presentation to the 3rd annual optimising mine operations conference 2015
TRANSCRIPT
BENEFITS ACHIEVED AT CANADIAN MALARTIC, MALARTIC
THROUGH OPTIMIZATION OF MRO INVENTORY MANAGEMENT
OMOC, TORONTO 2015
By Robert Lamarre, B.B.A., M.A.ScOctober 8th, 2015
Optimizing Mine Operations Conference 2015
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• Canadian Malartic is one of Canada’s largest gold miners
• Agnico and Yamana operates the Canadian Malartic gold mine in
Malartic, Quebec, and continues its exploration work in Canada and
Mexico
• One of the biggest gold reserves in production in Canada
• The first gold bar was poured on April 13, 2011 and commercial
production began in May 2011
• Proven and Probable Reserves of 9.371 million ounces of gold
OMOC, TORONTO 2015
Who is Canadian Malartic Mine?
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• Canadian Malartic Mine faces the same challenges as all industial
organizations trying to manage spare parts
• First objective is to maintain continuity of operations
• Intermittent demand
• Critical parts
• Large number of multi-references families
• Difficulty to forecast demand
• Variable lead times
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The challenges of inventory optimization
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• Manual Min-Max on more than 17,000 items
• The operations context is evolving
• Maintenance requirements in continual evolution
• Nobody dedicated to inventory analysis
• Not enough service on critical spares
• Not enough service on A items
• Too many small orders in purchasing and at receiving
• Limited use of scorecard
• No use of exception reports for inventory management
Portrait of the Situation - May 2013
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• One dedicated inventory analyst
• More than 75% of Min-Max now dynamic and calculated scientifically by IMAFS
• Management of inventory by product family and product class
• Bigger focus on service for critical parts and A items
• Constant follow up of inventory management scorecard
• Continual use of exception reports for inventory management
Major changes since May 2013
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Some results
Family Month ClassA C D S
Consumable May-13 91.7% 95.2% 82.4% 90.5%Consumable Mar-14 97.0% 98.6% 98.6% 97.9%
Mine/Mobile May-13 94.5% 94.9% 91.9% 94.2%Mine/Mobile Mar-14 99.2% 97.8% 96.2% 96.0%
Plant May-13 95.8% 93.5% 97.0% 93.5%Plant Mar-14 98.7% 97.6% 99.7% 97.8%
80% Reduction of backorders on A items
45% Reduction of backorders on S item
Globally, the product availability has increase by 3,5% from 93% with a 5% increase on critical items
Evolution of service
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Some results
Mine/Mobile was the first family implemented Results in about a year
Evolution of inventory and service for Mine/Mobile
14 ju
in 2013
10 ju
illet 2
013
9 aoû
t 201
3
9 sep
tembr
e 2013
7 octo
bre 2
013
7 nov
embre 201
3
9 déc
embre 2
013
8 jan
vier 2
014
11 fé
vrier 2
014
Mine/MobileClass A
+ 5%
Class S+2%- 24,5%
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Identify product family and demand stream
Criticalor
not
Stockor
non stock
New
Inactives (no usage for X
months)
A B C DBased on Hits or
usage value
Reparableor
not
Obsoleteor
not
Cla
sses
OMOC, TORONTO 2015
Parts classification - Process
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Measures existing levels
Allows service goals on part’ criticality level
Allows service goals by class, by family, by warehouse
Safety stock set in line with service goals
Simulations to measure impact of service goals variations
Dashboard to track service results
Tools to take corrective actions
Managing serviceCanadian Malartic Mine now tracks parts availability compared to
goals
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Management
by demand
flows
Determining
seasonality
Intermittent
demand
Automatic
data
cleansing on
extreme data
Better data for accurate forecasts
Managing demand
At Canadian Malartic Mine, we have 2 demand flow, 1% of items are
seasonal, 87% of items are intermittent
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Good solid statistical forecasts
Forecasting methods that account for
demand trends, seasonality and
intermittence
Best fit by item
Possibility of manual
adjustments
Filters & alerts
Canadian Malartic Mine is now using forecasted demand to dynamically adjust Min-Max
Better forecasts = better service + less stock
Forecasting demand
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Bad lead time information result in stock outs or surplus stock
Canadian Malartic Mine now have a closer management of both vendor lead times and internal lead times
Lead time
Dynamic calculation
By vendor and transport mode
Cleansing of extreme delays
Internal lead time managed by components
Possibility of manual control
Compare real lead time with
vendor promises
Managing lead times
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OMOC, TORONTO 2015
$Ordering Stocking costs costs
DATA BASE ERP or CMMS
Calculation
SSLead time
MinMax
ForecastingLot sizes
FINAL PARAMETERS
Service objectives per class /
family/ warehouse
AdjustmentsSimulation
Optimizing inventory parameters
Canadian Malartic Mine now uses IMAFS’ calculated Min-Max on 75% of items
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Key Performance Indicators
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• Parts availability up by 3,5% overall and 5% on critical items
• More availability of production equipment’s
• Inventory of items dynamically controlled by IMAFS went down by 15% overall with 24% on parts for mobile equipment, the first product family that Canadian Malartic Mine implemented
• A complete set of KPI’s with the tools to manage service
Key results at Canadian Malartic Mine
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Thank you
Questions?