cat performance metrics for mobile mining equipment version 1.1.pdf

8/18/2019 CAT Performance Metrics for Mobile Mining Equipment version 1.1.pdf

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Performance Metrics for Mobile Mining Equipment

copyright 2005 Caterpillar Inc. May 2005 - version 1.1


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Table of Contents

Preface 1

1. Philosophy 2

2. Introduction 5

3. Terminology & Definit ions 8

3.1. Basic Terms

3.1.1. Performance Metric

3.1.2. Key Performance Indicator3.1.3. Target

3.1.4. Benchmark

3.1.5. Shutdown / Stoppage

3.2. Elements of Time 8

3.2.1. Total Calendar Hours

3.2.2. Scheduled Hours

3.2.3. Unscheduled Hours

3.2.4. Available Hours

3.2.5. Operating Hours

3.2.6. Stand-by Hours3.2.7. Production Delay Hours

3.2.8. Operational Delay Hours

3.2.9. Downtime Hours

3.2.10. Repair Delay Hours

4. Top Tier Metrics 11

4.1. Equipment Maintenance Management Metrics

4.1.1. Mean Time Between Shutdowns 11

4.1.2. Mean Time To Repair 154.1.3. Availability Index 18

4.1.4. % Scheduled Downtime 21

4.1.5. Asset Utilization 24

4.1.6. Maintenance Ratio 27

4.1.7. Top Problems / Pareto Analysis 31

4.1.8. PIP / PSP Completion Rate 37



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4.2. Application / Operational Metrics

4.2.1. Fuel Consumption 40

4.2.2. Payload Management 43

4.2.3. Haul Cycle Detail 48

4.3. MARC / Customer Satisfaction Metrics

4.3.1. Contractual Availability 53

5. Appendix

5.1. Delay Code Development and Usage 57

5.2. Generic Pareto Reference 60



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Preface

This document compiles the experiences of various individuals from the Caterpillar’sGlobal Mining Division, field service consulting personnel, and other service and product

support staff who have contributed directly or indirectly to its content. The knowledge

gained from this experience has been applied in various locations and under varyingoperating environments and conditions. Caterpillar believes it is appropriate to share this

information with those who own, operate and support mining equipment for the purpose

of creating more uniform criteria for the evaluation of product and project management.

We hope you will find this work useful in enhancing the continuous improvement efforts

at your respective project.


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1. Philosophy

The ultimate performance of any piece of mining equipment is primarily dependent upon

three critical factors: the design of the product, the application that it is used in, and the

maintenance that it receives during its time in service. To some degree each of thesefactors can be controlled, but some much more than others.

The equipment design is basically set by the manufacturer based upon his knowledge of

the requirements in the market place. The mining equipment manufacturer has some

flexibility in its design and can use “custom shop” features to alter the base machine for a

particular set of operating conditions. However, the basic design is fixed based upon theclear definition of a set of functional specifications that define the environment,

application and operation that the machine will be placed in. In order to have broad

market appeal and to assure that the cost of the product is not prohibitive, themanufacturer is somewhat limited in terms of how far it can go. As such, a design

targeted at the 90th percentile of application severity is typically more reasonable thanone targeted at the toughest application that the equipment will ever be placed in.Obviously, the design target is also a function of the consequences of failure therefore

products such as nuclear power plants and commercial aircraft are far less cost-sensitive

than mining equipment. Thus, they can afford to invest in a more rigorous design and

can justify redundant systems that tend to drive product reliability (and costs) muchhigher. Manufacturers of mining equipment are far more restricted in terms of what they

can do and running modifications and improvements are typically limited to “tweaking”

the base machine.

The application in which mining equipment is used is also somewhat fixed although

mines do change over time, typically becoming more severe, i.e. deeper, steeper, longerhauls, etc. Parameters such as altitude, ambient temperature, precipitation, and the

materials that are excavated and mined are pretty much fixed and it is up to the miner to

determine how he can best deal with the conditions he’s faced with. He has some degreeof control in terms of the equipment he selects to do the job and the manner in which he

uses it but many of the challenges he has from an application standpoint he has to learn to

live with. To the extent that the mine’s Engineering and/ or Operations Departments canestablish criteria for haul road design and maintenance … the mine plan (grades, haul

road layout, haul distances, traffic patterns, etc.), and operations (payload management,

speed limits, operator training, etc.) … they can influence the performance of theequipment significantly, provided those policies are adhered to.

Maintenance is the factor that offers management the best opportunity to influence and

control the resultant performance of its equipment. Equipment manufacturers andsuppliers do publish a set of recommendations for the maintenance of the equipment that

it sells but those recommendations tend to be very generic and are frequently based uponthat manufacturer’s understanding of the “typical” application for its equipment. The

end-user has enormous ability to influence the performance of the equipment he

purchased through the maintenance practices he establishes. The proper selection of oils


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and lubricants, the contamination controls he implements, and the amount management is

willing to invest in facilities, tooling, support equipment, and training for its staff have adirect bearing on the final results it derives from the equipment it purchases.

More importantly, the organization that is put in place to maintain and support the

equipment must be designed to involve all of the critical elements of that organization inthe equipment management process, e.g. Maintenance, Operations/ Production, Planning,

Scheduling, Parts, Training, etc. If the organization is structured such that each of the

problems and issues that impact equipment performance are known, quantified, andcommunicated throughout the organization, the maintenance (actually, the equipment

management) effort can be extremely effective in managing problems or, better still, inavoiding them altogether.

Maintenance is frequently thought of as drop oil, change filters, and perform the various

tasks defined by the equipment manufacturer in its maintenance recommendations.Maintenance should also be viewed as predictive and corrective in order to be fully

effective. When maintenance is viewed in the broader sense of equipment management,

the predictive and corrective aspects of maintenance are emphasized since the termequipment management implies a cohesive effort on the part of the entire organizationand not simply those routine activities performed by the Maintenance Department.

Communication, participation, contribution and accountability by each functional area

within the organization are fundamental to the overall success. With informationgathered and flowing across departmental boundaries, everyone involved knows and

understands what the key issues affecting performance are and maintenance can be

customized to focus on management, correction and avoidance of root causes of problems. Obviously, this process requires regular and ongoing review of equipment

performance and appropriate revisions of maintenance and equipment management

routines to address the problems at hand. Each step in the maintenance/ equipmentmanagement process should be targeted at identifying and addressing specific existing or

potential problem areas. Activities that are performed for no apparent or known reasonare oftentimes of questionable value. Clearly, maintenance has the greatest potential to

affect equipment performance of a given piece of equipment in any given application.

In order to quantify equipment performance, some set of performance criteria must be putin place. The following holds true for most activities including the management of

mining equipment:

You cannot manage what you cannot control,

you cannot control what you cannot measure,

you cannot (or at least should not) measure without a target,

and, without a target, you cannot improve.


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Management without metrics is, in reality, “management” by intuition. Benchmarking is

a process used to identify best practice for an industry or for specific functions or processes within that industry. Benchmarking may be used to gauge performance

relative to competition (external) or to monitor progress toward a specific set of

objectives (internal). Benchmarking identifies weak areas, poor practices and areas for

improvement. It is a systematic, ongoing, continuous improvement process that requireshonest self-evaluation and analysis. For optimum results, benchmarking requires a long-

term commitment from all levels in an organization and involvement and

communications among all the functional groups within the organization, i.e.management must set the tone and all participants should understand what they are doing

and why it is important.

Benchmarks, the result of the benchmarking process, are standards, measurements,

metrics, or key performance indicators that quantify best practices of an operation.

Benchmarks for mining could be operational (payload management, delays, load times,truck exchange times, production, cost per ton, etc.), application-related (grade/ grade

variation, rolling resistance, haul road maintenance, traffic flow, etc.), or maintenance-

related (availability, utilization, etc.). The benchmarks we established for equipmentmanagement were designed to answer the following seven basic questions:

1) How are we? Where do we stand today?2) How much effort have we invested in getting where we are?3) Is our situation the result of planned work?4) What are the location and frequency of our “pain”?5) Is our situation stable? Is it sustainable?6) Are we using “failures” as an information source?7) Can we forecast the future?

Irrespective of how good the product is, how good the maintenance is or how easy the

application is, sooner or later there will be problems. What distinguishes the successfulsite from the less successful one is the organization that is in place and how it deals with

problems when they arise. Rather than ask, how long will it be down? or when can we

put it back in service?, the knowledgeable Equipment Manager should ask, why did it go

down? and what can we do to prevent this from happening again? Too frequentlymanagement views unscheduled shutdowns as failures of the equipment and seeks out

technical solutions. Management should also view unscheduled shutdowns as potential

failures of the equipment management system. Properly used, performance metrics

enable management to distinguish product issues from project issues.


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2. Introduction

Performance metrics are some of the least understood and most often misused concepts in

mining. Our experience has shown that many mine tend to collect mountains of data …

some of which they use, much of which they do not. Furthermore, much of the data thatis used is not used in such a way that it actually helps improve the operation. For the

most part, the data that is collected is presented in the form of purely informationalreports that present little more than a historical perspective as to how the product or

project has performed up to a given point in time.

While informational reports are important, they don’t tend to be very useful in terms of providing management with the kind of information that aids it in an understanding of

how and why an operation arrived at its present condition. The purely informational

report fails to give management a feel for the likelihood of a good situation remaininggood … is the situation sustainable? Nor does it give any indication as to why the

situation may not be meeting expectations and what can be done to reverse the trend.Clearly, the truly effective report format must be predictive and corrective as well asinformative. Reports should be viewed as powerful “management tools” and be used to

guide the combined efforts and resources of the entire organization in the development

and implementation of action plans targeted at achieving and maintaining acceptable

levels of performance over time.

Why do we use performance metrics? Valid uses are:

to provide a useful and meaningful delivery format for the data analysis process,

to assess, quantify and document “as is” performance relative to internal targetsand established benchmarks,

to facilitate the use of historical performance in the prediction of future performance,

to highlight shortcomings and opportunities for improvement relative to design,

application, costs and maintenance,

to identify problems and corrective actions,

to establish priorities in the deployment of resources, and

to monitor progress of proposed solutions to identified problems.Unfortunately, far too often performance metrics are used only to assign and fix blame.Metrics should help us make sense of our situation and through their use we become

smarter and gain some degree of control over the outcome.

Although the calculation methods vary greatly, virtually every mine measures and reports

some form of availability. It is the basis on which Operations projects its equipment

needs (productive hours) in order to meet the mine's production goals. And, it is typically


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a key yardstick by which mine management quantifies the performance of its equipment

fleet and/or that of the group responsible for providing maintenance to that equipment.The overwhelming majority of mines also measure and report utilization in some form or

fashion whether it is utilization of availability, utilization of the asset or both. Neither of

these parameters provides much more than a historical view of the past and present status

or health of the product and project. That is, they fail to give the user any clear insightinto why things are the way they are and what needs to be done to ensure that a healthy

situation will remain healthy or how a problem situation got that way and what needs to

be done to correct the problems.

In addition to availability and utilization, mines frequently monitor and report any

number of other performance parameters that provide information but very little else thatcould be viewed as either predictive (allowing the mine to be proactive) or corrective

(enhancing the mine’s ability to develop suitable action plans).

Reports serve three primary purposes: to provide basic performance information to top

management, to identify problems or needed action, and to set priorities for the problemmanagement (continuous improvement process. Only the latter two provide information

that directly helps to improve the operation. Unfortunately, many systems concentrate onthe first item and leave maintenance management searching for ways to develop data and

information for the remaining two.

So, what is wrong with what we have today? As previously mentioned, reports tend to be

purely informational offering no more than a “historical perspective” of the past and

present situation. In general they lack the analytical (why the situation is as it is),interpretive (what it all means), corrective (what needs to be done? ... how do we manage

/ solve problems?), and predictive (what the consequences are or are likely to be)qualities that are required to facilitate continuous improvement. They also lack

standardization, which minimizes their understanding making them difficult to use. And,

lastly, they tend to be driven far more by “form” than “function” … attempts to“individualize” reports limit their utilization and reduce their value. Altogether too often

we find that attempts to innovate places over-emphasis on format, which trivializes

content. Information should be presented in a style that best suits the content and

objectives of the report and, at the same time, meets the needs of the audience. Charts,graphs and tables should be thought of only as a means to an end. The real “meat” of any

good report are the conclusions made from the “picture” of the data provided by the

graphics and the resulting action plans that are developed to address problems that areidentified.

What do we really want and need? Reports that identify problems (present and pending),document product and project health and eliminate “surprises”, e.g. cost overruns,

availability shortfalls, customer dissatisfaction. Reports should also help set priorities for

problem management / continuous improvement activities in order to help focus the

effort of the limited resources at our disposal. They should inform and at the same time possess analytical, interpretive, predictive, and corrective characteristics, stimulating

thought not simply reporting data. Reports need to be regular (typically monthly), timely


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(management can’t manage with old information), visual (easy to use and understand at a

glance), and concise (bigger is not always better; encouraging the audience to read).Reports should be driven by functional objectives (results / action oriented!) and consider

design, application and maintenance. One very good “Rule of Thumb” is “don’t generate

more questions than you answer”. If one thinks of reporting as, “applying what you

know to what you want to know”, the task becomes much simpler.

In the same sense that an airline pilot needs only five or six of the hundred or so sources

of information he has at his disposal to safely land a plane, our intent is to provide a“cockpit view” of the handful of performance metrics, actually Key Performance

Indicators, that mine management needs to assess their situation. Obviously, in both

cases this cockpit view needs to be supported by sufficient secondary information to permit the pilot or the mine manager to proactively take necessary action should a

potential problem be detected and to take the appropriate remedial steps to resolve any

existing problems. Without this supporting information we find that altogether too often

the strategy for curing the ills of a project is purely reactive and that frequently this knee

jerk approach drives the organization even deeper in the direction that created much ofthe “pain” in the first place.

Caterpillar has invested a great deal of time, energy and resources identifying and

developing several metrics of performance (Key Performance Indicators) that we are

very comfortable with to quantify and trend product and project health. Understandingwhat those metrics mean relative to site performance and how they interact with each

other was the initial focus in our development of the process. The next step was to devise

a presentation format that enables management to quickly and easily recognize criticalissues facing it in order to implement solutions to meet its overall objectives. The

primary objective of this document is to summarize a globally consistent measurementand evaluation system for all mining operations that use Caterpillar equipment using the

measurement parameters presented herein as the basis for quantifying product and project

performance.


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3. Terminology & Definitions

3.1. Basic Terms

Performance Metric: A term used to describe the outcome of any process used tocollect, analyze, interpret and present quantitative data. A measurement parameter that

enables performance against some pre-defined Target or Benchmark to be monitored. Ameasurement used to gauge performance of a function, operation or business relative to

past results or others.

Key Performance Indicator: Also known as KPI; a top level Performance Metric. Thecollection of KPI's used to describe performance of a particular project may vary from

site to site, by product, application and even one's perspective, i.e. dealer & customer,

Operations & Maintenance Depts., Project & Contract Controls Dept. NOTE: All KPI'sare Performance Metrics but Performance Metrics are not always KPI's.

Target: A desired goal; a standard by which a Performance Metric can be measured or judged. The Target for a particular Performance Metric can be somewhat arbitrary and

will likely vary by product, application or specific site. The Target is frequently

determined by customer needs, his expectations and / or contractual commitments, andmanufacturers’ specifications.

Benchmark (noun): A world-class performance standard relative to a specific

Performance Metric; represents and quantifies "best practice" of an operation or ofspecific functions within that operation according to a specified Performance Metric. A

Benchmark may vary by product but, by contrast, is much less arbitrary than a Target. A

Benchmark is determined by and represents actual, documented, sustainable performanceover time relative to some Performance Metric.

Shutdown / Stoppage: An event that takes a machine out of service. Shutdowns may bescheduled or unscheduled and include all types of maintenance and repair activities

except daily lubes, refueling and inspections executed during lube or refueling activities.

Operational stoppages, e.g. shift changes, lunch breaks, etc., are not included as

shutdowns. “Grouped” repairs count as a single shutdown. Shutdown count isindependent of event duration or complexity, i.e. a five-minute event counts the same as a

100-hour event and a headlight replacement counts the same as a catastrophic major

component failure.

3.2. Elements of Time

Many of the performance metrics in use today (most notably availability and utilization)involve time or ratios of time as the fundamental calculation parameters. While the

formulae used to calculate these metrics are similar, the results often vary somewhat from

site to site due largely to differences in the interpretation of the elements of time that


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comprise those equations. As such, it is important to define and document the individual

elements of time that make up the various categories of daily minesite operations.

Furthermore, many sites tend to use terms such as physical availability, mechanical

availability and simply “availability” interchangeably. Due to this lack of standardization,

it is impossible to tie these metrics to a global Benchmark. Therefore, we have notattempted to use these metrics as key performance indicators for equipment management.

Simply put, physical availability formulae exclude all forms of downtime from the

calculation of available hours while mechanical availability formulae ignore the effects ofareas such as communications radios, dispatch system, fire suppression systems, tires,

etc. as non-mechanical downtime and exclude only elements pure mechanical downtime

in the calculation of available hours.

A similar and perhaps even more compelling argument could be made for contractual

availability since not only does the interpretation of the time elements vary from one site

to the next, the exclusions and limitations placed on downtime counted against

availability are highly variable from contract to contract. In spite of the fact that thesevariations make global Benchmarking meaningless if not impossible, we do consider

contractual availability to be an equipment management KPI since it has not onlyfinancial implications but also contributes significantly to customer satisfaction as it

relates to the product as well as the service organization responsible for its support.

It should also be noted here that even in the absence of a formal contract the end-user has

a set of expectations for equipment performance. A measure of these expectations will

likely include some variation of the physical, mechanical or contractual availabilityformulae. Since the equipment manager’s ability to meet the expectations of his

customer are linked to that customer-specific metric, it should be viewed as an equipmentmanagement KPI and treated in exactly the same way as contractual availability.

The following graphic and descriptions (figure 1) illustrate our interpretation of theelements of time that make up the various categories of daily mining equipment

operations.

Figure 1: Elements of time for mining operations


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Total Calendar Hours: Total time in the period to be analyzed, e.g. 8760 hours / year,

720 hours / 30 day month, 168 hours / week, etc.

Scheduled Hours: Time that a machine is scheduled for operations. Typically

determined by the mine Planning and Operations Departments in conjunction with their

overall production targets.

Unscheduled Hours: Hours outside the plan; lost time that result from accidents,

strikes, weather, acts of God, any holidays that are observed, etc. (typically defined bythe customer or contained in the Customer Support Agreement or MARC).

Available Hours: Time that a machine is capable of functioning in the intendedoperation.

Operating Hours: Time that a machine is actually operating in the intended function.

Stand-by Hours: Time that a machine is available for operation but is not being used,e.g. no operator available, "over-trucked", etc. Also known as "Ready line" hours.

Production Delay Hours: Time that a machine is operational but is waiting with the

engine running due to blasting, loader wait time, etc. Production delay hours are

frequently not accounted for separately and are included in the operating hourstabulation. One the other hand, some dispatch systems do track production delay hours in

an effort to minimize and manage them. In either case, lost hours that result from

production delays should be reconciled and not counted against machine availability.

Operational Delay Hours: Time that a machine is available for operation but is not being used due to shift changes, lunch breaks, meetings, prayers, etc. Just as was the case

for production delay hours, lost hours that result from operational delays should be

reconciled and never counted against machine availability. On the other hand, policy atmany mines ignores operational delay hours altogether and therefore, does not credit

operational delay hours as either scheduled or available hours.

Downtime Hours: Time that a machine is not available for operation; out of service forall forms of maintenance, repairs and modifications. Includes inspection and diagnostic

time as well as any delay or wait time for manpower, bay space, parts, tooling, literature,

repair support equipment, decision making, etc. May be scheduled or unscheduled.

Repair Delay Hours: Time that machine is waiting for repairs due to unavailability of

labor, parts, facilities, equipment or tooling. Typically not well documented in mostmachine downtime histories but is nonetheless included, yet unrecognized, as part of the

machine downtime record.

NOTE: Please refer to Appendix 5.1, “Delay Code Development and Usage” for a more

complete discussion on production, operational and repair delays.


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4. Top Tier Metrics

4.1. Equipment Maintenance Management Metrics

4.1.1. Mean Time Between Shutdowns

Definition:

The average operating time between machine stoppages … the average frequency of

downtime events, expressed in hours.

Description:

The most successful mining operations are those that manage and maintain equipment

such that it is available for extended periods of uninterrupted service. MTBS is a

measure that combines the effects of inherent machine reliability and the

effectiveness of the equipment management organization in its ability to influenceresults through problem avoidance, i.e. defect detection, repair planning, scheduling

and execution. MTBS is the single most important measure of equipment

maintenance management performance.

Calculation Methodology:

Data Source(s):

Operating hours obtained from machine service meter reading. Note, hours obtainedfrom dispatch systems frequently do not agree with machine SMU due to coding of

production delays, etc. Note that hours taken from machine SMU will be higher than

those taken from dispatch, oftentimes by as much as 10 percent.

* Production delay hours may not be tracked and accounted for separately and aretherefore included in the total operating hours. Sites that use dispatch systems may

track and code production delay hours separate from operating hours hence they must

be acquired from dispatch.

Shutdown count obtained from machine workorder history and dispatch system.

Dispatch information must be used to account for shutdown events that are notaccompanied by a workorder.

Operating Hrs + Production Delay Hrs*

Number of Shutdowns

MTBS (hours) = (1)


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MTBS is used to gauge product reliability and, more importantly, the ability of the

equipment management organization to influence the end result. Since availability isa function of the frequency and duration of machine downtime events, a lower than

desirable MTBS is symptomatic of low availability.

It is extremely important to note that problems arise when the calculation criteria arenot adhered to, e.g. arbitrary modifications in the shutdown criteria or using hours

other than operating hours for the purpose of “artificially” increasing MTBS

invalidates the results since the benchmarks and ranges of acceptability are based onspecific calculation methodology. Comparing results derived from one calculation

method to benchmarks or targets established by another is of questionable value.

Interpretation:

MTBS should be interpreted, at least initially, by model on the basis of theconsolidated fleet over a period of one month and trended over time (six to twelve

months). Recognize that MTBS will vary significantly from machine to machine

within a given fleet and from day to day during the period under investigation. Assuch, analyzing results of small populations over short intervals will result in wide

variations that can be very misleading. Declining MTBS is a valid predictor of

pending problems. Likewise, MTBS can be used to gauge the impact of changes thatresult from efforts in continuous improvement.

Action:

If MTBS is lower than desirable or declining over time, the organization should

review the following:

• Investigate on the basis of individual machines. Pareto applies here and wetypically find that a relative small percentage of machines are operating well

below the overall fleet average. Attacking those machines and bringing them

up to standard will have a dramatic effect on overall fleet performance.

• Use Pareto to determine which areas of the machine (components or systems)

are resulting in higher than anticipated repair frequency. Results of this typeof investigation will typically point out sources of chronic product

unreliability and/or equipment management shortcomings, e.g. repair redo,

inability to distinguish symptom from cause, inadequate ConditionMonitoring, etc.

•

Analyze machine history records to determine if unscheduled stoppages aredriving the result. If this is the case, it indicates gaps in the detect-plan-

execute cycle and revisions to the Condition Monitoring, Planning &

Scheduling and/or execution areas will be necessary.

• Use machine history to calculate MTBS after PM. MTBS after PM should beat least 50% greater than overall MTBS. If MTBS after PM is not sufficiently


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4.1.2. Mean Time To Repair (MTTR)

Definition:

The average downtime for machine stoppages … the average duration of downtime

events, expressed in hours.

Description:

Repair planning, management and execution are all factors that contribute to the

duration of machine shutdowns. Mean Time To Repair (MTTR) is a performance

measure that quantifies repair turnaround time, i.e. how quickly (or slowly) a machineis returned to service once a downtime incident occurs. MTTR combines the effects

of inherent machine maintainability / serviceability and the efficiency of the

equipment management organization in delivering rapid remedial action in theexecution of needed repairs.


Data Source(s):

Downtime hours obtained from machine workorder history and dispatch system.

Dispatch information must be used to account for downtime that is not accompanied by a workorder. It is essential to note that repair delay time should be included in the

downtime history calculation. If delay times are known, MTTR should be calculated both with and without delays.

Shutdown count obtained from machine workorder history and dispatch system.

Once again, dispatch information must be used to account for shutdown events thatare not accompanied by a workorder.

Benchmark:

MTTR benchmarks vary somewhat by machine model, their relative size and design

complexity but to a much lesser extent than MTBS; machine age is the primary driver

of MTTR. MTTR for large Off Highway Trucks in the 785 – 793 size class is very

well documented. The benchmark for a fleet of trucks in the 785 – 793 size class is 3to 6 hours. MTTR for new trucks should be close to the low end of the range while

that of a “mature” fleet (one that has undergone its first round of major component

rebuilds) should be closer to the high end of the range. This is a result of the relativecomplexity of the repairs seen on new versus “mature” machines.

Total Downtime Hours

Number of Shutdowns MTTR (hours) = (2)


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Benchmarks for trucks smaller than the 785 and the 797 are less well known although

it is believed that MTTR for trucks in the 769 – 777 size class will be slightly lower(10 to 20%) while that of the 797 will be perhaps 10% higher.

Similarly, benchmarks for other large mining equipment are not well documented.

However, indications are that once MTTR data is collected, analyzed and validated,the results will fall into much the same range as large OHT fleets with larger

machines, e.g. 24H MG and 5000 series HEX, being as much as 30 to 40% higher.

Usage:

Just as it is with MTBS, valid use of MTTR as an equipment management tool

requires acceptance of a repair-before-failure philosophy as the most cost efficient

and effective maintenance strategy for ensuring maximized fleet performance and

optimum costs. Running to failure will result in excessive machine downtime,inefficient use of resources and higher repair costs.

MTTR is used to gauge product serviceability but, more importantly, the ability of theequipment management organization to influence the end result through efficientrepair execution. Since availability is a function of the frequency and duration of

machine downtime events, a higher than desirable MTTR is symptomatic of low

availability. Viewing MTTR in the context of delays will also assist management in

identifying sources of those delays and taking appropriate action to minimize them.

Here again, it is extremely important to note that problems arise when the calculation

criteria are not adhered to, e.g. arbitrary modifications in the shutdown criteria orusing hours other than downtime hours for the purpose of “artificially” reducing

MTTR invalidates the results since the benchmarks and ranges of acceptability are

based on specific calculation methodology. Comparing results derived from one

calculation method to benchmarks or targets established by another is of questionablevalue.

Interpretation:

MTTR should be interpreted, at least initially, by model on the basis of theconsolidated fleet over a period of one month and trended over time (six to twelve

months). Recognize that MTTR will vary somewhat from machine to machine within

a given fleet and from day to day during the period under investigation. As such,analyzing results of small populations over short intervals will result in wide

variations that can be very misleading.

High or increasing MTTR is an indication of problems in the detection, planning

and/or execution of repairs and inefficient use of resources while low or decreasing

MTTR is an indication of “patching” rather than fixing problems. It is also

worthwhile to note that availability can be “bought” by driving MTTR lower with thedeployment of excessive resources, e.g. manpower, facilities, parts, etc., however this

approach is results in additional costs that will impact profitability.


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Action:

If MTTR is lower than desirable, the organization should review the following:

• Focus on grouping repairs for execution during available “windows of

opportunity”, e.g. PM. This can be achieved through improved detection

(Condition Monitoring) and planning; backlog management is an effectiveequipment management tool than should help in this area. It should be noted

here that “shop-found” defects are repaired far less efficiently than defects

that have been detected in advance and have benefited from the planning process.

• Devise audit procedures particularly for repetitive problems; this should

minimize “patching” rather than fixing problems.

If MTTR is higher than desirable, any or all of the following could achieve reduced

turnaround time, lower MTTR:

• Increase the percentage of scheduled repairs; unscheduled repairs typicallyresult in higher than necessary downtime hours.

• Improve personnel efficiency; control time to execute repairs; identify, focus

and train on the most inefficient areas, i.e. high repair time shutdowns.

• Identify and document sources of delay time; address the causes of delay /

wait time.

• Improve field service auxiliary equipment; fully equipped service trucks and

well-trained personnel can help reduce field repair times. The majority of

unscheduled stoppages occur in the field thus the organization should be well

prepared to handle them.

• Control and improve PM execution time; while average PM execution times

area far less than major component exchanges, they occur far more frequentlyand have a much greater influence on total downtime (availability).

• Develop specialized staff for PM routines and major component exchanges.

Has Impact On:

• Fleet availability & resultant production• Quantity & cost of supporting infrastructure• Efficient utilization of manpower & resources

Is Impacted By:

• High percentage of unscheduled repairs (poor Condition Monitoring)• Inadequate resources (manpower, facilities, tooling, parts, etc.)• Excessive delay times• Inadequate Planning & Scheduling (minimal use of grouped repairs)


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• Lack of training (excessive and/or ineffective diagnostic / troubleshooting)• Use of information (reactive vs. proactive)

Presentation Format:

Plotting monthly MTTR over a twelve-month period on an X-Y line graph is the most

effective method to demonstrate trends in MTTR. (Refer to figure 3).

Figure 3: MTTR trend versus target range for large OHT’s

0

1

2

3

4

5

6

7

8

9

10

Nov-02 Dec-02 Jan-03 Feb-03 Mar-03 Apr-03 May-03 Jun-03 Jul-03 Aug-03 Sep-03 Oct-03

Month - Year

M T T R

- ( h o u r s )

Target Rang e

4.1.3. Availability Index

Definition:

The ratio of MTBS (average shutdown frequency) to the sum of MTBS and MTTR

(average shutdown duration), expressed as a percentage.

Description:

Availability is the result of the frequency and duration of downtime events(shutdowns). Since idle hours and specific availability calculation methods vary

significantly from site to site, a “normalized” variation of the general form was

developed for the purpose of comparison. The Availability Index formula is avariation on both the mechanical and physical availability formulae therefore changes

will be proportional. The Availability Index does not take into account any stand-by

(idle) hours where the equipment may have been available but was not utilized by


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production thus any effects of utilization are ignored (low utilization operations tend

to exhibit “artificially” higher availability since stand-by hours are essentially “free”).

Because of this mathematical relationship, if any two of the three factors are known,

the third can be calculated. In addition, when the Availability Index changes, this

mathematical relationship shows which of the other two factors had the greatestinfluence upon that change. This allows management to react appropriately to

changes in the Availability Index and by focusing its effort and resources on the

frequency (MTBS) or duration (MTTR) of downtime events.


Data Source(s):

Since Availability Index is derived from MTBS and MTTR, the data sources for thosetwo metrics are applicable here as well. (See previous two sections).

Benchmark:

Availability Index benchmarks vary significantly by machine model, their relative

size, age and design “maturity” and complexity. Availability Index for large OffHighway Trucks in the 785 – 793 size class is very well documented. The benchmark

for a fleet of new trucks 92%; that of a “mature” fleet (one that has undergone its first

round of major component rebuilds) is 88%.

Benchmarks for truck smaller than the 785 and the 797 are less well known althoughit is believed that the Availability Index for trucks in the 769 – 777 size class will besomewhat higher (possibly 2 to 3%) while that of the 797 will be perhaps 1 to 2%

lower.

Similarly, benchmarks for other large mining equipment are not well documented.

However, indications are that once the data is collected, analyzed and validated, the

results will fall into much the same range as large OHT fleets with larger machines,

e.g. 24H MG and 5000 series HEX, being as much as 3 to 4% lower and smallermachines, e.g. 16H, being 1 or 2% higher.

Usage:

Since the Availability Index ignores the effects of utilization, invariably will yield a

lower result than physical, mechanical and contractual availability calculations.

Thus, it provides the organization a management tool that enables it to determine thetrue affects of its equipment management efforts while ignoring any influence of

variations in machine utilization.

MTBS

MTBS + MTTR X 100 (3)Availability Index (%) =


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The standardized calculation methodology also facilitates realistic comparisons from

site to site for the purpose of benchmarking performance relative to similar sites inother parts of the world. And by breaking availability down into its elements,

frequency (MTBS) or duration (MTTR) of downtime events, management is able to

react appropriately to changes in the Availability Index and by focusing its effort and

resources in the right areas.

Interpretation:

Since the Availability Index is purely a function of the frequency (MTBS) and

duration (MTTR) of downtime events and the effects of utilization are totally ignored,

management is able to quantify the impact of both on the end result and respondaccordingly. Availability Index should be analyzed, at least initially, by model on the

basis of the consolidated fleet over a period of one month and trended over time (six

to twelve months).

Recognize that Availability Index will vary somewhat from machine to machine

within a given fleet and from day to day during the period under investigation. Assuch, analyzing results of individual or even small machine populations over short

intervals will result in wide variations that can be very misleading. Low or declining

Availability Index is a valid predictor of pending problems. Likewise, AvailabilityIndex can be used to gauge the impact of changes that result from efforts in

continuous improvement.

Action:

Since Availability Index is derived from MTBS and MTTR, once the contributions of

each are known and understood, appropriate action can be taken to attack the

problems. Please see “Action” sections for MTBS and MTTR.

Has Impact On:

• Production• Customer satisfaction

(Since Availability Index is derived from MTBS and MTTR, if either one or both are

contributing to a shortfall in the Availability Index, any influence will be similarly

felt by variations in Availability Index).

Is Impacted By:

• MTBS• MTTR

(Please see contributing factors related to both MTBS and MTTR in previoussections).


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Plotting monthly Availability Index over a twelve-month period on an X-Y line graphis the most effective method to predict trends. Plotting MTTR and MTBS on the

same graph with Availability Index is the most graphic method to determine which

factor, MTTR (repair duration) or MTBS (repair frequency), is driving the end result.(Refer to figure 4 below).

Figure 4:Availability Index graphed with MTBS & MTTR

0

5

10

15

20

25

30

35

40

Nov-02 De c-02 Jan -03 Fe b-03 Mar-03 Apr-03 May-03 Ju n-03 Ju l-03 Au g-03 S ep-03 O ct-03

Month - Year

M T B S /

M T T R -

( h o u r s

)

84%

86%

88%

90%

92%

94%

96%

98%

100%

A v a

i l a b

i l i t y

I n d e x

Target Availability Index

4.1.4. % Scheduled Downtime

Definition:

The percentage of total downtime hours performed in a given period that have been planned and scheduled.

Description:

Work that has passed through the planning process is generally “scheduled” as thelast step in that process. By monitoring the amount of work that has been plannedand subsequently scheduled, the organization can assess its effectiveness in defect

detection, plan repairs and complete its work with a high level of efficiency. A

simple “test” to determine if a repair is truly planned and scheduled is to ask thequestion, “Are the parts and necessary resources allocated to the shop bay before the

machine is stopped?”


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A high percentage of unscheduled downtime incidents results in very inefficient use

of resources and excessive costs since personnel are frequently shuffled from job to job and facilities and manpower requirements need to be sufficiently large to

accommodate huge swings in the number of machines down for repairs. Data

collected from mine studies has shown that the average downtime for unplanned /

unscheduled work is up to eight times greater than the downtime for planned /scheduled activity. Aside from MTBS, % Scheduled Downtime Hours is the most

important measure of equipment maintenance management performance.


Data Source(s):

Downtime hours obtained from machine workorder history and dispatch system.Dispatch information must be used to account for downtime that is not accompanied

by a workorder. It is essential to note that repair delay time should be included in the

downtime history calculation.

Individual workorders should be coded as “scheduled” or “unscheduled in order to

track the number of downtime hours that are scheduled.

Benchmark:

% Scheduled Downtime Hours for large Off Highway Trucks in the 785 – 793 sizeclass is very well documented. Mines with highly effective equipment management

processes in place are able to execute 80% of its maintenance and repair downtime

activity on a scheduled basis. We believe that this criterion holds true for othermining equipment as well however requirements for less utilized, non-production

equipment may be somewhat less.

Usage:

% Scheduled Downtime Hours can be used to determine if an organization is incontrol of the situation (proactive) or if it is simply responding to the immediate

needs of the equipment (reactive).

Interpretation:

The % Scheduled Downtime Hours should be analyzed, at least initially, by model onthe basis of the consolidated fleet over a period of one month and trended over time

(six to twelve months). A low % Scheduled Downtime Hours is indicative of gaps in

the detect-plan-execute cycle and revisions to the Condition Monitoring, Planning &Scheduling and/or execution areas will be necessary. Declining % Scheduled

Downtime Hours is a valid predictor of pending problems and may very well predict

Scheduled Downtime Hours

Total Downtime Hours % Scheduled Maintenance = X 100 (4)


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future shortages of manpower and facilities. Likewise, % Scheduled Downtime

Hours can be used to gauge the impact of changes that result from efforts to improvethe disciplines related to the detect-plan-execute cycle.

Action:

If % Scheduled Downtime Hours is lower than desirable or declining over time, the

organization should review the following:

• Use Pareto to identify causes of machine unreliability that are resulting inunscheduled stoppages. Devise an improved detection and/or containmentstrategy to deal with these issues in order to minimize their influence or

eliminate them altogether.

• Review Condition Monitoring practices to ensure that they are focused on

problems that are leading to unscheduled downtime events.

• Refine Planning and Scheduling practices to ensure that once problems are

detected they receive full benefit from the planning and scheduling activity.

• Employ Backlog Management as an equipment management tool to deal with

problems identified through Condition Monitoring.

Has Impact On:

• Fleet availability & resultant production• Overall repair and maintenance costs• Manpower and infrastructure requirements• MTBS and MTTR

Is Impacted By:

• Product unreliability• Condition Monitoring quality• Planning and Scheduling disciplines• Limited or inadequate use of Backlog Management


Plotting monthly % Scheduled Downtime Hours over a twelve-month period on an X-

Y line graph is the most effective method to monitor and predict trends. (Please see

sample graphic, figure 5, on the following page).


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Scheduled vs Unscheduled Work

(Based on machine downtime hours)

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Jun'99 Jul'99 Aug'99 Sep'99 Oct'99 Nov'99 Dec'99 Jan'00 Feb'00 Mar'00 Apr'00 May'00

Month/ Year

P e r c e n t S c h e d u l e d

Trend

(rolling average)

Figure 5: % Scheduled Work trend

4.1.5. Asset Utilization

Definition:

The proportion of time that a machine is operating (operating hours) divided by the

total calendar time in the period, expressed as a percentage.

Description:

How effectively the Operations Department schedules equipment and efficiently it

utilizes that equipment has significant implications for Maintenance. If machines arescheduled for use 24 hours a day, 7 days a week, Maintenance must respond by

working with Operations to find windows of opportunity in which maintenance and

repairs can be performed without increasing downtime. These opportunities typicallyoccur during scheduled shutdowns but they may also come at shift change, lunch

breaks or during operational delays such as during blasting or fueling of equipment.

In all circumstances, Operations and Maintenance need to recognize that they areworking together toward common goals … high availability, good machine reliability

and the lowest possible cost per unit of production.


Operating Hours

Total Calendar HoursX 100 (5)Asset Utilization (%) =


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Data Source(s):

Operating hours are obtained from machine service meter reading and should include production delay hours. Note, hours obtained from dispatch systems frequently do

not agree with machine SMU due to coding of production delays, etc. Note that

hours taken from machine SMU will be higher than those taken from dispatch,oftentimes by as much as 10 percent.

Total calendar hours is equal to the total time in the period to be analyzed, e.g. 8760

hours / year, 720 hours / 30 day month, 168 hours / week, etc.

Benchmarks:

Asset Utilization for large Off Highway Trucks in the 785 – 793 size class is very

well documented. Mines with highly effective equipment management processes in

place are able to achieve Asset Utilization of 90%, over 7800 operating hours peryear. We believe that this Benchmark is valid for other production mining equipment

however the Benchmark for less utilized, non-production equipment, althoughunknown, may be significantly less.

Usage:

Usage of the Asset Utilization metric varies substantially based upon the perspective

of the user. The mine Purchasing Department views it as an indication as to whether

additional equipment purchases are necessary or if Operations should simply make

more efficient use of the equipment it already has. The MARC development staffviews Asset Utilization as a prediction tool for contract revenue stream. The

Equipment Management staff utilizes Asset Utilization as a tool to predict staffing

levels as well as in the planning and scheduling of component replacement, i.e. asmachine usage increases, the quantity of maintenance manpower must be increased to

keep pace and components will come due for replacement sooner.

Interpretation:

Asset Utilization and availability are directly related, i.e. high availability generallyresults in high Asset Utilization. For the equipment manager, high Asset Utilization

implies very good repair efficiency, a very low number of stand-by hours and, since

Maintenance Ratio is a function of operating hours, it dictates staffing levels requiredto support the fleet. Furthermore, since component lives are a function of operating

hours, high Asset Utilization means that components will come due for replacement

sooner. Asset Utilization is a valid indicator of equipment management proficiency.

Action:

Lower than desirable Asset Utilization should be investigated in the context of the

parameters that define availability as follows:


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• If stand-by hours are excessive, it may be a result of excess haulage capacity or

ineffective scheduling of operators. This is not something that the equipmentmanager will be able to influence but he should be aware of the issue and its

impact.

• If operational delay hours are excessive, it may be the result of excessive timelost at shift change, meals, etc. Once again, this is not something that the

equipment manager will be able to influence but he should be aware of the

issue and its impact.

• If both stand-by and operational delay hours are within reasonable limits,

availability (too few operating hours) is most likely the cause and theequipment manager should investigate to determine the root cause, e.g. repair

efficiency / effectiveness, machine reliability, etc.

Has Impact On:

•

Production, ... mine production results are related directly to Asset Utilization(and operational efficiency).

• Revenue, ... revenue stream in a MARC environment is related directly to

Asset Utilization.

• Manpower requirements, … maintenance and repair labor costs will increase

with Asset Utilization.

• Component life cycles, … components will reach their useful lives sooner as

Asset Utilization increases.

Is Impacted By:

• Repair efficiency/ effectiveness, ... efficient and effective repair execution

results in less downtime, which in turn produces higher Asset Utilization.

• Mine production goals, ... Asset Utilization is influenced directly by the mines

production requirements.

• Operator scheduling, … low Asset Utilization resulting from excessive stand-

by hours (machine idle time) is affected by the mines ability to schedule andassign operators to the equipment.


Data should be collected, analyzed and reported monthly. Plotting Asset Utilization

versus time over a twelve-month period on an X-Y line graph is an effective methodfor identifying trends. Analyzing Asset Utilization in terms of its components and in

conjunction with availability and production can be an effective method for

determining cause-effect relationships. (Please see sample graphic, figure 6, on thefollowing page).


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Figure 6: Asset Utilization trend

70%

75%

80%

85%

90%

95%

100%

Oct-02 Dec-02 Jan-03 Mar-03 May-03 Jun-03 Aug-03 Oct-03 Nov-03

Month - Year

A s s e t U t i l i z a t i o n

)

- ( %

/ A v a i l a b i l i t y I n d e x

4.1.6. Maintenance Ratio

Definition:

The dimensionless ratio of maintenance and repair man-hours to machine operating

hours.

Description:

Maintenance Ratio is an indication of the amount of effort required to keep

equipment in service as well as the efficiency with which labor is deployed and the

effectiveness of the workforce in carrying out its duties. Maintenance Ratio can becalculated as either “charged” or “direct”. “Charged” Maintenance Ratio considers

only workorder man-hours (direct labor). Repair shop, e.g. Component Rebuild

Center, labor is not included in the calculation. “Overall” Maintenance Ratio

includes all the elements of “charged” Maintenance Ratio plus staff, supervision andidle time.


Maintenance & Repair Man-HoursMaintenance Ratio charged = Operating Hours

(6)


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Data Source(s):

Maintenance and repair man-hours are obtained from the work order history. Theresult should include actual time spent working on all forms of maintenance, repairs

and modifications as well as inefficiencies that result from inspection and diagnostic

time or any delay or wait time for bay space, parts, tooling, literature, repair supportequipment, decision making, etc.

Operating hours are obtained from machine service meter reading and once again

should include production delay hours. Note, hours obtained from dispatch systemsfrequently do not agree with machine SMR due to coding of production delays, etc.

Benchmarks:

Maintenance Ratio benchmarks vary significantly by machine model, their relative

size, age and design “maturity” and complexity. Maintenance Ratio for large OffHighway Trucks in the 785 – 793 size class is very well documented. The benchmark

for a fleet of new trucks is 0.20 man-hours/ operating hour; that of a “mature” fleet(one that has undergone its first round of major component rebuilds) is 0.30 man-hours/ operating hour.

Since by definition these benchmarks represent documented, best-in-class performance sustainable over time, we are frequently asked to assess performance

through a range of results. The following (table 3) represents our best judgment in

this area.

MR Assessment / Characteristics

0.30 to 0.35 Excellent; high % of scheduled downtime; Equipment Mgmt. organization is highly proactive.

0.35 to 0.40 Acceptable; majority of downtime is scheduled; substantial emphasis on Equipment Mgmt.

0.40 to 0.50 Marginal; approx. half of all downtime is scheduled; Equipment Mgmt. disciplines not fully functional.

0.50 to 0.60 Fair; < 40% downtime is scheduled; minimal effort on Equipment Mgmt.

> 0.60 Poor; only PM’s are scheduled; Equipment Mgmt. organization is purely reactive.

Table 3: Site performance through range of Maintenance Ratios

Benchmarks for trucks smaller than the 785 and the 797 are less well known although

it is believed that Maintenance Ratio for trucks in the 769 – 777 size class will beslightly lower while that of the 797 will be somewhat higher.

Similarly, benchmarks for other large mining equipment are not well documented.However, indications are that once Maintenance Ratio data is collected, analyzed andvalidated, the results will fall into the ranges shown in the table below. It is important

to note here that machine application will play a role in Maintenance Ratio. This is

particularly true in the case of large Track-type Tractors that can be deployed aseither production or support equipment. (Refer to table 4 on the following page).


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Machine / Model MR

D10 / D11 TTT’s 0.40 to 0.50

992 / 994 WL’s 0.35 to 0.45

16 MG 0.10 to 0.15

24 MG 0.15 to 0.20

5000 HEX 0.50 to 0.60

Table 4: Maintenance Ratio guidelines for mining machines

Usage:

Valid use of Maintenance Ratio as an equipment management tool requires

acceptance of a repair-before-failure philosophy as the most cost efficient and

effective maintenance strategy for ensuring maximized fleet performance andoptimum costs. Running to failure will result in excessive machine downtime,

inefficient use of resources and higher repair costs.

Maintenance Ratio can be monitored over time to provide an indication of workshop

and manpower efficiency. It can also be used by the Maintenance Department to plan

manpower and budget needs. When Operations provides Maintenance with itsestimate of operating hours required to meet the production goals of the mine, the

Maintenance Department can use Maintenance Ratio to project the manpower

resources it must have to care for the equipment during that period.

Caution: While it is tempting to do so, the Project Manager should not use the

Benchmark levels to predict his manpower requirements unless he is certain that the

equipment management system in place is integrated and fully functional. The

Benchmark was measured at a site that was very well managed and all of the processes that comprise the equipment management system were in place and

performing at a very high level. Unless this is the case, using Benchmark performance to forecast manpower needs will result in significant delays waiting on

manpower thus increasing MTTR at the expense of availability. It is suggested that

Project Management use historical performance to predict future manpowerrequirements and gauge the efficiency of its operation based on the Benchmark.

To be useful as a budgeting tool, Maintenance Ratio needs to be measured for eachfamily of machines, i.e. trucks, loaders, dozers, motor graders, etc., as each family of

machines has different maintenance requirements. In addition, just as the

maintenance and repair requirements for equipment change with time, Maintenance

Ratio changes over time therefore Maintenance Ratio data must be analyzed relativeto the age of the equipment and where it is in the component replacement cycle. On

relatively new machines (those that have not yet started the component replacement

cycle) Maintenance Ratio is lower. However, once components are replaced, theMaintenance Ratio will increase and remain essentially constant.


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Interpretation:

In order to be best understood and utilized, Maintenance Ratio should be interpreted by model on a fleet basis for a consolidated period of one month and trended over

time (six to twelve months). Recognize that Maintenance Ratio will vary somewhat

from machine to machine within a given fleet and from day to day during the periodunder investigation depending upon the activities undertaken during the period. As

such, analyzing results of small populations over short intervals will result in wide

variations that can be very misleading.

Since Maintenance Ratio is an indication of the amount of effort required to keep

equipment in service, high or increasing Maintenance Ratio is an indication of problems in the detection, planning and/or execution of repairs. Mining operations

that must deal with a high percentage of unscheduled repairs (low MTBS) require the

investment of excessive manpower and shop resources to keep up with the demands

placed upon them. This inefficient use of resources can only be dealt with throughthe deployment of excessive manpower, facilities, parts, etc. (all costs to the project)

or by defining and correcting the shortcomings in the equipment management system.

Conversely, lower than required Maintenance Ratio will result in excessive delaytime waiting for manpower thus increasing MTTR and causing availability to suffer.

Action:

If Maintenance Ratio and the resultant cost of labor are too high, the organization

should investigate the following:

• Analyze machine history records to determine if unscheduled stoppages are

driving the result. If this is the case, it indicates gaps in the detect-plan-execute

cycle and revisions to the Condition Monitoring, Planning & Scheduling and/orexecution areas will be necessary.

• Improve personnel efficiency; control time to execute repairs; identify, focus

and train on the most inefficient areas, i.e. high repair time shutdowns.

• In general, any steps taken to increase MTBS will reduce manpower

requirements driving Maintenance Ratio in the right direction.

Has Impact On:

• Labor costs … Maintenance Ratio too high.

• Repair delays / excessive MTTR… Maintenance Ratio too low.

Is Impacted By:

• High percentage of unscheduled repairs.

• MTBS (too low).


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• Inadequate Condition Monitoring.

• Poor Planning & Scheduling.

• Insufficient resources (shop bays, tooling, equipment, etc.).

•

Inadequate training.


Plotting monthly Maintenance Ratio versus time over a twelve-month period on an X-

Y line graph is the most effective method to demonstrate trends in Maintenance

Ratio. Overlaying the Maintenance Ratio graph with the Percentage of ScheduledDowntime and MTBS is the most graphic method to determine which factor is

driving the end result.

Figure 7: Maintenance Ratio trend

Maintenance Ratio

793 OHT Fleet

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

J un -9 9 J ul -9 9 Au g-9 9 S e p- 99 O ct- 99 No v-9 9 De c-9 9 J an -0 0 Fe b-0 0 Ma r-0 0 Apr-0 0 Ma y-0 0

Month/ Year

" C h a r g e d " M a i n t e n a n c e R a t i o

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

" O v e r a l l " M a i n t e n a n c e R a t i o

BenchmarkRange

4.1.7. Top Problems / Pareto Analysis

Definition:

The distribution of problems affecting a fleet of equipment ranked in terms of MTBS,

MTTR, impact on Availability and Costs.


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Description:

All mining support operations have limited resources. The most successfuloperations are those that have a clear understanding of the problems and issues facing

them and are thus in a position to establish priorities in order to focus their efforts and

allocate the appropriate resources on remedial or containment strategies throughcontinuous improvement. The identification and quantification of top problems by

component (e.g. engine, transmission, …), system (e.g. hydraulics, electrical, …) or

even process (e.g. PM) facilitates the understanding of the extent that each area ishaving an influence on various criteria that comprise the success of a mining support

operation, i.e. shutdown frequency (MTBS), shutdown duration (MTTR), impact on

Availability and Costs. With this knowledge the Project Manager is able to “drilldown” to the key issues facing his site and apply the necessary resources in the most

efficient manner to improve his situation.


Data Source(s):

Operating hours are obtained from machine service meter reading. Note, hours

obtained from dispatch systems frequently do not agree with machine SMR due tocoding of production delays, etc.

Shutdown count is obtained from machine workorder history and dispatch system.Dispatch information must be used to account for shutdown events that are not

accounted for by a workorder. Shutdown count must be determined individually for

each area of the machine as well as for the machine as a whole in order to assess notonly the contribution of each area but also to calculate Availability Index.

Downtime hours obtained from machine workorder history and dispatch system.Dispatch information must be used to account for downtime that is not accompanied

MTBS (by system) = Operating Hours

Number of Shutdowns (by system)

MTTR (by system) = Downtime Hours (by system)

Number of Shutdowns (by system)

Impact on Availability (by system) = (1 – Availability (total machine)) X Downtime Hours (by system)

Total Downtime Hours (machine)

Cost per Hour (by system) = Cost (by system)

Operating Hours

(10)

(8)

(7)

(9)


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by a workorder. It is essential to note that repair delay times should be included in

the downtime history calculation. If delay times are known, MTTR should becalculated both with and without delays. As is the case with shutdown count,

downtime must be determined individually for each area of the machine as well as the

machine as a whole in order to assess the contribution of each area.

Total cost to support and maintain each of the systems and components on the

machine. At a minimum it is vital to know the breakdown for costs of repairs and

rebuilds of each major component on the machine. Most recordskeeping systems wehave studied do a fairly poor job of documenting costs but if Project Management is

to have any opportunity to manage contract profitability, costs must be known.

Benchmarks:

There is no set of Benchmarks that is applicable to this metric. However, over thecourse of investigation during EMR’s we developed a collection of generic reference

guidelines for large Off Highway Trucks in the 785 – 793 size class that can be used

as a gauge to evaluate MTBS, MTTR and impact on Availability. This referencedefines what we believe to be a reasonable level of acceptability for frequency of

downtime events (MTBS), duration of downtime events (MTTR) and impact on

Availability for each of the major areas on the machine.

The data is representative of a site operating at an Availability Index ofapproximately 90% and is, of course, generic since actual results achieved at any

given mine are site-specific because results of this kind are a function of not only

application severity but also of the operating environment, the maintenance theequipment receives and product design shortcomings that are particular to machines

either by model or within a given range of serial numbers.

Appendix 5.2, “Generic Pareto Reference – Large Off Highway Trucks” should beused as a baseline until Project Management can use individual site experience and

history to determine how this reference can be modified to fit the application inquestion.

Since there are many factors other than equipment management that influence costs(labor rates, transportation costs, import duties, taxes, etc.), it is impossible to define

Benchmarks that are universally applicable to any given machine model. This being

the case, we recommend that budgetary cost and component life projections be usedto define target cost per hour figures and that actual cost performance be compared to

those targets in order to determine if any particular area is out of line with

expectations.

Usage:

Using the top problems distribution analysis enables Project Management to identifyand prioritize critical issues affecting success of the project for investigation and

resolution. The Pareto principle tends to hold true and we typically find that a


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relatively small minority of potential issues is causing the overwhelming majority of

the grief on a project.

The output of this analysis should be viewed as input for the continuous improvement

process. As such, resources can be applied in the areas that will derive the maximum

benefit.

Interpretation:

In order to properly prioritize the four criteria each should be compared to some baseline of performance. MTBS, MTTR and Availability can be evaluated relative to predicted levels or acceptable historical data. If neither is available, the Project

Manager can use the generic set of guidelines defined in the “Benchmark” section

above until a set of references can be developed for his site.

MTBS and MTTR for each area under investigation should be viewed as the ratio oftarget to actual demonstrated performance. In other words, if the MTBS (reliability)

for a particular area of a machine is significantly lower than expected or if MTTR ishigher, that area should be designated for analysis and investigation.

It is also very important to note that experience has shown that a relatively high

percentage of shutdowns of very short duration occur on many sites. We frequentlysee that 40 to 50% of all machine stoppages are one hour or less in duration. While

our instincts tell us to attack the “big hitters”, it is critical and highly beneficial to

identify and correct these repetitive issues since they occur so frequently that their

influence on the end results can be very significant.

Availability for each area under investigation should be viewed as the difference

between target and actual demonstrated performance. That is, if the actual impact on

availability for a particular area of a machine is significantly higher than expected,that area should be designated for analysis and investigation.

Cost data should be evaluated relative to budgetary cost calculations. Just as with the

impact on availability, the difference between actual and budgeted costs is the criteria

for selection.

When reviewing the list of potential issues for nomination onto the top problemssummary, it is important to consider not only the problem itself but also the

consequences of failure related to the problem. For example, an excessive number of

coolant leaks when taken alone may be looked upon as more of a nuisance itemhowever when one considers the consequences of failure and the potential for engine

overheating and subsequent reduction in engine life, the issue becomes far moreserious.

Action:

• Once the top problems have been identified by component and system,

machine repair history should be reviewed to determine the nature of the

problems within each of those components and systems. In most instances we


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find that the key specific issues result from a relatively small percentage of

machines and a small number of causes.

• Submit the top problems to the Continuous Improvement process to determine

root cause and identify the containment and resolution strategy.

• Compare the top problems at the site to those listed in the Caterpillar CPI process as well as those covered under factory PIP/PSP programs. If the top

problems at the site do not align reasonably well with the list of global issues,

it is likely that the root cause is a result of site-specific conditions related toapplication and/or maintenance. Specific problems should be submitted to the

Caterpillar CPI process for consideration and investigation.

Has Impact On:

• Costs, ... operating costs can be better managed and contained when key problems are known and can be effectively dealt with via the continuous

improvement process.

• Manpower requirements, ... manpower can be deployed more effectively and

efficiently when top problems are identified and understood. Using intuition

(guessing) results in excessive expenditures of labor.

• Availability / reliability, … optimum availability and reliability can be

achieved when key issues are known and given appropriate attention for

resolution.

Is Impacted By:

•

Maintenance strategy, … a repair-before-failure strategy focused on earlydetection and failure avoidance plays a fundamental role in problem

management, i.e. Condition Monitoring (quality and quantity of inspections),Planning & Scheduling, Backlog Management, etc.

• Maintenance execution, … resources (facilities and manpower) in adequate

numbers and of sufficient quality have a direct influence on the end results.

• Application severity, ... drives the results e.g. excessive fuel burn rate will tend

to magnify engine-related downtime, overloading will accelerate power trainand structural deterioration, etc.

•

Operating environment, ... haul road conditions, ambient temperature extremesand precipitation all have a role in determining which areas on the machine

will experience problems.


Charts and graphs can be used to analyze top problems but they tend not to be veryvisual and typically become e

cat performance metrics for mobile mining equipment version 1.1.pdf

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