metrics (kpi's) to assess process performance

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Mining Equipment Maintenance & Repair Processes

METRICS (KPI’S) TO ASSESS PROCESS PERFORMANCE

Abelardo A. Flores James W. McCaherty

Revision #03 – March 27, 2007




Introduction

The primary goal and responsibility of the Maintenance Department is to maintain equipment in optimum condition via problem / failure avoidance. One of the key tools of the Maintenance Department is performance measurement. In order to be effective, performance measurements should give us not only an accurate picture of how we are performing relative to established targets and/or global benchmarks but also provide us with a prediction or projection as to what we can expect in terms of future performance.

In spite of the fact that it is human nature to want to report good news, the most valuable performance measures assist us in the identification of weak areas, poor practices and other opportunities for improvement. Therefore, it behooves us to take a critical look at our performance via an honest assessment of that performance. Only in this way are we able to correct small issues before they become major problems. The collection of performance measures included in this document help us to identify and understand on-site performance issues related to project health and maintenance / repair process performance in support of that project. In doing so we are also able to gain some insight into related issues such as application severity, operating practices, contract guarantees / commitments, and contract financial health.

“Performance Metric” is a term used to describe the outcome of any process used to collect, analyze, interpret and present quantitative data. It is a measurement parameter that enables performance against some pre-defined Target or Benchmark to be monitored … a measurement used to gauge performance of a function, operation or business relative to past results and projected future behavior.

“Benchmark” is another term frequently used to describe performance. Benchmark is defined as a world-class performance standard relative to a specific performance metric. A Benchmark represents and quantifies "world-class performance or best practice" of an operation or of specific functions within that operation according to a specified performance metric. A benchmark is determined by and represents actual, documented, sustainable performance over time relative to some performance metric.




Caterpillar has invested a great deal of time, energy and resources identifying and developing several metrics of performance that quantify and trend product and project health. Based on that experience we have been able to document actual site performance in many of those areas and feel very confident representing some of those results as Benchmarks.

Unfortunately, the overwhelming majority of that effort has been concentrated on fleets of large Off Highway Trucks. Therefore, most of the Benchmarks used in this document are specific to those fleets. When we have felt comfortable in doing so, we have also cited our best estimates of what those Benchmarks might be for other mining equipment if we had access to a significant sample of data for those machines. In situations where we do not have that same level of confidence, we have made that clear as we do not care to mislead the user by speculating.

The metrics contained herein will provide insight into the performance of the individual Maintenance & Repair Processes and their contributions to the end results. Those metrics are organized as follows:

1. - Fleet Performance Metrics

2. - Maintenance & Repair Processes Metrics

2.1 - Preventive Maintenance

2.2 - Condition Monitoring

2.3 - Backlog Management

2.4 - Planning and Scheduling

2.5 - Parts Management

2.6 - Repair Management

2.7 - Component Management

2.8 - Human Resources - Training

2.9 - Continuous Improvement




1.1 Fleet Performance Metrics

The following measures are “Top Tier” performance metrics or Key Performance Indicators (KPI’s) that enable management to quantify, assess and monitor product health and site performance.

1.1.1 - Mean Time Between Shutdowns (MTBS)

Definition:

The average operating time between machine stoppages … a function of the average frequency of equipment downtime events, expressed in hours. Calculation Methodology:

Description:

MTBS is a measure that combines the effects of inherent machine reliability and the effectiveness of the equipment management organization in its ability to influence results through problem avoidance.

Data Source(s):

Operating hours obtained from machine service meter reading. 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. Note: Production delay hours may not be tracked and accounted for separately and are therefore 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 not accompanied by a workorder.

MTBS = Operating Hours Number of Shutdowns (hours)




Benchmarks & Targets:

MTBS benchmarks vary significantly by machine model, their relative size, age and design “maturity” and complexity. MTBS for large Off Highway Trucks in the 785 – 793 size class is very well documented. The benchmark for a fleet of new trucks is 80 hours; that of a “mature” fleet (one that has undergone its first round of major component rebuilds) is 60 hours.

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 represents our best judgment in this area.

MTBS Assessment / Characteristics

50 to 60 hours

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

40 to 50 hours Acceptable; majority of downtime is scheduled; substantial emphasis on Equipment Mgmt.

30 to 40 hours

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

20 to 30 hours Fair; < 40% downtime is scheduled; minimal effort on Equipment Mgmt.

< 20 hours Poor; only PM’s are scheduled; Equipment Mgmt. organization is purely reactive.

Table 1: Site performance through range of MTBS

Benchmarks for trucks smaller than the 785 and the 797 are less well known although it is believed that MTBS for trucks in the 769 – 777 size class will be significantly higher (as much 30 to 40%) while that of the 797 will be perhaps 10% lower.

Similarly, benchmarks for other large mining equipment are not well documented. However, indications are that once MTBS data is collected, analyzed and validated, the results will fall into the following ranges:

Machine / Model MTBS

D10 / D11 TTT’s 55 to 75 hours

992 / 994 WL’s 55 to 75 hours

16 MG 95 to 105 hours

24 MG 55 to 75 hours

5000 HEX 55 to 75 hours

Table 2: MTBS guidelines for mining machines




1.1.2 - Mean Time To Repair (MTTR)

Definition:

The average downtime for machine stoppages … the average duration of equipment downtime events, expressed in hours. Calculation Methodology:

Description:

Mean Time To Repair (MTTR) is a performance measure that quantifies repair turnaround time, i.e. how quickly (or slowly) a machine is 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 the execution 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 that are not accompanied by a workorder. Benchmarks & Targets:

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 3 to 6 hours. MTTR for new trucks should

MTTR = Total Downtime Hours

Number of Shutdowns (hours)




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 relative complexity of the repairs seen on new versus “mature” machines.

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.

1.1.3 - Percentage Scheduled Downtime

Definition:

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

Description:

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.

% Scheduled Downtime = Scheduled Downtime Hours

Total Downtime Hours X 100 (%)




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. Benchmarks & Targets:

% Scheduled Downtime Hours 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 execute 80% of its maintenance and repair downtime activity on a scheduled basis. We believe that this criterion holds true for other mining equipment as well however requirements for less utilized, non-production equipment may be somewhat less.

1.1.4 - Contractual Availability

Definition:

The ratio of time that a machine is capable of functioning in the intended operation (available hours) to total hours in the period under consideration (typically either based on calendar or scheduled hours), expressed as a percentage. The calculation of available hours is not a pure calculation since the result is amended by downtime hours that are specifically excluded or limited by the terms of the contract. Calculation Methodology:

*NOTE: “Total Hours” are typically either based on calendar or scheduled hours depending upon the calculation methodology defined in the agreement or customer expectations.

Total Hours * - MARC Downtime Hours

Total Hours *

Contractual Availability

X 100 = (%)




Description:

Contracts are written largely to ensure that production equipment is available for operation a sufficient number of hours to enable the mine to meet its production goals at a reasonable, predetermined operating cost. The specific provisions of a contractual availability guarantee vary significantly from site to site, i.e. time that the contractor will be given credit for (available hours), time that the contractor will be held accountable for (contractual downtime), as well as specific exclusions, e.g. tires, dump bodies, welding, etc. are defined in detail in the contract. Furthermore, contracts frequently specify caps or limits on downtime that apply to things such as delays waiting on facilities, repair equipment and or other support infrastructure that the contractor is not expected to provide and has little control over. Because these exclusions and limitations vary so widely from one site to the next, it is not possible to link performance in this area to any kind of Benchmark nor does it make any sense to attempt to make comparisons from one site to the next. Target performance should be compliance with the provisions defined within the contract or, in the absence of a contract, with customer expectations. Data Source(s):

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.

If the available hours calculation involves the combination of operating hours, stand-by hours, production delay hours and operational delay hours (as it does in many instances), that information can be obtained from the machine service meter reading and information coded within the dispatch system.

MARC downtime hours are obtained from the machine workorder history as well as the dispatch system. Dispatch information must be used to account for downtime that is not accompanied by a workorder. It is essential that the machine repair history contain detail sufficient to determine if individual downtime events are excluded from the MARC downtime calculation. Benchmarks & Targets: There is no Benchmark that is applicable to the Contractual Availability performance metric. Target performance should be compliance with the




provisions defined within the contract or, in the absence of a contract, with customer expectations.

1.1.5 - Availability Index

Definition:

The ratio of MTBS (average shutdown frequency) to the sum of MTBS and MTTR (average shutdown duration), expressed as a percentage. Calculation Methodology:

Description:

Availability is the result of the frequency and duration of downtime events (shutdowns). Because of the mathematical relationship between MTBS, MTTR and Availability Index, the result shows which of the other two factors had the greatest influence upon that result. 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 those two metrics are applicable here as well. Benchmarks & Targets:

Availability Index benchmarks vary significantly by machine model, their relative size, age and design “maturity” and complexity. Availability Index for large Off Highway 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 although it is believed that the Availability Index for trucks in the 769 – 777

Availability Index = MTBS

MTBS + MTTR X 100 (%)




size class will be somewhat 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 smaller machines, e.g. 16H, being 1 or 2% higher.

1.1.6 - Maintenance Ratio

Definition:

Maintenance Ratio is a dimensionless ratio of maintenance and repair man-hours to machine operating hours. Calculation Methodology:

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 be calculated 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 and idle time. Data Source(s): Maintenance and repair man-hours are obtained from the work order history. The result 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 support equipment, decision making, etc.

Maintenance & Repair Man-Hours

Operating Hours Maintenance Ratio charged =




Operating hours are obtained from machine service meter reading and once again should include production delay hours. Note, hours obtained from dispatch systems frequently do not agree with machine SMR due to coding of production delays, etc.


Maintenance Ratio benchmarks vary significantly by machine model, their relative size, age and design “maturity” and complexity. Maintenance Ratio for large Off Highway 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 be slightly 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 and validated, 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 as either production or support equipment. (Refer to table 4 below).




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

1.1.7 - Top Problems Summary

Definition:

The distribution of problems affecting a fleet of equipment ranked in terms of MTBS, MTTR, impact on Availability and Costs. Calculation Methodology:

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

Total Downtime Hours (machine) (%)

MTBS (by system) = Operating Hours

Number of Shutdowns (by system) (hours)

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

Number of Shutdowns (by system) (hours)

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

Operating Hours (US & / hour)




Description:

All mining support operations have limited resources. The most successful operations 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 through continuous 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 is having 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 “drill down” 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 to coding 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 not only 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 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 be calculated 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 we have 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 & Targets:

There is no set of Benchmarks that is applicable to this metric. However, over the course 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 reference defines 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 of approximately 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 the equipment receives and product design shortcomings that are particular to machines either by model or within a given range of serial numbers.

The “Generic Pareto Reference – Large Off Highway Trucks” included in the Appendix can be used as a baseline until Project Management has sufficient individual site-specific experience and history to determine how this reference can be modified to fit the application in question. 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 used to 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.

1.1.8 - 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.




Calculation Methodology:

Description:

How effectively the Operations Department schedules equipment and efficiently it utilizes that equipment has significant implications for Maintenance. If machines are scheduled 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 typically occur 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 are working together toward common goals … high availability, good machine reliability and the lowest possible cost per unit of production.

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.


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 per year. We believe that this Benchmark is valid for other production mining equipment however the Benchmark for less utilized, non-production equipment, although unknown, may be significantly less.

Asset Utilization = Operating Hours

Total Calendar Hours X 100 (%)




1.1.9 - PIP / PSP Completion Rate

Definition:

A tracking tool used to monitor the status of implementation of factory programs. Calculation Methodology:

Factory program completion status is calculated as the ratio of programs completed on a machine-by-machine basis relative to the number of programs that are active and applicable at the time under consideration. This ratio should be expressed as a percentage. Programs that are defined as "after failure" should not be included in the calculation.

Data Source(s):

Factory programs are received on site via the dealer Technical Communications staff and include all of the information necessary to determine applicability and monitor their completion status, i.e. program identification number, dates of issue and termination, and program type. Machine serial number and hourmeter information obtained from the machine history at the site. Benchmarks & Targets:

Since factors such as parts availability can impact on management's ability to complete a program and in some cases program execution can be delayed to coincide with other related work (which may be a valid decision on the part of management), there is no Benchmark that is applicable to this metric. However, compliance with this discipline is viewed as critical to the success of a project and common sense would dictate that a higher percentage of completion of outstanding programs is desirable. Clearly, no program should be permitted to run beyond its termination date without being addressed unless it is an after failure only program.

2.1 Preventive Maintenance

The following metrics are indicators of the performance and / or contributions of the Preventive Maintenance process to the end results of the project, i.e. equipment reliability and availability.




2.1.1 - MTBS after PM

The average operating hours to the first stop after each PM service is a valid indication of PM quality and effectiveness. The Benchmark (best in class) for large Off Highway Trucks is 105 hours; a realistic target is 2 to 3 times the overall MTBS. Tracking and trending this metric monthly offers a reasonable representation of PM quality and effectiveness.

2.1.2 - Unavailability PM Unavailability due to Preventive Maintenance quantifies the impact of PM on availability. There is no Benchmark associated with this metric but a reasonably valid target is in the range of 2.75 to 3.25% for large Off Highway Trucks in the 785 – 793 size class.

The result of this measure should be taken in context with MTBS after PM. If unavailability due to PM is below the range and MTBS after PM is low, it is a safe assumption that insufficient time and effort is being placed on PM. Conversely, if unavailability due to PM is above the range and MTBS after PM is high, one can assume that the site is placing substantial emphasis on the value of PM.

2.1.3 - MTTR PM The average downtime hours dedicated to PM is an indication of PM efficiency. There is no Benchmark associated with this measure but a reasonable target is in the 7.75 to 8.5 hour range for large Off Highway

Unavailability PM = Total Downtime Hours

PM Downtime Hours X 100(1 - Availability) X (%)

Number of PM Services MTBS after PM =

Total Operating Hours to First Stop (hours)

Number of PM Services MTTR PM =

Total PM Downtime Hours (hours)




Trucks that are on a 250 hour PM service interval. The target for equipment that is on a 500 hour PM service interval is higher, i.e. double that of the 250 hour interval. Once again, if average PM downtime is the range, it may indicate and MTBS after PM is low, it is a safe assumption that insufficient time and effort is being placed on PM. Conversely, if average PM downtime is above the range and MTBS after PM is high, one can assume that the site is placing substantial emphasis on the value of PM. Additionally, one should consider the impact of efficiency factors such as facilities, tooling, training, planning & scheduling, etc. when assessing MTTR PM.

2.1.4 - Service Accuracy

A measurement of Preventive Maintenance execution timeliness based on a statistical calculation that predicts the probability that the next PM service will occur within the recommended range (+/- 25 hours of target interval). The calculation is based upon past performance and assumes that PM intervals are normally distributed about the mean. The Benchmark for S.A. is 95% but an aggressive target that will yield excellent results is 90%.

2.1.5 - Backlogs executed during PM

Backlogs executed during Preventive Maintenance is a good indication of how well the organization is using the “window of opportunity” presented by PM to maintain the equipment at a standard that will enhance product reliably. There is no Benchmark or target for this measure.

2.1.6 - Backlogs generated during PM

The number of defects identified and entered into the Backlog Management system during the execution of Preventive Maintenance. Since this measure is a direct function of the number of machines being monitored as well as their condition, no Benchmarks or targets are applicable. Backlogs generated during PM quantifies the use of the “window of opportunity” presented during the PM shutdown for defect detection (an element of Condition Monitoring).




2.2 Condition Monitoring

The following metrics are indicators of the performance and / or contributions of the Condition Monitoring process to the end results of the project.

2.2.1 - Mean Time Between Failures (MTBF) The average operating time between equipment failures; the inverse of failure frequency, expressed in hours. Failures may be the result of technical product issues, i.e. equipment unreliability, or due to maintenance / repair neglect, i.e. equipment management ineffectiveness in the area of problem avoidance. We have not established a Benchmark for MTBF and do not have sufficient confidence at this time to provide a reasonable target. (Please see the Glossary for our definition of equipment Failure.)

2.2.2 - Unavailability Unscheduled

Unavailability due to unscheduled downtime quantifies the impact of unscheduled events on availability. There is no Benchmark associated with this metric but a reasonably valid target is < 2% for large Off Highway Trucks in the 785 – 793 size class. If unavailability due to unscheduled downtime is significantly higher than 2%, it is reasonable to assume that gaps exist in the detect-plan-execute cycle therefore improvements to the Condition Monitoring, Planning & Scheduling and/or repair execution areas will be necessary. Increasing unavailability due to unscheduled downtime is a valid predictor of pending problems and may very well predict future shortages of manpower and facilities.

MTBF (Mean Time Between Failures)

= Number of Failures

(hours)Operating Hours

= (1 Total Downtime

Unscheduled DowntimeX 100 (%)– Availability) XUnavailability U/S




2.2.3 - Failure Reduction Failure Reduction is a means of quantifying the impact of Condition Monitoring in its efforts toward failure / problem avoidance. Since unscheduled events are inherently more difficult and inefficient to deal with in terms of the time required to make unscheduled (unplanned) repairs, Failure Reduction should be the primary focus of Condition Monitoring activities. Because the opportunity to improve in this area is highly dependent upon the amount of unscheduled downtime taking place at the site, there is no Benchmark or target for Failure Reduction. In any event, the result should be positive indicating a decline in the percentage of unscheduled downtime.

2.2.4 - Condition Monitoring Total Savings

Condition Monitoring Total Savings defines the “Value Proposition” for Condition Monitoring. In other words, the total savings generated by Condition Monitoring (cost of after-failure repairs – cost of preventive, before-failure repairs) must be greater than the cost of implementation and execution of the Condition Monitoring program. There is no Benchmark for this metric but the target should be a positive value (net savings as a result of Condition Monitoring).

2.2.5 - Total Backlogs Generated

The number of defects identified and entered into the Backlog Management system during a specified period (typically one month). This metric assesses the Condition Monitoring effort in and ability to successfully detect potential problems before failure. Since this measure is

Unscheduled hours(6 month rolling average)

Failure Reduction (FR)

=

Unscheduled hours(6 months RA)

X 100 (%)

_ Unscheduled hours(last month)

–CM Cost Saving CM Total Savings = CM Program Cost (US$ )

Backlogs Generated = Total Backlogs Generated in the Period (Total)




a direct function of the number of machines being monitored, there is no Benchmark or target.

2.2.6 - Working on Target

The percentage of Backlogs generated which address issues that appear on the “Top 10” historical problem list. The result yields the % of Condition Monitoring actions that are “On Target” relative to the key issues affecting site performance. There is no Benchmark or target for this metric however, if all issues on the problem list are not producing Backlogs, the Condition Monitoring effort may be misdirected.

2.2.7 - Backlogs Generated by Origin

Backlogs Generated by Origin identifies which areas that are or are not contributing to efforts by Condition Monitoring in failure detection. There is no Benchmark for Backlogs Generated by Origin, however, if the quantity of Backlogs generated by operators, inspectors, the PM crew, the shop crew, etc is low, additional emphasis should be placed on the offending party(s) to encourage their participation in the defect detection process. Conversely, if the percentage of “shop-found” defects is disproportionately high, the other areas must be encouraged to increase their involvement since “shop found” defects are typically far less efficiently executed due to the inability to plan the workload. There are no Benchmarks or targets related to this metric.

2.2.8 - Detection Level

Working on Target = % Backlogs on Problem List

Backlogs Generated (by Origin)

= Backlogs Generated in the Period by area of origin

Potential Failure Detection (PFD)

= Total defects pending

Recorded Backlogs X 100 (%)




This metric is based on a comparison between the number of Backlogs recorded in the system and the defects that can be detected in an inspection of a randomly selected sample of machines (10% of total fleet at minimum). Although inspections are limited to visual inspection, the Potential Failure Detection level can be used to assess the level of detection of Condition Monitoring.

2.3 Backlog Management

The following metrics are used to evaluate the ability of the Backlog Management process to prioritize, control and manage problems identified through Condition Monitoring such that they do not result in unnecessary downtime.

2.3.1 - Total Backlogs Pending

The total number of defects identified by Condition Monitoring and pending in the Backlog Management process. An indication of the pending workload and risk for failure. Since this number is dependent upon the size of the fleet being managed, there is no Benchmark or target for this metric.

2.3.2 - Backlogs Pending by Machine

The total number of defects per machine identified by Condition Monitoring and pending in the Backlog Management process. There is no Benchmark for this metric, however a reasonable target is that there should be no more than five pending Backlog repairs per machine.

2.3.3 - Total Backlogs Generated

The number of defects identified and entered into the Backlog Management system during a specified period (typically one month). This metric assesses the Condition Monitoring effort in and ability to successfully detect potential problems before failure. Since this measure is a direct function of the number of machines being monitored, there is no Benchmark or target. Backlog generation should be viewed in the context of % scheduled downtime and, if the percentage of scheduled downtime

Backlogs Generated = Total Backlogs Generated in the Period (Total)




is low, the total number of Backlogs generated should be correspondingly high.

2.3.4 - Total Backlogs Executed

The number of Backlog repairs performed during a specified period (typically one month). This metric evaluates the ability of the maintenance organization to react appropriately to correct defects identified through the Condition Monitoring process. Since this measure is related to the number of Backlogs in the system, there is no Benchmark or target, however, there should be a balance between the number of Backlogs generated and executed.

2.3.5 - Estimated Labor To Repair

The total estimated repair labor man-hours required to execute all of the pending Backlogs that have been generated. This metric is an indication of severity of the Backlog workload and the potential availability lost if manpower resources are insufficient to accomplish the task at hand. There is no Benchmark for this metric but a reasonable target is that the total estimated repair labor man-hours required to clean up the Backlog list should be < 5% of available man-hours labor for the month.

2.3.6 - Backlog Status Summary The Backlog Status Summary defines the number of pending Backlogs that are waiting for planning (“Red phase”), waiting for parts / resources (“Blue phase”), and waiting to be executed (“Green phase”). There is no Benchmark or target for the Backlog Status Summary however this metric analyzed to identify any weak area(s) in the detect-plan-execute cycle that may be delaying the Backlog repair execution process.

2.3.7 - Backlogs > 30 Days Old

Measured from the date the Backlog was generated, this metric assesses the quality and timeliness of the response of the Backlog Management system in its ability to respond proactively to eliminate potential problems. It is important to note that Backlogs are potential failures, thus Backlog

Backlogs Executed = Total Backlogs Executed in the Period (Total)




age is an indication of the risk of failure that a site is under. There is no Benchmark for this measure however an aggressive target is that no Backlogs are greater than 30 days old.

2.4 Planning and Scheduling The following metrics are used to evaluate how well the Planning and Scheduling process is organized and functioning to ensure that planned activities can be accomplished both efficiently and effectively and that they do not result in unnecessary downtime.

2.4.1 - Percentage Scheduled Downtime

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.

The Benchmark for percentage of scheduled downtime is 80% of maintenance and repair downtime activity is executed on a scheduled basis. A reasonably aggressive target for most sites is 60%.

2.4.2 - Schedule Compliance by Hours

Schedule Compliance (by hours) is the ratio of scheduled Preventive Maintenance and repair downtime hours actually executed to the Preventive Maintenance and repair downtime hours scheduled. There is no Benchmark for this metric but the target should be in the range of 90 to

% Scheduled Downtime = Scheduled Downtime Hours

Total Downtime Hours X 100 (%)

Schedule Compliance = (by hours)

Scheduled PM & Repair Hours Executed PM & Repair Hours Scheduled

X 100 (%)




100%. If the result is consistently 100%, it may be an indication that the schedule is too conservative (does not provide sufficient “stretch”. Conversely, if the result is consistently low, it could mean that the schedule is too ambitious, the workforce is inefficient, or that the amount of unscheduled downtime during the period was such that it interfered with work that had been previously scheduled.

2.4.3 - Schedule Compliance by Events Schedule Compliance (by events) is the ratio of scheduled Preventive Maintenance and repair events actually performed to the Preventive Maintenance and repair events scheduled. Once again, there is no Benchmark for this metric but the target should be in the range of 90 to 100%. Just as was the case for Schedule Compliance by hours, if the result is consistently 100%, it may be an indication that the schedule is too conservative (does not provide sufficient “stretch”. Conversely, if the result is consistently low, it could mean that the schedule is too ambitious, the workforce is inefficient, or that the amount of unscheduled downtime during the period was such that it interfered with work that had been previously scheduled.

2.4.4 - Components Exchanged (scheduled)

Components Exchanged is the ratio of component replacements scheduled and actually replaced to components replacements scheduled. There is no Benchmark for this metric but the target should be 100%.

2.4.5 - Estimated Time To Repair Pending Backlogs

The total estimated repair downtime hours required to execute all of the pending Backlogs that have been generated. At the time a repair request is entered (Backlog generated) the Estimated Time to Repair (ETTR) must

Schedule Compliance = (by events)

Scheduled PM & Repair Events Executed PM & Repair Events Scheduled

X 100 (%)

Components Exchanged =

PCR’s Scheduled & Executed PCR’s Executed X 100 (%)




be identified to permit effective planning of required corrective actions. This metric is an indication of extent of the Backlog workload and the potential availability lost if resources are insufficient to accomplish the task at hand. There is no Benchmark or target for this metric; it serves as a tool for the Planning process to enable it to “manage” availability by scheduling work in such a way that the availability goal can be met.

2.4.6 - Estimated Time To Replace Overdue Components

The total estimated repair downtime hours required to replace all overdue components. Standard jobs for component replacement will forecast the estimated time to replace each component. This metric is an indication of extent of the component replacement workload and the potential availability lost if resources are insufficient to accomplish those tasks. There is no Benchmark for this metric but a reasonable target is that the downtime required for component replacement should not result in more than 2% unavailability. It is important to note here that since fleets tend to come due for component replacement in “batches”, thus this metric is highly variable and must be looked at over the long-term … 12-24 months. Just as with the ETTR for Backlogs, this measure serves as a tool for the Planning process to enable it to “manage” availability by scheduling work in such a way that the availability goal can be met. 2.4.7 - Estimated Time To Execute Factory Programs

The total estimated repair downtime hours required to perform all overdue factory programs, i.e. PIP & PSP’s. The program will typically define the estimated time to execute each program. This metric is an indication of extent of the program execution workload and the potential availability lost if resources are insufficient to accomplish those tasks. There is no Benchmark for this metric but, if one assumes that program execution is relatively current, a reasonable target is that the downtime required for component replacement should not result in more than 1% unavailability. It is important to note that since programs are generated to cover fleets of equipment, those programs tend to come in “batches”, thus this metric is highly variable and must be looked at over the long-term … 6-12 months. Just as with the ETTR for Backlogs and component replacement, this measure serves as a tool for the Planning process to enable it to “manage” availability by scheduling work in such a way that the availability goal can be met.




2.5 Parts Management

The following metrics are used to determine how well maintenance activities are supported by the parts inventory and evaluate the relationship between the Parts, Planning & Scheduling and Maintenance Departments in their efforts to avoid unnecessary parts-related downtime.

2.5.1 - Warehouse Service Fill Level (instantaneous)

Instantaneous Service Fill Level is a parts management efficiency indicator that quantifies the percentage of individual parts requests entered against the on-site parts warehouse for repairs (including Backlog parts requests) and filled / closed at the first call. A reflection of the level of satisfaction of on-site parts warehouse performance. The Benchmark for Instantaneous Service Fill Level is 95%. An aggressive target is > 90%.

2.5.2 - Service Fill Level (24 hours)

Service Fill Level after 24 hours is a parts management efficiency indicator that quantifies the percentage of individual parts requests entered against the on-site parts warehouse for repairs (including Backlog parts requests) and filled / closed in the first 24 hours after the first call. A reflection of the level of satisfaction of on-site parts warehouse performance. We do not have sufficient data to define a Benchmark but an aggressive target is 100%.

2.5.3 - Unavailability Parts

= (1 Total Downtime

Parts Delay Downtime X 100 (%)– Availability) XUnavailability PD

Service Fill Level = (instantaneous)

Parts Orders Closed at 1st Request Total Parts Orders X 100 (%)

Service Fill Level = (after 24 hours)

Parts Orders Closed in 1st 24 Hours Total Parts Orders X 100 (%)




Unavailability due to parts delays quantifies the impact of parts delay events on availability. There is no Benchmark associated with this metric but a reasonable target is < .5%. If unavailability (downtime) due to parts delays is significantly higher than .5%, it may signify potential problems with inventory quality / quality and/or a higher than normal percentage of unplanned downtime, i.e. the inability of the maintenance organization to detect problems in advance of failure and plan & schedule the work and associated resources accordingly. If parts inventory quality / quality is found to be an issue, it may be due either to the fact that the maintenance organization is not doing a good job of defining the parts inventory support requirements to the Parts Department or that the Parts Department is not delivering on its obligation to support the site with the required parts.

2.5.4 - Emergency Response Time

Emergency Response Time quantifies the average response time (in days) to satisfy parts requests that cannot be filled instantaneously. This parameter works and should be analyzed in conjunction with Instantaneous Service Fill Level. There is no Benchmark or target for this metric.

2.5.5 - Parts Inventory Rotation

Parts Inventory Rotation is defined as the annual turnover of parts held in the on-site parts warehouse. No Benchmark is available for this parameter. Defining a realistic target for this metric is highly dependent upon site logistics of the specific operation including transportation, the capacity and design of the parts warehouse, the remoteness of the site, costs associated with carrying the inventory and the specific requirements of the site in terms of any availability guarantees that may be in place.

2.5.6 - Emergency Orders

Emergency Orders quantifies the percentage of parts orders that are placed against the system on an emergency basis, i.e. “panic mode”. The percentage of Emergency Orders is another method of analyzing the extent to which the maintenance organization is behaving pro-actively and control of the fleet. There is no Benchmark or target for this metric.




2.5.7 - Inventory (items)

This metric quantifies the number of individual line items maintained on-site in the parts inventory. Because this is proportional to the size of the fleet being supported, there is no Benchmark or target for this metric. Trending inventory levels over a 6 to 12 month period and relating the trend to fleet performance results such as MTBS, MTTR and % of scheduled work, is one way of determining the impact of parts support on the overall site performance.

2.5.8 - Inventory (value)

This metric quantifies the value of the on-site parts inventory. Here again, because this is proportional to the size of the fleet being supported, there is no Benchmark or target for this metric. Trending inventory value over a 6 to 12 month period and relating the trend to fleet performance results such as MTBS, MTTR and % of scheduled work, is one way of determining the impact of parts support on the overall site performance.

2.6 Repair Management

The following Repair Management metrics are indicators of the adequacy of the maintenance personnel, facilities, tooling and support equipment and how well those resources are organized and managed to perform efficient & effective repairs while contributing to efficiency, cost and availability objectives.

2.6.1 - MTTR (shop service)

The average downtime hours (including delays) required to execute shop repairs. There is no Benchmark or target associated with this measure. Actual results will vary significantly based upon the nature of the repair, whether it is scheduled or unscheduled and the extent to which repairs are grouped for optimum efficiency.

Number of Shop Repairs MTTR shop =

Total Shop Repair Downtime (hours)




2.6.2 - MTTR (field)

The average downtime hours (including delays & response time) required to execute field repairs. There is no Benchmark associated with this measure but a reasonable target is <1 hour. It should be noted here that the field service crew is the “first line of defense” for the maintenance organization and, as such, their attention should be focused on rapid remedial actions and fast, decisive decision-making. Consequently, if the field service crew determines that a repair can be better performed in the shop environment, they should release it to the shop unless those resources are unavailable. Thus, the target for MTTRfield is relatively low, <1 hour, and unless the machine is not mobile, higher quality and more efficient repairs can be performed in the shop.

2.6.3 - MTTR (shop service / without delays)

The average downtime hours (excluding delays) required to execute shop repairs. There is no Benchmark or target associated with this measure. This measure enables site management to assess the impact of delays on shop repair execution and, if delays are found to be a problem, take corrective actions accordingly.

2.6.4 - MTTR (field / without delays)

The average downtime hours (excluding delays & response time) required to execute field repairs. There is no Benchmark associated with this measure but a reasonable target is <.5 hour. This measure enables site management to assess the impact of delays on field repair execution

Number of Field Repairs MTTR field =

Total Field Repair Downtime (hours)

Number of Field Repairs MTTR field =

Total Field Repair Downtime (hours)

Number of Shop Repairs MTTR shop =

Total Shop Repair Downtime (hours)




and, if delays or response time are found to be problems, take the corresponding corrective actions.

2.6.5 - MTBS after Repairs

The average operating hours to the first stop after each repair is an indication of repair quality and effectiveness. There is no Benchmark available for this metric. A realistic target depends upon the level of current performance, i.e. if repair quality is an issue (technicians are creating more problems than they are correcting), the target should be much higher than if repair quality is relatively good.

2.6.6 - % Redo

Percentage Redo is a measure of repair effectiveness. It is the proportion or percentage of man-hours labor dedicated to redo (correcting repair errors) to the total number of man-hours labor dedicated to all repairs. There is no Benchmark for this metric but a reasonable target is that redo should be < 2% of total repair man-hours.

2.6.7 - Unavailability Delays

Unavailability due to delay downtime quantifies the impact of delays associated with shop and field repairs on availability. There is no Benchmark associated with this metric but a reasonable target is < 1%. If unavailability (downtime) due to delays is significantly higher than 1%, it may be related to inadequate manpower, excessive field response times, poor communications to the field service crew, excessive workload, and/or a higher than normal amount of unscheduled work.

= (1 Total Downtime

Delay Downtime X 100 (%)– Availability) XUnavailability D

Number of Repairs MTBS after Repairs =

Total Operating Hours to First Stop (hours)

Redo = Σ Repair Redo Man-Hours

Σ Repair Man-Hours X 100 (%)




2.6.8 - Contamination Control The “Star” contamination control rating scheme is a valid indication of the organizations ability to provide and maintain a working environment and work procedures that promote and support high quality repair execution. The Benchmark is “5 Star”.

2.7 Component Management

2.7.1 - Component Life Target Achieved

The Component Life Target Achieved quantifies the percentage of components that are reaching target life before component exchange. There is no Benchmark for this measure but a reasonable target is that 100% of components achieve target life to rebuild.

2.7.2 - Components Scheduled

The Components Scheduled metric quantifies the percentage of components that are exchanged on a scheduled basis as a percentage of the total number of components exchanged in the period. There is no Benchmark for this measure but a reasonable target is that 100% of components are exchanged on a scheduled basis.

2.7.3 - Component Replacement Costs

Component Life Target Achieved

Components Exchanged > Life Target

Total Components Exchanged X 100 (%) =

_

Components Scheduled

Scheduled Component Exchanges

Total Components Exchanged X 100 (%) =

Component Replacement

Cost

Actual PCR Costs

Budgeted / Target PCR Costs X 100 (%) =




The Component Replacement Cost metric quantifies the ratio of actual component replacement costs to budgeted (target) costs. There is no Benchmark for this measure but a reasonable target is that actual component replacement costs should not exceed (< or = 100%) budget.

2.7.4 - Unavailability Component Replacement

Unavailability due to component replacement downtime quantifies the impact of component replacement events on availability. There is no Benchmark associated with this metric but a reasonable target is < 2%. If unavailability (downtime) due to component replacement is significantly higher than 2%, it may signify potential problems with component inventory quality / quality, component rebuild (CRC) turnaround time, and/or a higher than normal percentage of unscheduled component replacement events. If the component inventory quality / quality is found to be an issue, it may be due either to the fact that the maintenance organization is not doing a good job of communicating the component replacement plan the Parts Department and/or CRC or that the Parts Department and/or CRC is not delivering on its obligation to support the site with the components they require.

2.7.5 - Availability Index after Component Exchange

The Availability Index during the first six months after major component exchange is a very good indication of the quality of work being performed during component exchange. This can be calculated by monitoring Availability Index for the individual machine for the period. There is no Benchmark for this metric but a valid target is that the Availability Index during the first six months after major component exchange is > 88%.

2.7.6 - PCR Compliance

= (1 Total Downtime

Comp. Replacement DT X 100 (%)– Availability) XUnavailability CR

PCR Compliance

PCR’s Planned, Scheduled & Executed

Total PCR’s Planned & Scheduled X 100 (%) =




PCR Compliance defines the number of components that are replaced on a planned and scheduled basis as a percentage of the total number of components planned and scheduled. There is no Benchmark for this measure but a reasonable target is that 100% of components that are planned and scheduled for replacement are indeed executed per the plan.

2.7.7 - Backlogs Executed during Component Exchange

Backlogs executed during component exchange is a good indication of how well the organization is using the “window of opportunity” presented by component exchange to bring the equipment up to a standard that will permit it to perform reliably. There is no Benchmark for this measure but the target should be that 100% of items on the pending Backlog list are executed during the component replacement activity.

2.8 Human Resources and Training

2.8.1HR - Unavailability Personnel Delays

Unavailability due to personnel delay downtime quantifies the impact of personnel delays (waiting on manpower) on availability. There is no Benchmark associated with this metric but a reasonable target is < .5%. If unavailability (downtime) due to personnel delays is significantly higher than .5%, it may signify potential problems with manpower staffing levels, higher than normal workload (an abundance of Backlogged repairs), workforce inefficiency, and/or a higher than normal amount of unscheduled work, i.e. work that enjoys the benefits of planning & scheduling are typically executed far more efficiently than work that is

– = (1 Total Downtime

Personnel Delay Downtime X 100 (%)Availability) XUnavailability PD

Backlogs Executed with PCR

B’logs Executed during Component Exchg

Total Backlogs Pending X 100 (%) =




performed in an environment of constantly changing priorities such as the one created when a high percentage of the workload is unscheduled.

2.8.2HR - Effective Man-Hours

The number of hands-on labor hours available per month is a metric that helps understand / measure the manpower available on site. This metric is use as a reference for other metrics.

2.8.3HR - Personnel Hands-On to Machine Ratio

This ratio gives us a quick relationship between the work force on-site and the number of machines. This metric can be used as a quick reference and must be combined with other metrics to better understand the personnel situation on-site.

2.8.4HR - Direct Maintenance Personnel

This metric documents the number of hands-on technicians. The total number of technicians on-site can be easily compared with other metrics and other sites with similar operational characteristics.

2.8.5. HR - Personnel Total to Machine Ratio

Effective Man Hours

= Σ Labor Hours (hands on) present in the month [ h ]

HO Personnel – Machines Ratio

= Number of Machines

Total Hands On Technicians

Direct Maintenance Personnel

= Quantity of Hands-On Technicians (-)

Total Personnel –Machines Ratio

=Number of Machines

Total Personnel [ - ]

(-)




This metric establishes the relationship between the total personnel on-site and the number of machines. Total personnel includes all people on site, technicians, planners, supervisors, secretaries, administration personnel, etc.

2.8.6HR - Total Maintenance Personnel

This metric asks for the total maintenance personnel on-site. How many people we have on-site to support the fleet of equipment. This metric in conjunction with metrics in 2.8.3, 2.8.4 & 2.8.5 gives us a dimension of the maintenance crew on-site and can be compared with other similar operations to support the understanding of personnel efficiency. All the above metrics are very straightforward and can be easily obtained. The documentation of these figures link with the characteristics of the fleet and the on-site operation will give us a quick reference for future studies.

2.8.7HR - Overtime to total Effective Hours Ratio

The overtime ratio measures the amount of extra hours required to satisfy the maintenance operation as a percentage of the total effective hours available in the period. Overtime may be an indication of labor needs or extra maintenance demand in a particular period of time. Constant overtime levels should be an indicator to consider to review and possibly to improve the on-site organization structure.

Total Maintenance Personnel

= Total Quantity of Maintenance Personnel

[ - ]

Overtime Ratio =Total effective hours in the Period

Overtime hours in the Period X 100 (%)




2.8.8HR – Labor Hours Covered by Workorders

The labor hours captured in the workorders are charged to specific machines whenever a technician is assigned and working on that particular machine. This ratio is an indication of technician idle time. Idle time includes breaks for lunch and shift changes. The ideal situation would be to have a ratio very close to 100%, indicating a full usage of the labor available. Be careful in those cases in which the on-site operation “justifies” technician labor hours by charging 100% of their hours to the machines being serviced.

2.8.1T – Training Hours / Labor Hours

This metric, used by the International Labor Organization, gives us the relationship between the hours invested in training and the total available labor hours in the period. This organization considers that a minimum of 1% of every 100 labor man-hours be dedicated to training to be acceptable. We don’t have results for our mining projects but we believe that if it were known it would be much higher than the OIT target.

2.8.2T – Training Hours by Systems (vs. Problems)

This metric gives us the opportunity to assess if the training efforts are addressing the actual problems that the maintenance organization is facing. The relationship between the Ranking of Problems (Top 5 or 10) obtained from the machine repair history and the hours trained in that particular subject or machine area must be very strong. The training needs detection (TND) process should consider this ranking of problems

Labor Hours in Work Order

=Total effective hours in the Period

Total Labor Hours in Workorders X 100 (%)

Training Hours Ratio

=Total Labor Hours available in the

Period

Total Training Hours in the Period X 100 (%)

Training Hours Ratio by Systems

= Total Training hours in the Period

Training Hours on “System A” X 100 (%)




and schedule training activities to support the organization to be better prepared to solve those problems.

2.8.3T – Training Program Compliance

The training compliance metric gives us an indication of how well the on-site operation is following the training activities scheduled. It is also an indication of the importance that is given to the training activities. Are we complying with what we scheduled?

2.8.4T – Competencies Required

To obtain this metric, total number of competencies required, the on-site organization must have a clear definition of the roles and responsibilities for each of the positions in the organization and the number of people assigned to each of those particular roles. This metric gives us an indication as to how many competencies we need in order to do the job efficiency and effectively.

2.8.5T - Competencies Satisfied

The percentage of Competencies satisfied will give us an understanding of how well the organization is prepared to perform the maintenance tasks. This metric compares the number of competencies that have been certified in a formal certification process against the total competencies required.

Training ProgramCompliance

=Total training hours scheduled

Training hours completed X 100 (%)

Competencies Required

=Competencies defined in each role &

responsibilities X Number of People in the corresponding Roles

% of Competencies

Satisfied =

Competencies Required

Personnel Competencies Certified X 100 (%)




2.8.6T - Personnel Skills Inventory Completion

The Personnel Skills Inventory is probably the foundation for any training detection needs or gap analysis study. The personnel skills must be surveyed and kept in an updated Data Base.

2.9 Continuous Improvement

2.9.1 - Top Problems with C.I. Projects

The Ranking of Problems is based on the Machine Repair History and represents those problems or areas that most affect the final performance of the fleet. The % of CI projects dedicated to solve those problems is an indication of effective communications and clear management to direct the organization efforts where they are most needed.

2.9.2 - Active C.I. Projects

CI working on Target (CIOT) = % of Continuous Improvement Projects on

Problem Ranking

Top 1-2 _________ %

Top 3-5 _________ %

Top 6-10 _________ %

Active CI Projects = Number of CI projects in process [ - ]

Personnel SkillsInventory

=Total Personnel Skills

Skills / Competencies in Inventory X 100 (%)




This metric, the number of CI projects that are in process or active, gives us an understanding of the magnitude of the CI effort and how active the organization is in the search for solutions or optimizations.

2.9.3 - C.I. Projects Closed during Period

This metric is an indication of the regularity of the CI process in place, that is how many CI projects are we closing in a period of time, or how many solution proposals are we delivering to the organization. We recommend measuring this result on a monthly basis.

2.9.4 - Average C.I. Project Execution Time

This metric in conjunction with 2.9.3 above gives us a measure of the CI process efficiency. Average days to close the CI Projects coupled with the regularity of delivery measured by CI Projects Closed in the period provides us a means of telling if the CI pipeline has the ability to deliver results in a reasonably constant timeframe.

2.9.5 - C.I. Projects Opened during Period

The number of CI projects opened or generated in the period is an indication of maturity of the CI process. This metric measures if the maintenance organization is continually looking for solutions and better ways to do things. It is also is an indication of the effectiveness of the Problem / Opportunity detection process and management.

CI Projects Closed = Number of CI projects closed in the Period [ - ]

CI Project Execution

Time

= Average days to complete CI projects [days]

CI Projects Opened

= Number of CI Projects generated in the Period [ - ]




2.9.6 - C.I. Project Delivered Value

This metric measures the effectiveness of the CI process in place through the proven value delivered to the operation. This value can be a recorded direct savings, an increase in productivity, an improvement in availability translated into more equipment hours to produce and / or maintenance labor reduction, etc. Accurate records are a must in order to be able to calculate and validate the results of this metric.

CI Delivered Value

= Proven Benefits due to CI solutions Implemented

[ $ ]




Glossary of Terms Performance Metric: A term used to describe the outcome of any process used to collect, analyze, interpret and present quantitative data. A measurement parameter that enables performance against some pre-defined Target or Benchmark to be monitored. A measurement 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. The collection 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's are 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, and manufacturers’ specifications.

Benchmark (noun): A world-class performance standard relative to a specific Performance Metric; represents and quantifies "best practice" of an operation or of specific 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 performance over time relative to some Performance Metric. Shutdown / Stoppage: An event that takes a machine out of service. Shutdowns may be scheduled 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 is independent 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.




Failure: The inability of a device or system to perform in its required function … the cessation of proper functioning or performance, for example a power failure. Failures may be the result of technical product issues, i.e. equipment unreliability, or due to maintenance / repair neglect, i.e. equipment management ineffectiveness in the area of problem avoidance. 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 by the customer or contained in the Customer Support Agreement or MARC). Available Hours: Time that a machine is capable of functioning in the intended operation.

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 hours tabulation. 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 at many 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 for all 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 most machine downtime histories but is nonetheless included, yet unrecognized, as part of the machine downtime record.




Generic Pareto Reference for Large Off Highway Trucks

The most successful mining support operations are those that have a clear understanding of the problems and issues they are facing. The identification and quantification of problems by component (e.g. engine, transmission, …), system (e.g. hydraulics, electrical, …) or even process (e.g. PM) facilitates an understanding of the influence each is having on the final outcome enabling management to focus its attention and resources on the most critical issues, i.e. those that will derive the maximum benefit.

Unfortunately there are no Benchmarks that are applicable to this kind of measurement. However a collection of guidelines for large Off Highway Trucks in the 785 – 793 size class is available to evaluate actual site performance in terms of MTBS, MTTR and impact on Availability. While not actually benchmarks, the information contained in this reference defines 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 of approximately 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 the equipment receives and product design shortcomings that may be peculiar to specific machines either by model or within a given range of serial numbers.

The table on the following page provides a baseline that can be used as a reference until individual site experience and history can be documented. Using it to generate and perform a top problems distribution analysis enables Project Management to identify and prioritize critical issues affecting success of the project for investigation and resolution.

It is important to note that due to the fact that most machine workorder history databases to not do a very good job of documenting delays, the duration of machine downtime events (MTTR) includes any delay downtime associated with the particular event. As such, delays are not listed separately in the table. A better way of doing business would be to break out actual repair downtime from any delays associated with the




repair and, if it is found that delays are an issue, concentrate the corrective efforts on the root cause of the problem.

6750 28.00 0.37%2100 2.80 0.12%6650 0.30 0.00%6100 0.90 0.01%4000 0.30 0.01%1200 6.00 0.45%450 2.60 0.52%

2850 7.00 0.22%1300 5.10 0.35%6950 12.90 0.17%800 0.60 0.07%

3750 6.90 0.16%1250 1.90 0.14%550 9.90 1.61%

2800 1.30 0.04%2100 12.20 0.52%6150 5.30 0.08%1350 3.10 0.21%1250 4.90 0.35%850 0.20 0.02%750 2.70 0.32%250 7.70 2.76%

1950 6.20 0.29%3150 9.40 0.27%1950 1.90 0.09%550 3.20 0.52%

7250 5.10 0.06%900 5.30 0.53%

5850 6.20 0.10%

Cab / Operator StationChassis

Cooling System

Air ConditioningAuto Lube System

Base MachineBrakes & Brk System

Generic Pareto Reference Large OHT's (785-793)

Component / System

AccidentsAir System & Starting

ref. Availability Impact (%)

ref. MTBS (hours)

ref. MTTR (hours)

DifferentialDispatch System

Dump BodyElectronics & Electrical

Engine

PMSteering System

Suspension

FiltersFinal Drives

Front WheelsHoist System

Hydraulic SystemMirrors

miscellaneous

Switches & SensorsTires & Rims

Torque Converter

unknownTransmission

NOTE: If the PM interval is 500 hours, MTBSPM = 500 hours, MTTRPM = 16.80 hours and Impact of PM on Availability = 3.00%.

"UNKNOWN":Stoppage is unidentified or data is

unavailable. An excessive number of unknown events is an indication of

inadequate recordskeeping practices.

"MISCELLANEOUS":Includes any shutdown event that is not covered by one of the other

description codes.

"BASE MACHINE":Includes ladders, hand rails, sheet

metal, brackets and other miscellaneous areas of the machine

not covered by one of the description codes in the list.

ELECTRONICS & ELECTRICAL:Includes electrical / electronic

components & systems, e.g. lighting, VIMS, wiring harnesses,

connectors, etc.

ENGINE:Includes all engine and engine-

related components and systems not covered by another

description code, e.g basic engine, air intake & exhaust, fuel

system, etc.

CAB / OPERATOR STATION:This description code includes

cab, windshield, seat, windows, etc.

HYDRAULIC SYSTEM:This description code includes all pumps,

hydraulic actuators, hoses, lines, oil coolers, tanks, etc not included in another description

code.

NOTE: MTTR = 16.80 hours for a 500 hour PM interval. In other words, if MTBS for PM = 500 hours, MTTR =

16.80 hours.

metrics (kpi's) to assess process performance

Documents