Maintenance Score Card

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The Maintenance Scorecard

Copyright 2005, Industrial Press, Inc., New York, NY


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Chapter 5 Fundamentals and Myths

Things should be as simple as possible, but not simpler.

- Albert Einstein

Definitions

The intention of this chapter is to try and dispel some of the myths and con-fusion that surround the discipline of asset management and that of its meas-urement. There is often the perception that the objectives for asset managementand, therefore, the best way to measure the fulfillment of those objectives, areobvious. This perception has been created over many years and is the result of

two fundamental forces.First, it has been contributed to by the perception that asset management is

a one-size-fits-all discipline, whereby generic solutions can be transferred easilyfrom one company to another or from one industry to another. This percep-tion is behind much of the benchmarking efforts that are carried out through-out the world and is also partly to blame for the reduced level of corporateattention that the area receives. Second, many people working in the consult-ing areas of asset management do not originate from the field. This is particu-

larly due to the technological revolution of the 1990s and has led to a largenumber of experts from fields such as IT or supply chain, or even data analysts,offering solutions to asset managers.

The resulting impact of these two areas has been that asset management solu-tions, and at time decisions, are taken based on incorrect premises, premisesbased on limited understanding that have fed the belief that asset managementsolutions are obvious. This chapter will focus first on providing some commonexplanations and definitions of terms commonly used when developing meas-urement programs, and second on addressing some of the more common mythsin the measurement of the asset management function.

To paraphrase the caption above, Asset management should be as simple aspossible, but not simpler. When the area of asset management is oversimplified,there can be catastrophic results, not the least of which is a failure to achievethe levels of performance that are open to companies by understanding some ofthe concepts at the base of this managerial discipline. One of the intentions ofthis chapter, and indeed of this book, is to look past what is accepted as com-mon sense or good practice to the concepts that all of this is based on, and

determining the real actions and measures, to manage organizations through arigorous application of engineering logic.

Throughout the world there are a range of terms and definitions that areused to refer to measurements of performance. This is often a cause of confu-sion and misunderstanding. As such it is necessary to define the various terms




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that are used within the context of the MSC. An important aspect of these def-initions is that they do not refer to particular indicators or measures; they referto the way in which the indicators are used.

Performance Indicator- This term refers to any indicator measuring the per-formance of a business process, work team, individual, piece of equipment orplant in terms of its ability to meet its desired levels of performance. This termis often inter-changed with other terms such as metricor measure.

Key Performance Indicator (KPI)- As denoted by its name, a key perform-ance indicator is the indicator that represents the overall performance of a par-ticular strategy theme or improvement initiative. For example, a strategic themeof regulatory compliance may have a range of indicators through each of the

perspectives of the MSC. However, one of these indicators will be able to beused as a guide to the overall performance of the company within this strategictheme. This term is often used, incorrectly, to describe all indicators. This dis-tinction is important as it highlights, clearly, the different weighting that needsto be given to differing indicators.

Leading and Lagging Indicators Understanding which indicators are lead-ing and which are lagging can provide managers with the ability to calibratetheir measurement systems to achieve best results. For example, when meas-

uring compliance with safety objectives, there is a tendency to use indicatorssuch as LTIFR, Lost Time Injury Frequency Rate, or other similar measures.This indicator gives management an immediate view of the frequency of inci-dents that have caused lost time injuries it is used to evaluate the perform-ance of safety initiatives and for targeting safety improvement efforts.

This measure, although both valid and useful, is reactive in its focus andis an example of a lagging indicator. It is based on waiting for events tohappen that signal a call to action. There are some particular dangers in

using this style of indication on its own, in particular because a lack ofincidents does not necessarily indicate that safety management processes areadequate.

An example of a leading indicator in this context can be developed usingprinciples of functional measurement, first mentioned in Chapter 4 of thisbook. When developing maintenance strategy, there is invariably a range ofroutine activities and maintenance tasks that are put in place to manage the riskof failure to within tolerable levels. The frequency and type of these tasks isdetermined by the consequences and probability of the failure mode occurring.

Therefore a measure that monitors the compliance of these tasks proves that thecompany is managing risk to within its pre-determined tolerable levels. It alsoshows forethought in the management of safety incidents in physical assets.This leading indicator forecasts possibilities rather than merely responding tothem and is often used alongside reactive safety indicators.

Chapter 5 Fundamentals and Myths 99




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Opposing Indicators This form of measurement is extremely useful inensuring that actions and reactions are occurring according to plan. Opposingindicators represent the two sides of any improvement initiative. A classicalexample of opposing indicators is found in the measurement of production.

When a plant raises its production levels, it needs to do so while keepingmaintenance costs at either the same level or at a reduced level. Failure to dothis can result in reduced profit margins. In this case we see one indicator, pro-duction rates, rising, and we see the second indicator, maintenance unit costs,lowering. If this is not the case, then there may be cause for concern. This obvi-ously depends on a range of external factors such as client demand and the needto clear backlog orders; however, generally this is a true relationship.

Another example of opposing indicators may be those of unavailability, the

inverse of availability, and machinery utilization. If unavailability is reducingand utilization is not rising then there are issues regarding the manner in whichthe equipment is being operated. While this could be related to a lack of pro-duction requirement it could also indicate a need for optimizing operationalprocedures to take advantage of increased uptime.

Time Based Indicators- All performance measurement is related, in somemanner, to time. A great many of the performance indicators, which are usedin day-to-day management of maintenance, are based on differing interpreta-

tions of the use of time. Mean Time Between Failure, Availability, Utilizationand all of their derivative measures are all ways of determining how time wasused as it applies to the equipment. If recorded and calculated separately we canfind ourselves with a disparity in measurement, that is, having a range of per-formance indications that do not necessarily agree with each other. The inten-tion of this brief section is to detail how data capture could most effectively bedone for time-based indicators.

The measurement of time-based indicators is based on the concept that the

equipment is only available for a set period of time, during which it can be usedin a range of differing ways. Accurate and consistent time-based measurementrelies on being able to create a structure of possible ways that a piece of equip-ment can be used that will be able to give us the information we require to pro-duce the measures that we need to produce.

While this can be done manually, using either paper forms or disconnectedspreadsheets, it is far easier if there is a central means of electronically captur-ing this information in order to apply it through the structure as required.Many of the EAM-level systems on todays market have this or similar style

capabilities. However there are also niche availability recording systems thathave similar capabilities.

While having the software in place to do this sort of information recordingthe most vital part of this solution is the structure itself. In Figure 5.1 the struc-ture shown is a generic example of how this could be applied. The initial step

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is that of total time, followed by a separation into scheduled and unscheduledusages of time. The depth of the structure is totally variable, driven only by therequirements of each corporation. Some things that may change the structureinclude contract arrangements, operating environment and industry type. At alltimes, the lowest levels that are defined are the levels that are used to enterinformation.

For example, if a piece of equipment was out of service for a scheduled replace-ment then this would be recorded using the code scheduled replacement above. In

some instances there is the ability, and desire, to go to greater levels of granularity;for example there may exist a code under this level called Replace Gearbox. Thisis particularly effective in cases where standard equipment types are used.

This code would feed up the hierarchical structure, through the code ScheduledRoutine, through Maintenance Time and form a part of the code ScheduledTime. As referred to elsewhere in this book, modern business intelligence softwareis easily able to drill-down through layers of data to reveal greater levels of detail. Inthis case the structure facilitates the drill-down functionality.

Using this sort of approach, if the underlying structure has been adequatelydefined, there can be a large number of time-based measures derived from thesame data capture exercise. However, one of the key misconceptions regardingtime-based indicators is the fact that they, by themselves, are able to representthe effectiveness of equipment performance.


Total Time

Scheduled Time Unscheduled Time

Maintenance Time Operation Time Other Maintenance Time Operation Time Other

Utilized

Non-Utilized

Idle

Utilized

Non-Utilized

Idle

OpportuneWorks

Breakdown

Rework

ScheduledRoutine

ScheduledCorrective

ScheduledModifications

Scheduled Replacement

Scheduled Overhaul

Failure F inding

On-Condition

Opportune preventive / Predictive works

Opportune Corrective Works

Figure 5.1 An Example of a Structure for Capturing Time-Based Indicators




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This highlights an area where there has been considerable confusion, that ofthe difference between under-utilization and under-performance. Althoughsimilar, these two are distinctly different and each one points to a different areawhere improvement initiatives could be made.

Under-utilization is almost entirely under the control of the operational partof any organization, and refers to the ability of operations to utilize the equip-ment during the time that it is available. Although this measure is out of thecontrol of asset management, it does reflect how well available time is beingused and provides an insight into how to make this better. Under-utilization isalmost always due to a conscious management decision of some nature. Attimes it highlights the need for reduced equipment numbers or it may indicatea need for better operations or handover processes.

Under-performance, on the other hand, refers to how well the equipment isproducing during the time that it is being utilized. This is not a measure of timeand needs to specifically take into account rates of production. Under-perform-ance can be at the heart of many issues regarding corporate performance.Unlike under-utilization, it may not be associated with a conscious decision toperform in this manner. Under-performance may be the result of poor equip-ment reliability, reduced levels of throughput, poor product quality or a rangeof other factors.

The remainder of this chapter is to point out some of the myths and miscon-ceptions regarding the measurement of the maintenance function that haveinvaded the asset management discipline during the past two decades. Thesemyths are currently found in many organizations and are directly related to theapplication and success of advanced asset management principles. Many ofthese go to the heart of machine maintenance itself, while others merely helppeople better understand how to apply a performance measurement regime.

Myth 1- Metrics as Purely Lagging Activities____________________________________________________________

MythMetrics are useful for monitoring asset and human performance as a

continuous improvement tool (Lagging After the event)

RealityMetrics are a management tool for implementing corporate strategy and

ensuring its execution as well as highlighting continuous improvementopportunities (Leading and Lagging)

____________________________________________________________

There is an often-quoted maxim within management that what can bemeasured can be managed. While this is a true statement, it supports the belief





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that management is a reactive art. As a result, measurement is often used in areactive manner, that is, measuring recent performance and then using this as abase for improvement in that particular area. In this manner indicators are lag-ging management tools. They are used to determine performance after the

event.This is common practice and is, without a doubt, a good practice to pursue

in any arena of professional activity. Yet in every field of human activity thereis always a need to first determine where it is that we wish to go, then plan ourmeans of getting there. If we want to get there in the best manner possible, interms of time, cost and comfort, then we will put in the effort to plan the jour-ney upfront.

This level of planning is done in the majority of organizations. Although

when it comes to asset management, it is often not done at a corporate level andis left to lower strategic and tactical level operators to determine strategy. TheMSC provides a tool and structure for integrating the corporate planningprocess for maintenance efforts. It also focuses these strategies into measuresand targets that need to be obtained.

This allows us to use indicators as a proactive rather than a reactive tool. Bytying these to corporate objectives, targets and strategy initiatives, we are ableto use them to forecast where a company wishes to go rather then merely usingthem as performance monitoring tools.

Myth 2- Availability as Effectiveness

____________________________________________________________

MythAvailability is a good measure of maintenance effectiveness

Reality

Maintenance Effectiveness is a concept that is not, and cannot be,represented by only one indicator.____________________________________________________________

Availability is a measure of the amount of time a piece of equipment is avail-able for operations. It is possibly the most widely used and most common per-formance measure in the asset managers arsenal throughout the world today. Itis used to understand equipment performance, set production targets, justifyequipment purchases or other expenditure and use as the base for a range ofother derived measures and practices. However the true mechanics of this meas-

ure are not often understood by those making decisions based on it.The most common misunderstanding is thinking that availability is a meas-

ure of the ability of equipment to perform to the standards required of it. Whenthis area of understanding is examined, it becomes clear that availability byitself is not an adequate measure of the effectiveness of the equipments per-





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formance. In order to understand the misunderstandings of this area it is firstnecessary to understand what is meant by the term effectiveness.

Effectiveness, in terms of asset management, refers to the equipments abil-ity to do what the users require of it. As stated elsewhere in this book, this

takes in a wide range of areas and factors. However principal among these isthat users fully understand what it is that they require of the machinery. Atfirst glance this question is often treated with the disdain people associate with simplicity. Users generally understand the reason why they purchasedthe machine and the productivity that is expected of it in order to meet annu-alized production plans. In a mining organization, for example, the haulagefleet may require an annual availability of 90% in order to achieve the pro-duction goals for that year.

However availability in itself is no guarantee of good performance. Take, forexample, the performance of an electrical motor. It is not important to under-stand anything else about its operating context for the sake of this example. Themotor is required to operate for a period of 10 hours continuously. During thistime it is out of service for 1 hour.

As measured by availability this would give a measure of 90%-

In some industries this may be considered an adequate measure of perform-ance, in other it could be woefully inadequate. If this were the result of only afew failure events, then this figure would be an adequate guide. However if the1-hour of downtime was caused by 20 failures, each lasting 3 minutes each,then the performance of the motor, in terms of failure rate, would have beenless than adequate.

Failure rate (often referred to as reliability or mean time between failures) ofthe motor in this case would be 0.5 hours -

Therefore, even though the equipment had an availability of 90%, a failurerate of half an hour indicates the poor level of performance of the motor. Itindicates that, on average, the motor could be relied upon to run for half anhour before failing. This relationship is illustrated in Figure 5.2.

There are further areas where availability fails to be a good measure of equip-

ment effectiveness. As stated previously effectiveness needs to be based aroundwhat users expect their equipment to do. This is often expressed as the produc-tion rate primarily; yet this is far from the entire range of expectations that usershave of their equipment. For example, a pump that is used to pump hydraulicfluid may have several key expectations of it-


Time available for production (9 hours)

Time required for production (10 hours)------------------------------------------------------------------------------------------------ x 100

Time in operation (10 hours)

Number of failure events (20)-----------------------------------------------------------------------




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To pump hydraulic fluid at a predetermined rate and pressure

To retain all hydraulic fluid so as not to breach environmental regulations

To relieve the pump when fluid pressure reaches a predetermined danger-

ous level

In this scenario we see the measure of availability falling short in a number

of areas. The first area is that of the primary function of the pump. If the pumpis not operating at all it is almost always registered as unavailable. However if

the pump is operating and available but pumping at a reduced rate and/or pres-

sure, then it may not be registered as unavailable. It also would not represent

times of reduced availability such as run-up or run-down times or other times

where performance, hence effectiveness, would be as per primary function

requirements.The other area relates to the secondary functions of the pump. The measure

does not reflect the fact that the pump may be leaking, or that the relief valvemay not be working in a manner that is required, not until the pump is taken

out of service and no longer able to perform its primary function. However it

may have been functioning at less than required performance for some time due

to leakages.


Figure 5.2 Comparing Availability and Reliability




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In summary availability remains a good measure of equipment performance.However, like every other measurement it is not a sole source of information.The limitations of this measure need to be understood in order for it to be usedto its maximum effectiveness. Some quick guides to the limitations of availabil-

ity are listed below.

1. Availability is a partial measure of how equipment fulfills only its pri-mary function. It does not necessarily measure partial availability orreduced availability.

2. Availability and failure rate together provide a more accurate guide tothe performance of machinery to fulfill its primary function.

3. Availability does not give any sort of indication of effectiveness of theequipment to fulfill user requirements, particularly secondary functional

requirements, until such time as the equipment has been removed fromservice to repair these.

These limitations have profound implications for other areas where availabil-ity is used as a part of, or as a base for measurement regimes. In particular thisrelates to the widely used Overall Equipment Effectiveness measure, OEE, andthe use of availability modeling techniques. In applying both techniques it isnecessary to bear in mind what the measure is showing the user.

In the case of OEE this means that one of the base components of this meas-ure is, at best, a measure of the effectiveness of equipment to measure a part ofits primary function. The effects of partial availability are often not captured bythe remaining elements of the equation.

Myth 3- Levels Where Metrics are Used

____________________________________________________________

Myth

Management uses indicators to monitor the performance of the organizationshuman and physical resources

Reality

Indicators are used by all levels of the maintenance organization as a tool toassist in carrying out their daily tasks

____________________________________________________________

Within various fields of asset management, indicators are only seen by sen-

ior and higher level managers. Often indicators are used by middle manage-ment to understand trends and present information to higher managementregarding what is occurring and the performance of various operational ormaintenance initiatives.

At times companies take communications initiatives such as posting Key





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Performance graphics in various places within the plant in order to inform peo-ple about performance and to hopefully create interest. However, if the indica-tors that are used are not of any use to the functional and tactical levels of theoperation, then they will be ignored or at best reviewed without understanding

the full significance of them.This poses some interesting challenges to companies. If people at the tactical

levels are able to find value in daily or weekly indicator reports, and are able torelate these in their personal efforts within the organization, then the capacityto achieve improvements will be multiplied.

For example, if weekly toolbox meetings focus on the mean time to repair ofa particular failure mode on a particular piece of equipment, then this is some-thing that the tactical level staff have a strong understanding of. As such the

toolbox meeting can be used to drive out initiatives to reduce the MTTR oreven begin initiatives to eliminate the problem entirely.

Myth 4- Performance Measures are One Dimensional Only

____________________________________________________________

Myth

Performance measurement is only done via key performance

indicators and standard metrics

Reality

Modern technology has enabled the use of sophisticated graphicalanalysis as well as one-dimensional indicators

____________________________________________________________

Indicators, or metrics, are usually expressed as one-dimensional tools that areused to give a numeric representation of performance in some form or other.

This is a traditional viewpoint and one that has its roots in the way that infor-mation has previously been managed. Prior to the 1980s graphical displays werenot common and as such were not often used in creative ways. Since the begin-ning of the 1990s graphing and information analysis software has become ubiq-uitous. It is on every desktop and most people have at least a glancing under-standing of how to use it or access it.

However with the advent of business intelligence tools this has been taken toanother level entirely. Companies now have the ability not only to graph theresults of the performance, but also to develop a range of other tools for analyti-

cal assistance (see Figure 5.3). These include the ability to drill-down into graph-ical displays to present further layers of detail, to immediately compare measuresand results, and to configure executive alarms or stoplight indications.

This is a continually evolving area and one that has resulted in companies find-ing a large number of new applications for these forms of representation. One of





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the key benefits of business intelligence solutions in industry is the ability to

reduce large volumes of data down to easily understandable measures and graph-ics. This is often referred to as the sweet spot within the data, the cross-section

of the captured information that best represents whatever is being measured.

This area has opened up the field of performance measurement to the appli-

cation of a great deal of creativity, using data sets and sub-sets to represent

improvement opportunities and performance, and comparing these sets in a

way that was previously not imagined.

In Figure 5.4, time-based measurements have been represented in a way that

makes large volumes of information easily able to be understood. At a glancean operator is able to see how his equipment is being utilized, for what reasons

and where there are gaps in the performance. These principles can be applied


Poor Good

Availability

Utilization

Figure 5.3 Example of Stoplight Indications

Figure 5.4 Example of Sophisticated Analysis Techniques

Hours Utilised Productive

Hours Utilised - UnproductiveHours Idle

Hours Breakdown

Hours Scheduled Maintenance

Hours Unscheduled Maintenance

Hours Utilised Productive

Hours Utilised - UnproductiveHours Idle

Hours Breakdown

Hours Scheduled Maintenance

Hours Unscheduled Maintenance

0%

100 %

75%

50%

25%




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to virtually any area of performance, limited only by the imagination of thosedeveloping the indicators.

If the underlying information sets are accurate, these sorts of principles canbe used to present almost real-time comparisons for internal benchmarking

purposes. The advent of this capacity has enabled asset managers to be able toreact and make decisions in vastly reduced timeframes and with a previouslyunheard of level of confidence in the decision-making information.

For example, a mine site in Asia had configured its CMMS system, reporting sys-tems and business processes to be able to produce almost real-time unit costing infor-mation with regards to how the mine was operating from day to day. By recordingproduction tonnages, times, costs and activities as they were occurring the companywas able to produce end of shift reports that clearly indicated the unit costs of pro-duction during the night, the variance from the previous shift and the overall ten-dencies over time.

Due to the inter-related nature of the data they were also immediately able topinpoint where costs had ballooned and the underlying reason for this. This couldhave reduced production for some reason or increased maintenance costs for somereason. However, this capacity enabled the company to react almost immediately tocorrect early signs of rising unit costs, or at least to understand them, based on fac-tual understanding rather than on purely experience and gut-feel.

Myth 5- Proactivity as a Measurable Element

____________________________________________________________

Myth

Proactivity leads to more efficient maintenance activities; therefore,measuring proactivity provides a snapshot view of how well the

maintenance effort is performing

Reality

Proactivityis a source of efficiency improvement; however,it is not easily measured and represents a form of thinking

rather than measurable actions____________________________________________________________

As the discipline of asset management continues to grow there is an increas-ing level of importance given to proactive actions. This has become somewhat

of a mantra to managers and consultants alike and has led to great leaps in pro-ductivity in various organizations. The area of proactivity in asset managementis complex and could be the basis for an entire book by itself; however, there isno doubt that a forward-looking philosophy of asset management will achievemore than a backward-looking philosophy.





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This rising level of interest and application of proactive thinking has raisedthe question of measurement. Often the measure applied is a simple one asdetailed below:

Proactive maintenance vs. Reactive maintenanceAt face value this appear to be a good measure and one that can easily be used

to give a high level representation of the level of proactivity within the organi-zation. However, when this indicator is reviewed in further detail, there are sev-eral gaps in this logic.

First, there is a need to understand what truly makes up proactive and reac-tive maintenance activities. Proactive maintenance is often defined as routinemaintenance, that is, the maintenance that we have decided to do to maintain

the asset base. Reactive maintenance is often made up of the corrective actionsthat are performed in response to something occurring.

So far so good, the indicator is giving the company a ratio of routine workand correctively performed work. However, when formulating maintenancestrategy, there is often, depending on the consequences of failure and the con-figuration of the physical assets, the decision taken not to perform routinemaintenance activities at all. (Run-to-fail)

The decision to not apply routine maintenance also represents a form of

proactivity through the use of analytical methods that determine the most cost-effective form of maintaining the asset base. Therefore when failures of thesepieces of equipment or components occur, they cannot be taken as purely reac-tive actions. Rather they are planned-for failures that have been determined asthe best strategy for that piece of equipment under its current operating cir-cumstances.

However, when reviewing the indicator above, this is not immediately obvi-ous. In fact it creates the image that asset management is out of control whenit may not be the case. Also, seeing a lowering unit cost of maintenance and arising level of reactive work would cause immense confusion, as it doesnt seemto follow what is commonly believed.

Another area where confusion can arise in this measurement is in the record-ing of actions taken in response to a fault being noticed. When performing pre-dictive maintenance and detective maintenance, there is always a possibility offinding a fault or a condition that indicates a fault is not far away. Therefore,how is the resulting corrective action recorded? Is it a reactive task, because weare responding to something that is failed or failing, or is it a proactive task

because we are acting on information from our maintenance regimes?Within the MSC these forms of repairs are referred to as proactive repairs

and represent part of the proactive approach to asset management. Failure torecognize these maintenance actions has long been a failing of RCM and of theimplementation and monitoring of RCM initiatives.





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Proactivity is a desirable attribute of any functional area, however, this is par-ticularly true for asset management where the company carries substantial eco-nomic and risk management implications. However, measuring proactivity isnot easily achieved and will depend on things such as:

Coding structures for work orders

The ability of the CMMS to record the types of strategies that have beenapplied to certain failure modes

The amount of additional strategic initiatives and the measures applied tothese.

Proactivity is more than a measurable group of activities. It is a way of think-

ing and acting that will have immense results when it becomes an integral partof the way that business is conducted. Its measurement is complex and requireslevels of functionality that are not found in many enterprise-level managementsystems.

Myth 6- OEE as a Measure of Overall EquipmentPerformance

____________________________________________________________

Myth

Overall Equipment Effectiveness (OEE) is a measure of the overall effective-ness of equipment, plant or processes

Reality

OEE is a useful measure if taken for what it is; however, if misused it canprovide indications of performance that are inaccurate and at times dangerous____________________________________________________________

Overall equipment effectiveness is one of the more widely-used indicators intodays maintenance environment. It is also claimed as one of the leading meth-ods for optimizing equipment performance and for providing a monitoringmechanism for continuous improvement initiatives. There have been volumesof work, books and other technical information dedicated to this measure andits application throughout industry, and there can be no doubt regarding thebenefits that it has assisted companies to achieve in many industries over recenttime.

This apparent success has led many maintenance professionals and corpora-tions to adopt this indicator into their operations without question; it is themost prominent example of influenced metrics existing in the world today. Yet,the measure itself, if wrongly applied or wrongly interpreted, can lead corpora-tions to make poor reliability decisions, or worse, dangerous decisions.





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OEE is a product of three aspects of equipment performance and normallyconsists of the following parameters:

Availablity x Production Rate x Quality

The thinking behind this measure is to have an indicator that represents thethree key aspects of machine performance in a format that is easy to view andto access, and one that provides information for use in continuous improve-ment initiatives.

However, in the world of reliability engineering, these three aspects ofmachine performance are not the only aspects that are important to either themaintenance function or the operational function. This goes to the heart of theissues regarding OEE, the claim to be an overall indicator of performance or

even of organizational capabilities.If any one indicator is truly going to represent the aspects of performance

that are of importance to capital intensive organizations, or any maintenancefunction, then there is a need for it to include, in some fashion, the ability tomeasure and indicate how the corporation is managing risk, both safety andenvironmental risk.

Lack of the correct amount of perspectives is one issue. However, using theexisting perspectives within the OEE could also lead to issues regarding relia-

bility and safety.The indicator is often applied without any limitations on the indicators. Forexample, equipment may not need to be available 100% of the time; rather, itmay only be needed 90% of the time. Another issue, and more important, isthat within reliability engineering there is a distinct difference between whatequipment is required to do, and what its design capacity permits it to do.There are a range of reasons for this. One of the more common reasons is thatmost equipment contains items which will wear over time, often in a randommanner (as is the case with complex equipment) but wear is still a considera-tion. By operating equipment at, or near, its design capacity, companies arereducing the time that is available for equipment to wear.

Therefore, a piece of equipment with a production rate of, at, or near itsdesign capacity will have a positive OEE reading, even though this may bereducing the level of reliability of the machine and, therefore, reducing theoverall effectiveness of it (over time). In worst case scenarios, equipment maybe operated at beyond its design capacities due to deliberate or accidental over-loading of the system. This will produce a yet higher level of OEE and there-

fore create the perception that the equipment is operating at better than previ-ous levels of performance.

However, what is really happening is that temporary or continual over-loadingof equipment reduces its ability to perform in a reliable manner. This is a funda-mental principle of reliability engineering that, at best, could lead to early equip-





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ment failures or, at worst, could lead to safety incidents. Over-loading equipmentwithin a manufacturing plant could be an example of where reliability and eco-nomic life of equipment is the principal result. When the same principles areapplied to a petroleum refinery, then the results could be far worse.

This leads to another issue in the areas of performance management. Oftenthe three areas that are monitored within the OEE indicator do not have an equalvalue to the organization as a whole. That is, all three aspects of this measure aretreated as equal under the normal way that this measure is implemented.Therefore an increase in production rates is considered to be equally as importantas an increase in quality. This does not reflect the individual nature of each of theorganizations that use this measure and could lead to decisions taken to focusresources on areas when they could be better utilized elsewhere.

Asset management is not a one-size-fits all management discipline. In factthe complexities of each company, combined with the complexities of each baseof installed assets, makes asset management uniquely challenging. OEE is agood measure when it is taken for what it is, that is, a measure of the perform-ance of the equipment in three fundamental areas. In some applications this fig-ure is extremely useful and, if the method of applying it is adapted, can providea good indication of equipment performance. However, in other industries,such as electrical distribution, this indicator will provide extremely limited andalmost non-consequential results. Within this particular industry the combina-

tion of availability, production rate and quality will result in a consistently highfigure,23 so much so that the figure will only really change when there has beensome form of interruption to services.

It is the opinion of the author that there is, to this date, still no one measureof organizational effectiveness or of overall equipment effectiveness. Issues suchas these can only truly be represented by a range of indicators, each of whichhas been implemented in a logical manner, with a clear understanding of thebehaviors that the indicator will drive.

This takes us back to the point made in the first chapter of this book. Whenoperating a car, drivers use a range of gauges and indications to ensure that thecar is operating in a manner that it should be. They do not use a combined met-ric or resort only to one indicator. If this concept is true at the level of opera-tion of a simple automobile, how could it be dramatically different when oper-ating complex and large-scale machinery installations?

Benchmarking and Best Practice

Benchmarking is a term that is often used in the field of asset management;however, at times the application of this method is not in keeping with the


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23 The only real variable in these sorts of equipment is production rate, which is controlled by customer

demand.




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requirements of capital-intensive industries. This section will attempt to clarifysome of the myths and misunderstanding around this area. There can be nodoubt that, when applied correctly, the principals of benchmarking can addsubstantial value to a corporation. However, there can also be no doubt that it

can also be a large waste of time.

Benchmarking and Best Practices

Xerox Corporation first coined the term benchmarking in 1977-1979. Theyused it to define a management tool for the monitoring and ranking of theirproducts against the products of their competitors. It is a continuous process ofmeasurement and comparison of business processes and performance againstprocesses and performance in other organizations. The goal of benchmarking is

twofold.

Identify the strengths and weaknesses of current performance.

Determine best practices that have contributed to the success of marketleaders.

At its heart, benchmarking is a tool for increasing the ability of an organiza-tion to compete within its chosen markets. As such, it fits in with the statedintention of the MSC. While it is important to be aware of what competitors

may be doing in the area, merely repeating the performance or actions of com-petitors is more of a competitive necessity than a competitive advantage.

Although the original intent of benchmarking was for comparison withother organizations, it can also be used as a tool for the analysis and compari-son of different areas within the same organization. It is also used by variousindustry regulators throughout the world to provide a guide to pricing and effi-ciency improvements that are required by companies under their remit. Thegoal of benchmarking initiatives needs to be highlighting of unique practices

that provide some substantial competitive or strategic benefits. These are oftenreferred to as best practice.

A benchmarking survey conducted by the European Centre for Total QualityManagement provided an interesting insight into the results gained from bench-marking implementations. This study involved 227 corporations in 32 differentcountries and is a good representation of the types of benefits an organization canexpect from a benchmarking project. The survey was aimed at evaluating thelevel of benchmarking maturity reached across different industry fields.

A surprising result was the relatively low percentage of companies thatreported innovative approaches to business improvement or improvements inquality.

The highest benefits were achieved in the areas of-

Influencing the strategic decision making process





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Allowing more effective deployment of resources

Process Improvement

Regardless of the strategic benefits that the technique offers, benchmarking

cannot be easily and randomly applied. There are several factors within assetmanagement that restrict, severely, the application of the method. These factorsare best grouped under the following headings-

Determining what to measure and understanding the operational environ-ment

Determining best practices based solely on economic benefits gained

Determining what best practices are generic and are able to be applied in

any industry

What to Measure and Operational Environment

This is by far the most important point to consider when embarking on abenchmarking project. It is also a key contributing factor to one of the otherkey issues, finding benchmarking partners.

We now operate within an open market. Our competitors may come fromthe United States, Europe, Asia or Latin America. As such, if we are looking to

define practices that are driving extraordinary performance, we need to lookoutside of our immediate areas. Even within similar markets, there are oftenvast differences in the way that organizations do business.

While it may be fantastic to realize that we are among the best maintenancepractitioners in the manufacturing sector of Ohio, that does not assist us at allwhen our main competitors come from China. This opens the issue up to arange of potential problems and difficulties in applying benchmarking. First,we need to know what to measure.

For example: A common benchmarking measure in the areas of asset manage-ment is percent of overtime worked. For the sake of the example we will look at thismeasure based on a weekly period. The basis of this measure is to be able to pointout that corporations that are market leaders are those that are able to operate witha percent of overtime worked of 5% (for example).

However, under closer scrutiny it can be found that this measure is not a goodcomparative guide at all. Almost every corporation in the world today operates withdiffering contracts of employment. Some companies may pay overtime and may usea timesheet system to do so. Other corporations may use a salaried option whereby

overtime is not measured nor is it recorded. In the second company they have foundthat by offering higher salaries to their employees, they can expect a reasonableamount of overtime from their employees without additional pay.

This becomes even more complicated once we look outside of familiar territory. Inmany organizations in the developing world, standard wages are not adequate for





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most people to live comfortably. As such they are regularly offered overtime as ameans of rewarding good performance and other initiatives. In other organizations,where labor is not a high cost, the cost of overtime is rarely even considered. Laboris cheap, so if it needs to be done just do it!

This also extends to other measures such as supervisor to technician ratios. In someindustries this ratio can easily be kept low. In the water distribution industry thereis often not a high level of supervision required, particularly when a company man-ages potentially hundreds of treatment works over hundreds of miles. Yet, in the gasextraction industry a higher level of supervision is required for reasons such as safetyassurance or managing the flow of workers in reaction to unexpected events that arestill common in some capital-intensive industries.

All of these facilities operate in vastly different operational contexts. Some have

higher levels of technology to be maintained, some have to deal with higher customerexpectations and others have to deal with highly corrosive materials that require spe-cial attention.

When we look at these simplistic examples, where does that leave some ofthe standard benchmarking measures offered up as a means of benchmarkingin a generic fashion? It quickly becomes obvious that many of these measuresare not adequate to assist companies in determining any form of competitiveadvantage. In fact they are only ever relevant when a host of other factors coin-

cide to enable a direct comparison. This also applies to a range of other bench-marking type measures that do not take into account the differences in opera-tional environments of differing companies. Determining what to measure isheavily dependent on which partner the company is able to find to do a bench-marking survey.

Another example of misplaced application of benchmarking can be found infinancial indicators. As has been discussed, competition within the global mar-ketplace is becoming more and more open. As such, any benchmarking initia-

tive that uses financial costs as its base can be misleading in the results that itprovides. As a side issue it is important, when comparing performance, not toconfuse low cost with low quality. At the time of writing, India produced thegreatest number of engineering graduates, per capita, of any country in theworld. This has given them the resource of highly skilled professionals availableat lower costs than many developed nations.

An example of erroneous application of benchmarking initiatives is in the costper foot2 (or meter2) maintained measure that is used in facilities management.

This measure seems to be applied despite the fact that the facility in question maybe-

An urban shopping mall

A specialty store in Beverly Hills





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A sports stadium

A factory

A plant with corrosive substances (such as an ammonia plant)

If one market were to be focused on, within which all corporations had similartechnician costs, then this could be an applicable measure. Once we go outside offamiliar borders this indicator can point to a vast difference in Cost per foot2main-tained between facilities managers of the United States and Mexico (for exam-ple).This goes for all price comparisons; all types of unit costs comparisons will haveto take into account lower labor costs. However there is a need for an objective viewhere. If corporations are truly after increased profitability over all else, which isdebatable, then a comparison such as this will show that their wages costs are far toohigh compared with up-and-coming competitors. As such it may lead to a conclu-sion that the best option for low cost production is to-

a) Move the operations to economies where labor costs are lowerb) Try and reduce the labor costs within their current place of business

In fact, benchmarking comparisons such as these contribute to the justificationsof many of the movements of capital throughout the world, initially from the UnitedStates to low-cost Mexico, then from Mexico to China and so on.

If cost comparisons are to be applied then they need to be applied in a man-ner that either restricts them to companies within similar local cost factors ormanages them in a manner that eliminates local cost factors from any compar-ison. A possible way is to compare the cost benefits percentage of cost reduc-tions as a measure of improvement initiatives. Even here there are issues. Acompany may operate in a remote location, thus exposing itself to high trans-port costs for parts. After conducting a costs/benefits analysis it determines thatit is more efficient for it to continue paying high transport costs rather than tryto manage with an extensive maintenance store. As such this company has abuilt-in and accepted higher threshold of maintenance costs. This will also dis-tort any benchmarking effort.

Another element of cost comparisons is ensuring that the same definitionsare used throughout the group of companies that are undergoing the bench-marking process. Some firms apply maintenance costs to only the costs arisingfrom day to day maintenance activities; others may choose to include the costsof modifications or renewals in this category. This issue in particular often raises

its head in regulated industries. In these industry types, government bodiesinvariably use some form of benchmarking process to establish best practiceunit cost operations. However, the problem comes in the way that differentcompanies assign and manage their costs. In some instances what may bedeemed as capital expenses are treated as a part of operational expenditure. In





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other cases, it may be that operational maintenance expenditure includes build-

ing and facilities maintenance also.The final factor in understanding operational environments of different

companies relates to how the equipment is used and operated. Here a vast

amount of work needs to be done. This can cover a range of areas from theenvironmental conditions where companies operate to the regulatory environ-ment that they operate in. Some regulatory frameworks have been rather ill

conceived and actually encourage high costs in operational management to fitin with regulatory timetables.

For instance, we will take the example of three electricity transmission companies.To negate the effects of regulation, all use overhead power lines as a means of trans-

mission and all operate within the United States.Company 1- Transmission Company based in Arizona. The environment is dry,

dusty and hot. The principal effect to them from the environment is in the build upof dust on the lines. As such they are required to frequently employ live-line wash-ing techniques in order to reduce the risk of power loss to their clients.

Company 2 - A transmission company based in Minnesota. A concern to this firmis the build up of snow and ice around the insulators and lines. In order to mini-

mize their risks of power loss for their clients, this company is forced to take meas-ures substantially different from those of their counterparts in Arizona.

Company 3 - A transmission company based around the forested areas of Raleighin North Carolina. In this scenario the main gnawing failure mode to this organi-zation is the growth of trees close to the power lines. As such their costs of preventionare on tree trimming services.

Those three companies perform fundamentally the same tasks, in three vastly dif-

ferent environments within the same general market. In these cases comparisons ofcosts would be inaccurate because all have different factors to contend with. In asimilar fashion, reliability measures may also be difficult to compare. The Raleighcompany may be suffering high fault incidence due to unusually high rainfall thathas enabled rapid growth around its transmission lines, for example.

There can also be no understatement of the effects of regulation, or the lackof it, when comparing two companies. The effect of this changes from country

to country. In some countries large-scale utility companies are still owned by

the state, reducing the requirement for cost-effective operation and focusingresources instead on safety and continuity of supply issues. Yet, they still mayhave some practices that are ahead of the market in terms of the results they

achieve, this is particularly the case as these sorts of corporations generally havelarge-scale internal reliability departments.





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Looking for Purely Financial Benefits

At a corporate level it is realized that while profits are paramount, they can-not be achieved at the cost of other areas of risk management. This is the

essence of responsible asset management and is a driving factor in the changesthat we are seeing across the globe in areas of asset management.As such any best practices that are noted in a benchmarking survey must first

be analyzed prior to adopting them. For example, a practice may have becomelowest the cost option by neglecting safety considerations. Alternatively, theremay be several practices that have lowered the costs of effective safety manage-ment and can provide an equal level of benefits to a corporation.

Recognizing Generic as Opposed to Specific Best practices

Defining best practices often falls into two specific areas. First there are newways for us to go about what we are currently doing. These are generally processspecific practices that can change the efficiency or effectiveness of day-to-dayactivities. However from time to time there are paradigm-shifting practicesnoted that have the ability to revolutionize the way that business is done withinan industry. These can often be applied across all industries regardless of thesector or operating environment.

In the recent past in engineering there have emerged two generic best prac-

tices. One is the best practice of RCM, originally from the U.S. airlines industryand now used across the world in all types of industries. The other, TotalProductive Maintenance, originated from the Japanese auto manufacturingindustry and is now applied to a wide range of industries throughout the world.

Recognition of such practices is often not easy, as is underlined by the raritywith which they have appeared. Many organizations will protect their intellec-tual capital when it comes to the development of new approaches such as these.However, they can exist on a smaller scale. They may include sending dieselengines off-site as a means of controlling overhaul quality and reducing direct

labor costs, potentially outsourcing the planning of plant turnarounds. Theymay even include routine detective activities to electrical switchgear as a costeffective means of managing risk exposure.

In summary, the areas of benchmarking and searching for best practices areareas that can help corporations to achieve substantial strategic advantages.However, it can be seen that attempts to execute wide-ranging benchmarkingstudies are often flawed because they do not take into account the operationalenvironments of each individual business. In these efforts there is generally a lot

of interesting information developed, but the benefits are doubtful at best. If abenchmarking project is to be successful, then it needs to follow some basicguidelines-

1) What to measure and how it should be measured are heavily dependenton the operational environments of each company in the benchmarking





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efforts. Questions should focus on issues such as innovative practices inproductivity improvement; safety and risk management improvement,and efficiency improvements.

2) A focus on costs can only truly be effective within companies that share

similar local cost factors. Comparisons with companies from low-costlabor economies will distort the results. What may be acceptable is meas-uring the percentage of cost reduction as a result of applying certain ini-tiatives. This steers away from total costs and focuses on improvementonly. However if a true benchmark of lowest cost production is required,this may be an option.

3) All benchmarking projects, whether internal, external or defining best inclass, need to have at their core the ability to define unique practices that

are the enablers for exemplary performance in a specific process or area.These need to be generic enough to be applied from one industry toanother without major alteration.

4) All results of benchmarking projects need to be further analyzed prior toimplementation. An irresponsible neglect of safety may be acceptable insome economies, while it may not be in others. All best practices need tobe understood for their full effects, not just the economic effects.

5) Although benchmarking continues to gain ground as a strategic tool formany organizations it is worth recalling that mimicking our competitors

does not necessarily provide us with competitive advantages.

Benchmarking is supported by the MSC. By finding companies that work inthe same operational environment, with similar processes and local factors, wecan compare our performance with others to determine what are the best prac-tices that have contributed to higher levels of performance. The measures usedwithin the MSC facilitate this and allow us to see outside of our current envi-ronment.

The MSC also adds an additional perspective to this exercise. By having

worked through the corporate planning and strategy sessions, companies arealready aware of the types of performance that they need to achieve, the typesof initiatives that they need to take and the types of timeframes that they believeare able to be achieved. Implementation of these aspects provides companieswith a pre-existing structure within which best practices can be integrated rap-idly, and corporate measures and strategies changed to suit almost immediately.



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