This document discusses how mining organizations can increase production through improved spare parts availability. It provides 12 elements for effective inventory management in mining operations, including classifying parts based on criticality and demand patterns. Forecasting demand for spare parts is challenging due to intermittent demand for many parts. Managing lead times is also important given the long and variable lead times common in mining supply chains. Implementing best practices for inventory management, such as separating demand types and improving forecasting accuracy, can help mining organizations reduce stockouts by over 80% while decreasing inventory levels by 20% or more.

1. INCREASE PRODUCTION THROUGH IMPROVED SPARE PARTS AVAILABILITY
Robert Lamarre
Gestion Conseil Robert Lamarre & Associés (GCRL) and IMAFS Inc.
937, Boissy Street, St-Lambert, Quebec, Canada J4R 1K1
info@imafs.com

2. INCREASE PRODUCTION THROUGH IMPROVED SPARE PARTS AVAILABILITY
ABSTRACT
In today’ environment, the availability of production equipment is a must to increase throughput
and profits. A number of mining organizations around the world have identified that having a good level of
availability of spare parts has a direct impact on this goal. Fortunately, having less production equipments
immobilized by a lack of spare parts does not equate having more cash tied up in spare parts. Advance
operations research has shown a number of avenues to increase equipment availability while reducing total
investment in stock. The presentation will presents key changes in inventory management that can result in
better service with less stock. We have applied our approaches successfully in start-up mining projects, in
mature projects and in end of life mining operations. We will illustrate with examples that come from our
work with more than 30 mine sites around the world.
The presentation will be conducted by Mr. Robert Lamarre, who has a Master degree in
Operations research from Waterloo University. He is the president of Robert Lamarre & Associates, a firm
that is specialized in Supply Chain Management, especially in spare parts environment. He is also
president of IMAFS Inc, a solution provider for maintenance parts optimization.
KEYWORDS
Inventory Management, Spare parts, Mine Production Equipment, Lead time, KPI, Demand forecasts,
Criticality of parts, Min-Max, Material management, Parts classification
INTRODUCTION
Importance of Materials Management in the Mining Industry
Production throughput has always been the goal and the most important performance indicator in
the mining world. Production equipment represents huge investments. There has been a lot of focus on
asset management and asset utilization. However, it is only during the last decade that the mining industry
has taken an interest in exploiting Materials Management as a very important key to reaching that goal.
Mining organizations are now recognizing that inventory management of spare parts and
maintenance materials is a key component to the success of their operations. They want to ensure the right
part is on hand, in the right quantity and at the right time. What would be the impact on your bottom line if
your stockouts could be cut down by more than 80%? How much productivity would you gain if your
maintenance crew didn’t have to wait for spare parts to do a job? What would be the impacts if 80% of
your missing parts’ emergencies were eliminated? How much can be saved by cutting down by 80% your
expediting activities?
By focusing on materials inventory management; some of our clients have experienced a decrease
of equipment downtime by as much as 25% due to the absence of materials and have increased their parts
availability from 75% to 94%. The resulting increase in profits represented several millions of dollars.
Rigorous and scientific approaches to Inventory Management have allowed them to achieve these
results while reducing investments in stock by 20% to 35%. This has a major impact on cash flow in a

3. period when it is difficult to obtain capital investment to conduct valuable projects in exploration or
expansions.
METHODOLOGY
Unique complexities and challenges of inventory optimization in a mining environment
Managing spare parts inventory is very different from other types of inventories. The key to
succeed is to understand these differences and use the appropriate tools to achieve your inventory and
throughput goals. The major differences to be considered are:
• The criticality of parts: Organizations must evaluate the probability of failure of a part against the
potential impacts on production of not having the part in stock when needed. This is more important
than its demand history in frequency or value.
• More than 80% of parts in the mining industry have intermittent demand.
• There are various forms of demand for a unique spare part. The demand can be split in various flows:
unplanned repairs, projects and planned maintenance activities. Effective Inventory Management has
to manage these forms of demand separately.
• Lead times are long and often unreliable due to isolated geographical sites.
• Very often the transport mode to obtain the part varies from one order to the next.
• The number of spare parts needed to support maintenance and operations often exceeds 25,000.
• There are big investments in inventories, yet parts’ availability is often considered inadequate.
• Typically, the people and systems involved in maintenance planning are not linked with the inventory
management and replenishment systems or departments.
• There are a lot of slow moving and surplus stock.
• Mines and mills have their unique life cycle. There are different strategies to use for each operational
phase (start-up, maturity and closing).
As you can see, the differences are many and the tools needed to manage them must be adapted.
One must consider this when choosing a ERP, EAM or CMMS system. It is our experience that most of
the out-of the-box solutions are not effective at managing spare parts. They do not have the required
flexibility to account for parts criticality, to develop a parts classification adapted to a maintenance
environment, to manage the complexity of lead times encountered on mining sites, to account for a
maintenance plan or to assess inventory requirements in line with service objectives. Organizations in the
mining industry require that flexibility and they must be able to override parameters manually when
exceptions are identified.
We will present 12 elements that have helped mining organizations turn their Inventory
Management into a profit machine instead of being saddled with a burden.
1. Parts Classification: All parts are not created equal
Parts classification is your building block that will help you prioritize your actions and your key
performance indicators. Unfortunately, the traditional way of doing ABC classification is not optimal. All
parts are not created equal and there is no unique process in inventory management that fits all parts. The
very first key in inventory optimization is to classify the parts in relation to both their relative importance
on operations and on the inventory strategies needed to manage the parts. Special classes can be used to
identify and manage obsolete inventory or to repair critical parts, for example.

4. When establishing a part’s importance, it is good to know what the part is being used for. In many
mining operations, parts are segregated according to their use may it be for the maintenance of mobile
equipments, mill operations, underground, consumables or for the living quarters. Once the product
families are properly defined, we then proceed to analyze the part’s importance.
We have found it very useful to first identify obsolete parts. We assign a class O (for Obsolete) to
these items. This helps stop further purchases of these parts by ensuring that we set the inventory
parameters to zero for all O items. Disposal procedures can therefore be initiated and we can thus
determine the amount of effort required to manage these parts.
We must then identify parts criticality. This is no simple matter but it can be made easier by using
the right tools. We have to establish valid and clear criteria that are easy to understand and to
communicate in order to establish parts criticality. We recommend establishing a grid for parts criticality
with a scale from 1 to 9, nine being most critical and one being not critical. It is advisable to translate in
dollars the impact of a stockout within the normal lead time.
At Omai Gold Mines in Guyana, they have established such a criticality index. For example, when
a stockout of an item generates a loss of revenue exceeding $50,000, it would have a criticality ratio of 8
on their scale. They then reviewed the criticality of all the 2,500 parts that had been identified as critical at
the moment of their creation. After review, less than 500 parts of that list remained critical and were
classified P (protected) and S (critical). The amount of parts previously carried in inventory considered as
not truly critical exceeded 4 million dollars. They were also able to identify parts that were truly critical but
were not classified as such. The overall savings related to this exercise alone were in excess of 1 million
dollars.
At Areva Katco Mine in Kazakhstan, the company was able to determine there were significant
losses in production because the critical items were not identified and manage properly.
The next step would be to identify the repairable parts. Several mines sites (like Osisko and
Aurizon in Northern Quebec) have identified repairable parts as class R. This is considered best practice as
the inventory management processes for repairable parts are very different in nature than those for new
parts.
Once repairable parts are identified, we must determine the parts that are bought on demand only.
It is a good practice to track the activities on these items although you do not want to keep the part in stock.
Barrick Gold uses the class X to identify the non-stock parts. It provides the buyer with the required
visibility needed to make appropriate sourcing decisions when dealing with minimum buys or standard
packs. It will also provide visibility into inventory levels for these items and invite people to find ways to
reduce them.
New parts where we have less than a year of historical demand need to be properly identified
(class N). Since the history by definition is unreliable for these items, they require additional attention and
more manual interventions. Most mining companies that work with product classification are identifying
their new parts separately.
Once all of these steps have been finalized, one can complete the product ABC classification. It is
recommended to do a classification based on the total number of times a part has been requisitioned over
the last year. In mining sites, we generally find that less than 15% of the parts account for more than 75%
of the total number of demands. These are your class A items (Figure 1).

5. Figure 1: Distribution of items in ABC classification according to percentage of hits
We can proceed in doing the next classification based on dollar of usage and we will reclassify C
and D (intermittent demand) with high dollar values to B.
Companies such as Osisko, Areva, Aur Resources, Richmont Mines and Xstrata Zinc have all
used an ABC classification that reflects the frequency and the dollar of usage.
2. Better manage the service you provide for operations and maintenance with your stock
Most mining companies we have visited did not measure the fill rate or product availability that
they were providing operations and maintenance.
The reason we keep inventory is to support operations and maintenance. In analyzing our
performance, it is essential to have measures of our ability to provide service. One of the first steps in
analyzing inventory management is to determine our ability to supply the parts when needed. We analyze
parts availability by product class per warehouse.
A quick way to get an estimate of parts availability for a given item group is to identify the parts
with zero inventory within the group. You look at the number of times these parts were used over the past
year. The proportion you get when you compare the number of usages on the items with zero inventory
versus the total number of demands for the entire product group gives you a percentage that corresponds to
the probability of servicing a demand for any item in that product group. This is your starting point.
This exercise has provided results that surprised Materials Managers in a majority of the mines we
have visited. On the other hand, the results were very much in line with the service perceived by their users.
Afterwards, you want to establish service goals required for each product class, each product
family and each warehouse. From there, you need a system that can calculate safety stock in relation to
service objectives. You also want to continually measure your performance in comparison to your
objectives. Xstrata in Matagami is in the process of implementing safety stock in line with their service
objectives per product class, per product family and per site.
The interesting point here is that in most mining sites where we have worked, we have
demonstrated that you can eliminate 80% of the stockout situations while reducing inventory by more than
20%. We find that most customers do not readjust their MINs when their usage is trending down. They
react faster to increases in demand than to decreases in most cases.
Aurizon Mines has seen major improvements in parts availability in only three months after
implementation of a best of breed inventory management system.

6. 3. Demand history has to be manipulated and managed to improve inventory management
To do a good job in inventory management, you need historical information that is representative
of the future usage. Ideally, you want to segregate your demand in demand flows. Demands to satisfy
projects (planned major maintenances) should be in a separate flow. Let’s say that you had a project last
year that required 100 parts per month for 3 months and your average demand outside project time is 20
units per month. If you calculate your average demand last year, without removing project data, you would
plan for 40 units per month which is misleading.
Similarly, you want a separate demand flow for parts used on planned maintenance versus
emergencies. It is best practice to plan out your maintenance work three weeks in advance and the
planning horizon for major overhauls should be greater than the parts lead time. The parts demand
generated from these planned work orders are called planned demands. You simply buy the components in
advance.
Emergencies are not planned and it is for the emergencies that safety stock is needed. Ideally, you
would like to have access to 3 years of historical demand, if it exists. The more data you will have, the
more accurate you can be. Now, you want your data to reflect demand. If a part was requested in May but
delivered in June, you would like the demand to appear in May.
ArcelorMittal in Mont-Wright and Port-Cartier, Osisko and Aurizon Mines in Abitibi are amongst
the few mining organizations equipped to manage the various demand flows separately. This is definitively
part of the Best Practices.
Most companies use the standard deviation of the history to determine their safety stock levels
instead of forecasting their demand and using the accuracy of the forecast to determine it. The more
accurate your forecast is, the less you need safety stock to ensure service. Since your history needs to be
representative of your future demand, we have found that removing extreme data from the history helps
improve your ability to generate forecasts. In every one of the sites where we have conducted analyses, we
have proven that automatically removing extreme data normally improves forecast accuracy by 10% to
20%.
It is also very useful to analyze demand patterns. You have to account for seasonality if it exists.
You have to account for growth or decline in the demand. You will not treat items with intermittent
demand the same way you treat items with regular demand.
4. Forecasting spare parts’ demand is a challenge in itself
One of the biggest challenges in managing inventory for maintenance is forecasting. Considering
its benefits, it was surprising not to find demand planners or forecasting tools implemented in the mining
industry. It is not easy to predict what part will be needed in advance but with the right tools, it can be done.
The reality is simple: there is no human being that can forecast future requirements of 25,000
parts on a month by month basis. It is also true that there isn’t one magic mathematical formula that can
generate accurate forecasts for all parts.
The good news is that with computers today, we can generate thousand of variations of
forecasting formulas and parameters and use the best fit logic to tells us which forecasting formula and
parameter should be used in order to generate future monthly forecasts. The system can automatically
select for each individual item which of the thousands of approaches is needed to generate forecasts that
would provide the best results for the last six months, in comparison to what we know really happens.
It is our experience that dependence on a machine to forecast the future is very helpful but can be
very misleading also. We need human intelligence to adapt the forecast. The forecasted requirements

7. should also include the information that we have on ongoing projects or planned maintenance. The
maintenance planner may know that a production machine has been decommissioned and spare parts for it
are no longer required even if this is not reflected in the product history yet. Usage and Operations
meetings help address such issues.
It is also important to monitor forecast accuracy. You want somebody to analyze the items that are
very difficult to forecast and where the forecast accuracy is very low, especially for expensive items.
Filters and alerts are used to identify such situations. These are the items where you would need more
human input to improve forecast accuracy.
A key ingredient that renders the forecast a major challenge in a mining environment is the
intermittent demand. Studies conducted at Cambior, Xstata, Rio Tinto and at most other mine sites shows
that 80% of the items do not have any demand for most months and, when there is demand, it is erratic.
5. Lead times need to be managed in the mining industry
Long and variable lead times are a given in most mining operations. This is even more reason to
manage them closely. We have found that in the majority of mining sites there are serious opportunities to
improve external and internal lead time management.
It is important to measure and manage the elements of internal lead times. For example, we had
identified for one of our clients that the internal lead time had increased from 1 to 2 days on an average of
10 days over the course of the last year. The amount of inventory needed to maintain service to the users
exceeded one million dollars.
You want your inventory management to be based on calculated lead times that reflects the reality.
To do this, we measure the actual lead times for each individual item by vendor and by transport mode. For
example, if you sometime fly the part in and use boats in other instances, calculating the average lead time
would be misleading.
Analyzing the lead times by transport mode can prove very useful. For example, we have found
that total lead time for shipments coming by air to the Areva uranium mine site in Somaïr, Niger could be
reduced by 80% by cutting back the internal processes that were in place to gain approval for the use of air
transportation. We have found with one of our other clients last year that the time to approve an air
shipment was 40 days on average. We all agree that 40 days to approve to fly a part in just doesn’t help
reduce equipment downtime.
Cleansing your reception history is necessary. Extreme values like an emergency with same-day
delivery must be removed or you will underestimate your lead time. Once your calculation is complete, it
is very interesting to compare calculated lead time with the promises from your vendors. You can use the
information as part of your scorecard.
6. Inventory parameters have to be set dynamically using scientific calculations and common sense
There are still too many mining organizations that depend on manual Min-Max to manage stock.
How can one expect an individual or two to set optimal inventory parameters for more than 25,000 parts
when the demand and lead time fluctuate and there is continuous pressure internally to rush after parts?
You need tools to scientifically calculate your inventory parameters like safety stock, Min and Max. To
pick the right tool, you must first understand what is needed to optimize your parameters.
Safety stock has to be calculated to provide the service level goals for each class of item, each
product family and each warehouse. Safety stock needs to be adjusted to reflect true calculated lead times.
It also has to be adjusted to cover for demand variability and our ability to forecast the demand (Figure 2).
If we can accurately forecast future demand, we do not need as much safety stock. If on the other hand, we

8. have difficulty forecasting, we need more safety stock to protect the company against demand that is
greater than the forecast during the lead time interval.
Figure 2: Impact of demand variations on inventory
Min-Max have to be adjusted dynamically at least once every month to reflect variations in
service goals, in lead times and in demand. The Min is set to reflect the calculated safety stock and the
forecasted demand during the total calculated lead time (both internal and external).
Once you have determined your Min, it will be used with your lot size demand to calculate your
Max. Ideally the lot sizes are established in time units (eg 1,5 months of stock) that are then adjusted to
reflect forecasted demand during the coming period. This allows the Min and the Max to adjust itself
according to trends, seasonality and intermittency of the demand.
Finally, you need to identify the regular usage multiple for each item. If you always use 3 fuses at
a time, there is no point in keeping 8 in stock. It should be in multiples of 3. Your parameters must reflect
this but keep in mind that usage multiples may vary from one machine to the other.
A majority of our clients have started to implement dynamic and scientific Min-Max. All of them
have seen improvements in parts availability with decreases of at least 25% in total stocking levels.
Cambior has experienced an inventory reduction of more than 30%. At Areva Somaïr in Niger, we
attained a decrease in inventory of 35% with significant increase in parts availability.
Scientific Min-Max calculations are a good start, but it does not replace the user’s experience.
There are valid reasons to manually adjust Min-Max. If an item is being replaced by another, you will want
to adjust its Min-Max. If you change or eliminate production equipment, the parts normally kept to
maintain it will see a decrease if not a total stop in their demand. Your system must allow for such manual
adjustments, ideally with tracking functionality.
In such a context with scientific dynamic Min-Max, the inventory analyst can focus on exceptions
and do only a few manual changes. This is a better use of the inventory analyst.

9. 7. Clarifying roles and responsibilities is essential to obtaining results in Inventory Management
When all these tools are introduced, it will generate important changes within the organization.
Change management is very important to succeed. Results are never achieved without a clarification of
roles and responsibilities related to the various elements of inventory management.
We often recommend shifting the responsibility of managing the Min-Max from the Maintenance
Group to the Materials Management Group. The maintenance people are responsible to identify which
parts they need (item creation), what are the forecasted requirements and what are the impacts of not
having this part (parts criticality). Materials Management is responsible for sourcing the product, managing
the lead times, gaining visibility of total demand from various operational and maintenance groups.
Materials Management employees are responsible for the management of the inventory guidelines
to be used in the scientific determination of Min-Max.
8. You need to set inventory management policies and procedures
Service goals have to be set by top management after reviewing the costs associated with various
service levels with the help of simulations. Policies will clarify how to determine parts criticality.
Management will validate parts classification criteria. The inventory management policies will clarify and
document the roles and responsibilities. Policies will also address the rules to dispose of surplus or obsolete
stock and who will be responsible in each department to ensure its success. Policies are also a good place
to document objectives.
Procedures are essential to document how the organization wants to address issues like part
creation, management of free issue stores, surplus stock processes, etc. Best of class organizations have
well documented policies and procedures related to Inventory Management as well as Procurement.
9. You need tools and people to manage surplus stock
Because of the nature of mining operations, there are a lot of slow moving and surplus stock. You
need the tools to identify such stock and you need people from Procurement, Materials Management,
Maintenance and Operations to work together with a clear action plan to dispose of surplus stock. If you do
not assign such clear responsibilities, our experience tells us that the surplus stock will still be there in the
years to come.
The management of surplus stock is even more important for phasing out activities. This has been
true for organizations like Xstrata for their Brunswick operations or for Areva for their ANC operations in
France.
10. There is no scientific and dynamic calculation of Min-Max without a good Inventory Optimization
System
We have identified above a number of basic functionalities to expect from such a system. As you
can see, a good inventory optimization system is needed to get results, the desired service level, the
targeted inventory reductions, the minimization of equipment downtime and the increase of profit and
throughput.
11. Without good Key Performance Indicators (KPIs), you will not achieve expected results
There should be no surprise when we insist on the importance of key performance indicators
related to inventory management. The first focus should be on service by measuring parts availability and
equipment downtime due to lack of parts. You also want to track inventory investment, inventory turns,
evolution of surplus stock and the accuracy of your forecasts. You also need reports on inventory

10. classification and on lead time management. You also want to know the amount of stock you need
theoretically to reach your service goals with a minimal amount of stock. This is a benchmark on how you
are doing and what the true potential for inventory reduction is exactly. It will allow you to discern if your
purchasing is in line with your inventory parameters.
12. Good exception reports help achieve expected results
You also need exception reports plus the ability to do data mining on KPIs and reports. It is
interesting to know how many critical items are out of stock with no orders placed to the vendors, but you
definitely want to be able to get to the item level so that corrective actions can be taken. Similarly, you
need to know if you have open orders for items in a surplus position because of a planned maintenance
activity that was cancelled or other.
Osisko Mining Corporation have chosen to start their new operation with an inventory
optimization system in place even if there was no history of parts usage in order to have access to KPI’s
and exception reports to help them start their store operations on a solid base.
CONCLUSION
I hope that you now find that Inventory Management can be a passionate and exciting field. Yes,
it can bring a smile to the Operation Manager’s face by eliminating 25% or 40% of equipment downtime
due to lack of parts. By eliminating 80% of stockouts at the store, your maintenance efficiency will
dramatically increase. Finally, by reducing your total inventory by more than 25% while improving service,
you are freeing up capital dollars and space that are always badly needed.