Benefits achieved at Osisko Mining Corp. through optimization inventory management

BENEFITS ACHIEVED AT OSISKO MINING CORPORATION,

MALARTIC THROUGH OPTIMIZATION OF INVENTORY

MANAGEMENT

CIM 2014 - VANCOUVER CONVENTION

By Robert Lamarre, B.B.A., M.A.Sc. &

Roch Trépanier

May 13th, 2014

CIM Convention 2014

1

Agenda

Presentation of Osisko Mining Corporation

Portrait of the situation

Challenges

Results

2 CIM 2014 - VANCOUVER CONVENTION

• Osisko Mining Corporation is a mid-tier gold producer

• Osisko 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

CIM 2014 - VANCOUVER CONVENTION 3

Who is OSISKO?

• Osisko 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

CIM 2014 - VANCOUVER CONVENTION 4

The challenges of inventory optimization


• 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

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Portrait of the Situation - May 2013


• 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 Class

A 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%

Globally, the product availability has increase by 3,5% from 93%

with a 5% increase on critical items

Evolution of service

7


Some results

Globally, the inventory went up by 6,9%.

The inventory of items manually controlled went up by 14,2%.

The inventory of items dynamically controlled went down by 7,5%.

Evolution of inventory for all items

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Evolution of inventory for items

dynamically controlled

Evolution of inventory for items

manually controlled


Some results

Mine/Mobile was the first family implemented

Results in about a year

Evolution of inventory and service for Mine/Mobile

9

Mine/Mobile Class A

+ 5%

Class S

+2% - 24,5%

Identify product family and demand stream

Critical or

not

Stock or

non stock

New

Inactives (no usage for X

months)

A B C D Based on Hits or

usage value

Reparable or

not

Obsolete or

not

Cla

sse

s


Parts classification - Process

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Osisko parts

classification for

mobile equipment’s

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Parts classification - Process

• The reason we keep inventory

• Analyzing our performance is important

• Ability to supply the parts when needed

• Ability to reduce downtime on equipment’s

• Estimate parts availability

• Service goals to be determined for each product class, each

product family and each warehouse

• The system has to adjust Min-Max to service goals

• 80 – 20 Rule -> Focus on important items


Managing service

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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 service Osisko now tracks parts availability compared to goals

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• Historical Information

• More data = more accurate you can be

• Demand flows regular, project, planned maintenance

• Demand patterns: planned or emergencies

• Regular demand or intermittent demand

• Manage on demand data; not shipping


Managing demand

Osisko uses the automatic data cleansing and have effective

tools to manage parts with intermittent demand

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Better data for accurate forecasts

Managing demand

At Osisko, 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

Osisko is now using forecasted demand to dynamically adjust Min-Max

Better forecasts = better service + less stock

Forecasting demand

16


Bad lead time information result in stock outs or surplus stock

Osisko 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

17


$

Ordering Stocking

costs costs

DATA BASE ERP or CMMS

Calculation

SS Lead time Min Max Forecasting

Lot sizes

FINAL PARAMETERS

Service objectives per class /

family/ warehouse

Adjustments Simulation

Optimizing inventory parameters

Osisko 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 8%

overall with 24% on parts for mobile equipment, the first product family

that Osisko implemented

• Improvements in maintenance effectiveness related to service

improvements

• Improvements in Supply chain effectiveness related to a reduction in the

number of orders to vendors

• A complete toll box to continue inventory reduction with high service

levels. There is still a potential to reduce inventory by 20%

• A complete set of KPI’s with the tools to manage service


Key results at OSISKO

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Thank you

Questions?

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Technology

Benefits achieved at Osisko Mining Corp. through optimization inventory management