS from Seeing Machines to drive real time alerts and analytics.
Copyright © 2019 Accenture. All rights reserved. 8
ONE SOURCE OF THE TRUTH
• Create foundational digital platform
• Gain insights into data through visualization and alerting
• Enable people, build trust in the system through agile delivery
• Create “pull” from the business to increase usage
• Reorder traditional processes
• Start the digitalization process
DIGITALIZE KNOWLEDGE
• Manually capture new actions and processes based on real time data
• Set up regular clinic with end users
• Run trend analysis on alerts and model key data sets
• Capture value/impact of decisions
• Feedback to business through Steering Committee regularly
• Create decision matrix: users can digitally record actions/outcomes
• Daily retrospective of shift
• Empower users to determine best practice
PROCESS AUTOMATION
• Capture workflows, actions and impact
• Automate elements of process such as reporting and delivery of diagnostics/alert trend analysis cross-discipline
• Digital Twin created
• Key capacity opportunities identified
• Scenario Modelling on rate determining steps
• Run total system optimization; dynamic constraints
NEXT BEST ACTION
• System identifies pattern in actions based on data
• System recommends appropriate and optimal action and expected impact to users
• Users still select appropriate/best action from matrix
• System continues to learn
• Upskill workforce to generate knowledge and insights to inform Data Scientists/Engineers
AUTOMATED DECISIONS
• Self-learning, autonomous systems designed to Sense, Comprehend, Act, and Learn, mimicking human behaviour [computer vision, NLP, machine learning, knowledge representation and reasoning]
JOURNEY TO AUTOMATED DECISIONS
Platforms & Automation Instrumentation
Rules Based Judgement Based
Tact
ical
Tran
sfo
rmat
ion
al
ProgrammedStrictly Controlled
Contained
Self-LearningAutonomousUnbounded
BU
SIN
ESS
IMP
AC
T/O
UTC
OM
E
Copyright © 2019 Accenture. All rights reserved.
PIVOT TO FOCUS BUSINESS ON VALUE GENERATION
Operational Users
Office Users
Executive Users
Vis
ual
isat
ion
(sin
gle
pan
e o
f gl
ass
min
imis
ing
dis
rup
tio
n t
o e
nd
use
rs)
Applications & Infrastructure- IT & OT applications- Available for all – strategy to reduce number and consolidate- Connectivity infrastructure- Hosting, Compute, Storage
Governance- Cyber Security- Master data management- Data Architecture
Intelligence- Application of data analytics to drive insights- Machine Learning
Partners - Strategy- Analytics / Data- Change Management
Domains Strategy C suiteDigital TransformationEnd UsersValue
Financial
Safety
Productivity
Smart sensors- IIOT devices- PLC’s - Control of smart sensors
Social
Integrated Operations
TeamCreating the link between the
business and end user.Focus on driving value
Company owned 3rd Party support
Copyright © 2019 Accenture. All rights reserved.
THE DIGITAL TRANSFORMATION JOURNEY
Mining companies are facing challenges to transform their business to fully unlock the potential value of their digital POCs at scale.
Digital POCs
Industry Forces (e.g. Demand and Price volatility)
Regulatory & Compliance Pressure (e.g. Safety, environment)
Market Trends (e.g. new age workforce, tech advancements)
C Suite Mandate (e.g. Digital, Op Excellence, Ind 4.0)
“Drivers & market forces”
‘The catalysts for change’
VALUE
SCALE
STRATEGY & VISION
OPERATING MODEL
INNOVATION PROCESS
TECHNOLOGY CAPABILITY
PEOPLE & CULTURE
STRATEGIC MISALIGNMENT
UNCLEAR ROADMAP
FUNDING DIFFICULTIES
FRAGMENTED BUSINESS
UNCOORDINATED EFFORTS &
ECOSYSTEM
LONG CYCLE TIMES
INCONSISTENT INNOVATION
UNCLEAR SPONSORSHIP
LOW INTEGRATION
SECURITY RISKS
TECH SKILLS MISMATCH
RESOURCING GAPS
SCARCITY MINDSET
LOW DIGITAL FLUENCY
THE TRANSFORMATION CHASM
How to navigate the ‘Chasm’ ?
Focusing on people & core value chain
Creating a frictionless business & ecosystem
Layering legacy technology with the new
Transforming the culture & ways of working
Embedding innovation & encouraging change
Often isolated, limited in value, scale and
adoption
Copyright © 2019 Accenture. All rights reserved.
Austmine Webinar: Getting Ahead In the
Digital Age of Mining
Roy Pater
Feb 2019
A 1% productivity improvement = up to a 3% profit improvement
So consider…
Something to think about
13Confidential
*Base calculation
$1.4mLost when underloading a truck by 3%
$42,000Gained by loading 1
additional tonne on each
carriage per yearapprox
approx
14Confidential
Decision-Making using Digitisation
What does Payload Monitoring Technology deliver?
Real-time, actionable information
Lowers operational & maintenance costs
Sustainable improvement in production
Icons sourced: Iconfinder.com
Result is consistent &
predictable truck payloads
What does better Mine Compliance (Dig to Plan) mean for operations?
– Real time information for decision making
• Stops over and under digging
– Enables Upstream mining = real-time short interval control closed loop feedback
• Quicker adjustments based on what is happening in the mine
• Higher ability to remain on target
15Confidential
Decision-Making using Digitisation
Mine Process
16Confidential
What Digitisation Achieves
Bauxite Mine – Australia
Underloads Compliant Trucks
Minor Overloads
Post Blind 7% 88% 4%
Blind Trial 11% 81% 7%
Improvement 4% 8% 3%
Coal Mine – South Africa
Copper Mine – Chile
Trucks: 32.8% Overloaded & 26.6% Underloaded Trucks: 11.7 % Overloaded & 5.8% Underloaded
17Confidential
Where do we need to get to?
● Provision of a single on board platform for a shared and integrated
infrastructure with ’apps’ to run on this
● i.e: One phone with many apps not a phone per app
● One platform and the mine selects the best apps to solve specific
challenges
● Needs a robust network connecting the mine to the Ops Centre
GuidanceFMS PayloadGuided Spotting
SafetyTooth
Detect
Machine Health
Shared On-Board PlatformOperations
Center
Platform
18Confidential
MineWare Installations
330SYSTEMS Installed
77MINE SITES
Number of mine sites
we operate in
19© 2019 The MathWorks, Inc.
Getting Ahead in the Digital Age of MiningImpacts of artificial intelligence on the mining industry.
By Sam Oliver
Technical Consultant
MathWorks
20
21
2015https://www.eetimes.com/document.asp?doc_id=1325712#
Artificial Intelligence (AI) vs Human
22
AI will result in safer operations
23
AI will result in increased efficiency
24
AI will result in less downtime
25
Source: Real Truth of Artificial Intelligence by Whit Andrews
Presented at Gartner Data & Analytics Summit 2018
50% Planning4% Deploying
26
What is AI?
27
Artificial Intelligence
The capability of a machine to imitate
intelligent human behavior
28
Artificial Intelligence
The capability of a machine to match or exceed
intelligent human behavior
29
Artificial Intelligence Today
The capability of a machine to match or exceed
intelligent human behavior
by training a machine to learn the desired behavior
30
There are two ways to get a computer to do what you want
Traditional Programming
COMPUTER
Program
Output
Data
31
There are two ways to get a computer to do what you want
Machine Learning
COMPUTERProgram
Output
Data
32
There are two ways to get a computer to do what you want
Machine Learning
COMPUTERModel
Output
Data
Artificial Intelligence Machine LearningDeep
Learning
33
With MATLAB and Simulink, you ARE ready for AI!
DevelopAnalyze DataAccess Data Deploy
Data
Model
Output
AI model
Modeling &
simulation
Algorithm
development
34
Develop
AI model
Modeling &
simulation
Algorithm
development
With MATLAB and Simulink, you ARE ready for AI!
Data
exploration
Preprocessing
Analyze Data
Domain-specific
algorithms
Sensors
Files
Access Data
Databases
Deploy
35
With MATLAB and Simulink, you ARE ready for AI!
Develop
Data
exploration
Preprocessing
Analyze Data
Domain-specific
algorithms
Sensors
Files
Access Data
Databases
Desktop apps
Enterprise
systems
Deploy
Embedded
devices
AI model
Modeling &
simulation
Algorithm
development
MATLAB makes AI easy and accessible for
Engineers, and Scientists
36
Mikusa Tunnel
Japan
Safe tunnel drilling with deep learning
Obayashi Corporation
Challenge
• Geologists assess seven different metrics
• Can take hours to analyze one site
• Critical shortage of geologists
Solution
• Use deep learning to automatically
recognize metrics based on images
• On-site evaluators decide with support
from deep learning
37
Use deep learning to identify features automatically
Feature extraction Classification
Safe
Warning
Rock fall
Data
Machine Learning Workflow
Safe
Warning
Rock fall
Deep neural network
95%
3%
2%
..
.…
Data
Deep Learning Workflow
38
Safe heavy equipment operation
Challenge
Develop autonomous,
remote operation, and
driver assistance systems
to remove people from
harsh and unsafe
environments
39
Training a Machine Vision is time consuming
41
Optimise Operations of Locomotives
Challenge
Optimise train speed profiles to reduce
fuel consumption, reduce travel times,
and equipment wear.
42
43
Iron Ore Sample
Challenge
Optimise value extracted from Iron
Ore sample.
44
45
More Efficient Copper Flotation Plant Operation
Challenge
Optimise Copper Recovery of the
Telfer operations.
46
IT Systems Smart assets OT Infrastructure
DataIngestion
LocalCommunications
Long-RangeCommunications
EdgeManagement
Edge systems
Integration
What is a Digital Twin in Operation?
• Faithful, up-to-date representation of asset (current, past, or future state)
• Composite of modelled behaviors using any number of modeling approaches –
data or physics. Can be hierarchical and include multiple levels of fidelity.
47
Production System
Applying Digital Twin to Copper Processing
Edge Device Analytics
DevelopmentMATLAB
MATLAB Production Server
MATLA
B
Analyti
cs
MATLAB
Compiler
SDK
• Algorithm
Developers
• Metallurgists
• Data Scientist
Storag
e
LayerDigital Twin of
Flotation Plant
Plant operators▪ Reduction of acid
soluble copper
▪ Timely maintenance
of sensors
▪ Notification of below-
average performance
48
Challenge
Reduce energy consumption of
Cooling Towers and control variation
of chilled water outlet temperature
Cooling towers at Tata Steel
Optimise Cooling Tower’s Energy Consumption
49
Customer Example: TATA Steel optimizes cooling tower
operation via digital twin
Challenge • High energy consumption in cooling tower
• Changing weather conditions caused substantial variation
in operation
Solution
• Mass and energy balance equations modeled in MATLAB
• Model optimized and parameters calibrated with plant data
• MPC controller implemented
Results
▪ Savings of $100,000 per CT per year
▪ Variation in outlet water temperature reduced
Link to TATA Steel’s talk
Water cooling tower for the blast furnace
Effect of Murphree efficiency on number of stageshttp://www.digitalcreed.in/tata-steel/
50
AI will result in
safer operations,
increased efficiency, and
less downtime
51
How will you leverage AI?
2020!?
52
With MATLAB and Simulink, you ARE ready for AI!
Develop
Data
exploration
Preprocessing
Analyze Data
Domain-specific
algorithms
Sensors
Files
Access Data
Databases
Desktop apps
Enterprise
systems
Deploy
Embedded
devices
AI model
Modeling &
simulation
Algorithm
development
MATLAB makes AI easy and accessible for
Engineers, and Scientists
Audience Q&A
Part 5 – Mine Site Connectivity: Enabling Mining’s Digital Revolution
16 April 2019
REGISTER
Analytics, Data and Security: The Changing Winds
Marco Orellana, Chief Information Officer, Codelco
Barry Elliot, VP Enterprise Accounts – Heavy Industries,
Rockwell Automation
Rob Labbe, Director Information Security, Teck
Resources