How to measure the added value of maintenance?

Specialization:

Production Engineering and Logistics

Report number: 2013.TEL.7745

Title:

How to measure the added value of

maintenance?

Delft University of Technology

FACULTY MECHANICAL, MARITIME AND MATERIALS ENGINEERING

Department Maritime and Transport Technology

Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl

This report consists of 103 pages and no appendices. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all legal rights on liabilities concerning the contents of the advice.

Specialization:

Production Engineering and Logistics

Report number: 2013.TEL.7745

Title:

How to measure the added value

of maintenance?

Author:

E.P. van Os BSc.

Title (in Dutch) Het bepalen van de toegevoegde waarde van onderhoud

Assignment: literature

Confidential: no

Supervisor: Dr.Ir. H.P.M. Veeke

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Summary

A parsimonious view on maintenance exists because the relation between cost and benefits of

maintenance is not clear, leading to overly cost cutting. Notwithstanding, optimization of maintenance also gives rise to the need for knowing the cost and benefits of maintenance. Furthermore,

maintenance is tied to risk mitigation and improving Safety, Health and Environment (SHE). The above, as well as the fact that performance measurement acts as management tool, all fuel the need for a performance metric that discloses the added value of maintenance. Such a metric should disclose all cost and all benefits of maintenance including SHE aspects and allow simultaneous assessment of these to show the overall added value of maintenance and allow optimization. This paper investigates whether a means of performance measurement is available that meets the above requirements.

Conventionally used maintenance metrics are not capable of disclosing the added value of

maintenance. Four methods of maintenance performance measurement are examined therefore to see whether they are able to disclose added value of maintenance, and have rendered success in doing so in practice.

Mathematical maintenance optimization models aim to model maintenance actions and their effects. Apart from incorporating SHE aspect, these models meet all requirements in theory but fail to be useful in practice due to the complexity following the incorporation of minutiae and subsequent need for data (data problem).

Total Productive Maintenance (TPM) combines quantitative and qualitative approach. The method is widely adopted in practice, and has met with approbation. However, its legacy metric Overall Equipment Effectiveness (OEE) does not nearly cover all costs and benefits and as such fails to disclose added value of maintenance.

The Maintenance Scorecard (MSC) approach qualitatively derives a comprehensive list of performance metrics from corporate strategy. Although covering most of the costs and benefits, a collection of individual metrics is unable to disclose the overall added value of maintenance.

Value Driven Maintenance (VDM) is a novel method aiming to calculate the added value of maintenance, which has already been rapidly espoused by the field of maintenance. The method starts by determining what would offer most value (e.g. more uptime, cost reduction) to focus maintenance efforts. The method does suffer from a data problem, although reduced as compared to mathematical modeling

In conclusion, the VDM method is appointed as being the method that is best suited to be a performance measurement method capable of showing the added value of maintenance and allow optimization.

In addition to this conclusion, it is noted that the very act of quantifying the benefits of maintenance in monetary terms is not common in the field of maintenance. The problem statement including the parsimonious view on maintenance, relegating it to second concern next to production, may very well stem from this omission.

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Summary (in Dutch)

Onderhoud wordt veelal beschouwd als een louter kostenpost, omdat de relatie tussen de gemaakte kosten en de voordelen die het oplevert onduidelijk is. Dit leidt tot overmatig beknibbelen op onderhoudskosten.

Het inzichtelijk maken van de kosten en voordelen van onderhoud is tevens een voorwaarde als men onderhoud zal willen kunnen optimaliseren. Een van die voordelen van onderhoud is het beperken van risico’s met betrekking tot veiligheid, gezondheid en milieu (VGM).

Bovenstaande observaties, evenals het feit dat het meten van prestaties als management tool dient, voeden de noodzaak en behoefte aan een manier om de toegevoegde waarde van onderhoud inzichtelijk te maken.

Een dergelijke indicator zal alle kosten van-, en voordelen die voortvloeien uit onderhoud, met inbegrip van VGM aspecten, moeten omvatten. Tevens zal deze indicator al die kosten en voordelen simultaan tegen elkaar moeten kunnen afwegen om zo de toegevoegde waarde te bepalen, en het optimaliseren van onderhoud mogelijk te maken.

Deze literatuurscriptie onderzoekt of er een prestatie indicator is die aan bovenstaande voorwaarden voldoet.

Conventionele prestatie indicatoren het gebied van onderhoud blijken niet n staat om de toegevoegde waarde aan te geven. Daarom worden er vier methoden om onderhoudsprestaties te meten

onderzocht.

Onderzocht wordt of elk van deze vier methoden in staat is om de toegevoegde waarde van

onderhoud aan te geven, en of er praktijkvoorbeelden bestaan van het succes van de methoden. -Wiskundige onderhouds-optimalisatie modellen hebben ten doel om de effecten van elke

onderhoudshandeling te modelleren. Afgezien van het feit dat dergelijke wiskundige modellen geen VGM aspecten meenemen, voldoen ze in hun theoretische opzet aan de eisen. Succesvolle toepassing in de praktijk komt echter nauwelijks voor omdat de gedetailleerde modellen te complex blijken en er te weinig gegevens voorhanden zijn om ze te voeden (data probleem).

-Total Productive Maintenance (TPM) is een combinatie van een kwantitatieve en kwalitatieve

methode. De veelgeprezen methode wordt in de praktijk veel toegepast. De enige prestatie indicator van de methode, de Overall Equipment Effectiveness (OEE) is echter niet geschikt om alle kosten noch voordelen van onderhoud te omvatten. Als zodanig is het dan ook niet mogelijk om de toegevoegde waarde van onderhoud in deze ene indicator te vangen.

-De Maintenance Scorecard is een volledige kwalitatieve aanpak. Deze methode leidt uit de bedrijfsstrategie een selectie van prestatie indicatoren af. Hoewel de resulterende verzameling indicatoren alle kosten en voordelen van onderhoud beslaan, is het niet mogelijk om uit een verzameling losse indicatoren de toegevoegde waarde te abstraheren.

-Value Driven Maintenance (VDM) is een nieuwe methode die ten doel heeft om de toegevoegde waarde van onderhoud aan te geven. De methode wordt in toenemende mate omarmd in de onderhoudsbranche. Datgene wat de meeste toegevoegde waarde oplevert (bijv. uptime of

kostenreductie) wordt als eerste vastgesteld, om vervolgens de onderhoudsacties daarop te kunnen richten. Ook in deze methode doet zich het eerder genoemde data probleem voor, zij het in

verminderde mate vergeleken met volledige wiskundige modellen.

Concluderend wordt de VDM aangewezen als de meest geschikte voorhanden zijnde methode om de toegevoegde waarde van onderhoud aan te geven en het onderhoud te kunnen optimaliseren. Bovenop deze conclusie wordt opgemerkt dat het kwantificeren van de voordelen van onderhoud (in financiële termen) niet gebruikelijk is in het vakgebied van onderhoud. Het feit dat dit tot nog toe nauwelijks gebeurt, draagt zeer waarschijnlijk bij aan de visie op onderhoud als ‘louter kosten post’ zoals gesteld in de probleemstelling.

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List of Abbreviations

BSI British Standards Institute

CAPEX Capital expense

CBM Condition Based Maintenance

COPM Cost of Poor Maintenance

KPI Key Performance Indicator

LTO License to Operate

MTBF Mean Time between Failures

MTTR Mean Time to Repair

OEE Overall Equipment Effectiveness

OEEMB Overall Equipment Effectiveness Market Based

OEEML Overall Equipment Effectiveness Manufacturing Line

OPEX Operational Expense

OTE Overall Throughput Efficiency

SHE Safety Health & Environment

TEEP Total Effective Equipment Performance

TPM Total Productive Maintenance

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Table of Contents

Summary ... 4

Summary (in Dutch) ... 5

Table of Contents ... 8

Introduction ... 11

1. The need for performance measurement in maintenance ... 13

1.1

Maintenance is viewed upon as cost center ... 13

1.2

Performance measurement as a prerequisite for optimization ... 14

1.3

Risk aversion through maintenance management ... 15

1.4

Performance indicator as a management tool ... 16

1.5

Conclusion ... 21

2. Maintenance ... 23

2.1

Definition ... 23

2.1.1

Maintenance typology: Planned versus unplanned ... 25

2.2

Maintenance in the production function ... 27

2.2.1

Performance of production system: Effectiveness, efficiency, productivity ... 27

2.2.2

Performance of maintenance system: effectiveness and maintenance ... 32

2.2.3

Reliability and availability of production system ... 34

2.3

The size of maintenance ... 35

2.4

Optimal maintenance ... 36

2.4.1

Cost cutting: aiding efficiency or harming effectiveness? ... 36

2.4.2

Optimizing ... 38

2.4.3

Integrated approach ... 39

2.5

An example of optimal maintenance ... 40

2.6

Changing view on maintenance ... 42

2.7

Conclusion ... 43

3. The costs and benefits of maintenance ... 44

3.1

Costs of maintenance ... 45

3.1.1

Costs found in literature ... 45

9

3.2

Benefits of maintenance ... 49

3.2.1

Benefits found in literature ... 53

3.3

Intermediate Conclusion ... 55

3.4

Cost or yield? ... 56

3.4.1

Focus on benefits ... 57

3.5

Existing KPIs in maintenance ... 58

3.5.1

What are conventionally used metrics? ... 58

3.5.2

Measuring added value with conventional metrics ... 59

3.5.3

Single KPI versus performance measurement system ... 61

3.6

Conclusion ... 62

4. Maintenance measurement methods ... 64

4.1

Mathematical maintenance optimization models ... 65

4.1.1

Definition of Mathematical Maintenance Optimization Models ... 65

4.1.2

Drawbacks and Benefits of Mathematical Maintenance Optimization Models ... 68

4.1.3

Data problem ... 68

4.1.4

Practical use of Mathematical Maintenance Optimization Models... 68

4.1.5

Conclusion on Mathematical Maintenance Optimization Models ... 69

4.2

Total Productive Maintenance ... 71

4.2.1

Class of Quantitative/qualitative methods ... 71

4.2.2

TPM Total productive maintenance ... 71

4.2.3

TPM use ... 73

4.2.4

TPM Benefits and drawbacks ... 73

4.2.5

Conclusion TPM ... 76

4.3

Maintenance Scorecard ... 78

4.3.1

MSC maintenance Scorecard ... 78

4.3.2

Class of methods to select KPIs from strategy ... 80

4.3.3

MSC Benefits and Drawbacks ... 81

4.3.4

MSC Use... 82

4.3.5

Conclusion MSC ... 82

4.4

Value driven maintenance ... 84

4.4.1

VDM Value Driven Maintenance ... 84

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4.4.3

VDM Use ... 90

4.4.4

Conclusion VDM ... 91

5. Conclusion ... 92

5.1

Conclusion ... 92

5.2

Reflection ... 95

5.3

Discussion ... 96

Suggested further reading ... 98

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Introduction

“They break it, we make it”. That is perhaps the most archaic description of maintenance. Nowadays maintenance has evolved into a discipline which comprises more than just repairing failed equipment. Maintenance encompasses a plethora of activities, aimed not only at repairing but also preventing failures.

As the discipline of maintenance has become more intricate and has grown to be a substantial part of all activities (and thus costs) within companies, the question arises how to measure performance of maintenance. The archaic perception of maintenance and its objective, that is simply concerned with fixing breakdowns, means that the performance can be readily measured by taking notion of such indicators as the time to repair and the cost of repair.

The more complex nature of current maintenance makes defining and thus measuring maintenance performance accordingly more complex. Indeed the area of maintenance struggles to disclose all its effects and therefore attract acknowledgement commensurate to its relevance.

In fact, it will be established that maintenance is an equivocal matter: Literature advocates the all-encompassing relevance of maintenance, whereas a derogatory attitude towards maintenance is entrenched in general management.

This paper revolves around measuring the performance of maintenance. Therefore, the paper is relevant to maintenance as well as the production system it serves, and the business it ultimately serves, as a need for a performance measurement stems from all these areas. The problem statement pertains to maintenance in general industry. The theories developed in this paper are applicable to general industry. Software maintenance, due to its special nature, is excluded from this definition as the concept underlying industrial maintenance in general, such as wear, degradation are not relevant in software.

How to measure maintenance performance? That is the problem statement initiating this paper. By looking into the need for a performance metric, and thus the problem statement more closely we establish what such a measure should include (chapter 1). Based on this further study of the problem statement, the main research question is defined:

Research question: How to measure the added the added value of maintenance?

The equivocality mentioned earlier makes this literature research one of the empiricism versus theory type. The second chapter elaborates on the empiricism. Chapter 1 also infers conditions that a performance metric should meet in order to answer the main question. As these conditions will show to relate to maintenance costs and benefits, chapter three will elaborate on the sub question:

Sub question 1: What are the costs and benefits of maintenance?

The subject of maintenance is studied further in the second chapter to gain understanding of the subject.

Having established the conditions, and knowing which costs and benefits it should be capable of disclosing, we have narrowed down the problem statement and main question. We have arrived at the conditions that a metric should meet in order to have the ability to measure added value, yet we have not selected an actual metric.

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Sub question 2: Can conventionally used performance metrics measure the added value of maintenance?

This sub question directly imposes an additional sub question that needs answering first: Sub question 3: What are the conventionally used performance metrics?

Answering both questions indicates that conventional performance metrics are not without limitations. Therefore the question will be expanded:

Sub question 4. Can a method be found to measure the added value of maintenance?

Four maintenance performance measurement methods are assessed using the conditions pursuant to chapters two up to four. The conclusion, chapter 5, will discuss whether a performance measurement method exists that meets the conditions and, if so, how it does or does not answer our main research question and subsequently addresses the problem statement.

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1. The need for performance measurement in

maintenance

Various reasons can be identified that fuel the need for performance measurement in maintenance. This chapter will further investigate this need which exists in current maintenance practice. All four reasons are distilled from literature on empiricism. In other words, this chapter takes stock of real world problems with regard to performance measurement.

Paragraph 1.1 up to 1.4 will each elaborate on distinct reasons why a suitable way of measuring performance is called for.

In conclusion, it turns out that these distinct reasons give rise to a research question to be defined, and number of conditions that a performance metric should adhere to (paragraph 1.5).

1.1

Maintenance is viewed upon as cost center

The added value of maintenance is not acknowledged. That statement is a complaint often expressed by maintenance managers and staff. (Tsang, 2000) indicates that maintenance is especially viewed upon as a cost or necessary evil and is therefore prone to cost reduction programs.

(Alsyouf, 2004) confirms this view. In his survey, among managers in general industry, a vast majority of respondents indicated that maintenance is indeed seen as a necessary evil and not as a value adding activity.

(Jonsson, 1997) blames a lack of visible relation between maintenance activities and the profit made, as reason for a too low interest in maintenance from corporate management.

(Wiremann, 2005) also points out the simplistic relation that managers assume between maintenance and profit. Since it is an expense, any achievable reduction in (seemingly unnecessary) maintenance is seen as a direct contribution to profit.

Furthermore (Dekker, 1996) addresses this issue and states that the stochastic nature of maintenance need (such as the occurrence of failures) prevents a clear judgment (or acknowledgement) of

individual maintenance decisions and their effects, leading to a hard estimation of a reasonable maintenance budget at macro level. Again due to this fact, maintenance is viewed upon as a cost function.

The fact that maintenance is seen as a necessary evil, a cost function, rather than a value adding activity is more than just a burden to the maintenance manager’s pride. The attitude described results in a situation where maintenance is prone to cost cutting (Saltzer, 2010). It is therefore that a large amount of the literature on maintenance actually pitches the term ‘justification’ when it comes to maintenance (e.g. Salonen & Deleryd, 2011. Parida & Chattopadhyay, 2007. Muchiri et al., 2010. Kodali et al., 2009. Simões et al., 2011. Ahmadi et al., 2010. Dekker, 1996. Koochaki et al., 2011). Production, as primary goal of an organization, receives attention over maintenance, even though maintenance is of large importance to said production (Mata & Aller, 2008).

(Kodali et al., 2009) also see the maintenance function under the same tension between production as primary focus and maintenance being something of an afterthought. In other words, production is planned, and maintenance is to react. The fact that production enjoys preponderance over

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“typically resources and funding are provided to ensure that production is planned and scheduled with great care, but in the same operations department, maintenance is put into a position to only react”, confirming that maintenance is viewed as a sheer cost center.

This calls for a performance indicator that reveals the added value of maintenance. It should translate the merits of maintenance in the (financial) lingo of management.

• A maintenance performance metric should reveal the added value of maintenance.

In other words, the benefits inflicted by maintenance should be disclosed next to the maintenance.

1.2

Performance measurement as a prerequisite for

optimization

However, it is not just the (financial) interplay between maintenance manager and (general corporate) management that incurs the need for performance measurement. The maintenance manager himself should also have performance measurement at his disposal. The fierce competition in today’s industry demands optimization of business practices. In his book (Wiremann, 2005) describes a shift in focus in recent years. In times when economies flourish, focus is on growth and ‘’breakthrough events” (Wiremann, 2005, p. 1). Maintenance, in line with the view described earlier, simply had to follow along, delivering the required capacity. However, in economic downturn the strain on competitiveness increased. This forced companies to pursue any improvement possible through improvement and optimization programs, including maintenance (Sharma et al., 2011). This pursuit of optimization is found in areas outside maintenance as well (e.g. Supply Chain Integration, Total Employee

Involvement, Lean manufacturing etc.).

The pursuit of improvement, combined with a simplistic view on maintenance as a cost function (i.e. reducing maintenance costs is a direct contribution to business result) puts maintenance under pressure. Especially when considering the fact that maintenance makes up a large portion of operational expenses.

This paper will argue that maintenance can be viewed upon as value adding activity, rather than a cost function. However this does not circumvent the need for improving maintenance performance in any way. Au contraire, the very fact that maintenance is an activity that influences business goals in many ways (see chapter Error! Reference source not found.Error! Reference source not found.) makes it especially eligible for improvement practices, in order to benefit business goals as much as possible.

In order to improve maintenance performance, a suitable (set) of performance indicators is called for. After all, only with a suitable indication of performance we can set a goal, or at least can give

direction to, and measure progress made in optimization.

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1.3

Risk aversion through maintenance management

On top of these business orientated arguments to abandon viewing maintenance as a mere cost center a distinct phenomenon is witnessed that emphasizes the importance of maintenance; Large impact catastrophic failures that are related to poor or lack of maintenance. (Mather, 2004) identifies a 24 hour power outage in New York, The Columbia Space Shuttle disaster and a fatal train accident in the UK as examples. The public opinion, in combination with new legislation that makes asset owners responsible for manslaughter, puts maintenance on the agenda of boardrooms. (Parida & Kumar, 2008) also add to this a 2005 refinery explosion in Texas. Besides fatalities, it led BP to pay over 1 billion dollars in settlements, in addition to other costs incurred. More recently, the BP oil spill disaster in the Gulf of Mexico in 20101 _{could be added to the list where maintenance deficiencies are}

linked to risk exposure on a strategic level. In this particular case, the pressure of cost-cutting and poor maintenance was specifically mentioned as root cause2. This aligns with our earlier statement that maintenance cannot be seen as a mere cost center that is to be minimized.

The license to operate (LTO) is a concept that is becoming generally accepted as a precondition for businesses to operate. Either as a ‘moral license’ that is granted by customers (through their procurement decisions) and other stakeholders, or as a true license with legal ratification and ramifications. Either way, risk aversion is key in obtaining and especially retaining such a ‘license to operate’. Maintenance is an important means of achieving reduced risks.

The above strengthens the need for a performance indicator for maintenance. Even though maintenance is more than a cost function and the above incidents show the impact of poor maintenance, this does not imply that maintenance is to be an area without boundaries. After all, maintenance will always be competing for scarce resources. And those resources that are to be assigned should be used as efficiently and effectively as possible.

Hence the need for a performance measurement indicator is called for, that covers the Safety, Health and Environmental (SHE) related yields of maintenance. Only then can the amount of maintenance (resources), necessary to reduce risks to an acceptable level, be determined and allocated whilst acknowledging that limits apply to the costs of this risk reduction.

• A maintenance performance metric should disclose Safety, Health an Environment effects of maintenance.

It is worth noting in light of the above mentioned catastrophic failures that, although execution (responsibility) of maintenance can be (and increasingly is being) outsourced, liability (accountability)

1

On April 20th 2010, a wellhead blowout (11 fatalities) at the Macondo well in the Gulf of Mexico (Deepwater Horizon rig) resulted in an oil spill of 4,9 million barrels. The leak wasn’t sealed until 19th of September. The liability for BP is unprecedented: BP has agreed to create a 20 billion USD response fund, financed by selling 10 billion USD assets, cutting OPEX and dropping dividend. Liabilities remain all the while. Furthermore, BP is temporarily dismissed from bidding US gov. contracts due to lack of business integrity.

2

National Commission on the BP Deepwater Horizon Oil Spill and Offshore Drilling. Deep Water The Gulf Oil

Disaster and the Future of Offshore Drilling Report to the President. Washington, USA: U.S. Government

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cannot. Liability will remain at the asset owner at all times (Mather, 2004). Regarding outsourcing, which is an increasing trend in maintenance, (Panesar, 2008) notes that the field of outsourcing struggles to find suitable performance indicators. Contracts are seldom performance based, and when they are (through the use of key performance indicators, KPIs) detrimental effects occur such as neglecting non-KPI items or blaming lack of performance on factors outside the contractors’ influence (Kroha, 2003). In short, outsourcing as an activity is not an area where we can tap into to find a suitable performance indicator for maintenance. Rather, what is found is just another cry for a comprehensive performance indicator. In fact, (Al Turki, 2011) explicitly mentions the capability to assess and monitor the delivered (maintenance) service as an absolute requirement for outsourcing. Should a company lack this ability it should not even consider outsourcing.

(Parida & Kumar, 2008) confirm this view. Due to outsourcing the ownership and management of assets become separated. Combined with an ever more complex and competitive nature of maintenance, Parida & Kumar stress the importance of being able to measure performance of maintenance.

1.4

Performance indicator as a management tool

(Mather, 2004) identifies how performance metrics used in the field of maintenance drive behavior. Metrics allow management to make more informed (maintenance) management decisions as well as keep track of the results and subsequent progress. This was already mentioned in the earlier

paragraph on optimization. Mather distinguishes an extra merit of these metrics. They drive behavior and operate as a motivational tool as such (on an operational level). In fact this can explicitly be identified as one of the reasons of measuring maintenance performance.

It is a well-known phenomenon in many disciplines of science that measuring a system in turn affects the system. In science this phenomenon is often unwanted (e.g. a thermocouple disturbs the thermal balance of the small physical system being measured). In maintenance management it is not harmful in itself. In management the objective is not just to study the system, but especially to control it. Influencing behavior of human elements within the system is important in this respect.

A performance indicator can be used as a management tool for improving maintenance. By

measuring, a maintenance manager may detect problems or learn the state of the system in general. Based on this information he makes decisions. The decision might be that improvement or change of the system is called for. He then influences the system by explicitly performing an action.

Imagine a production system with a fixed input and an output that consist of two streams: those products that fall within the required quality range, and a fraction of rejects. The manager aims to keep the fraction of rejects as low as possible, if not eliminate it at all. When he measures and learns that this fraction is too high compared to a set standard, he may make adjustments to the production system. For example he may alter the maintenance policy, or he may alter (tune) the production process. He makes a conscious and purposeful decision to intervene. This is essentially KPI use as described in paragraph 1.2 on optimization. Note that the example concerns feedback (measuring the output), but feed forward can be applied equally well. A maintenance manager may measure the amount of emergency repairs as well, informing him that the process is disturbed and intervention is called for in order for the system to retain its functionality (delivering the right output).

The above is an example of well-established control theory (Figure 1). Four conditions apply when controlling any system. One must establish a goal output or state of the system (1) of which it is capable of achieving (2). Control also implicates we need ability to influence the system (3), and know precisely how to do so in order for the system state or output to move to the goal (4). Given these

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conditions are met, a control system needs presence of four elements to be able to execute control: a measurement, a goal state to compare this measurement to, a control function to decide on the intervention and a means to perform the intervention. In the above example the KPI (reject rate) defines what is measured and allows us to define a goal state for that KPI (a standard reject rate) for it. In lacking an exact goal state (value), a KPI can at least be appointed to give direction to

improvement, as was discussed in the paragraph 1.2.

Systematically, this example of use of KPI measurement in controlling a system can be illustrated as follows:

Figure 1 Feedback control using a KPI (metric), in accordance with classical control theory

However, since maintenance and production are concerned with human elements the act of measuring may influence the system. When people realize that a certain metric is used as KPI this may influence the system. This effect can be the intended effect of installing a KPI (usually

accompanied by feedback of the results, Figure 2) or it can be a side-effect. The intentional effect is that the positive behavior is realized to drive the KPI. Continuing on our schematic depiction of a controlled system, this would be depicted as follows:

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Crucial elements of a controlled system seem to be omitted (decision and intervention). This depiction therefore does not reveal how measuring and merely supplying feedback alone would influence the system. Crucial elements are left out, infringing classic control theory. How then is it possible that there is control in the system depicted? The fact that the system constitutes of human elements accounts for this. After all, human elements have (autonomous) control mechanisms at work (Figure 3). In case of our production system depicted earlier, a feedback of the reject rate could be intended to promote working more precisely. In this case, the measurement and subsequent reporting of the measurement to the system is causing the system to improve (autonomously).

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The intended result is to have good behavior (e.g. working more focused and precisely) to minimize reject rate. An unintended effect could take place as well. This would constitute for example that workers allow defective products to flow into the stock of finished goods by (deceitfully) altering the quality threshold when inspecting for defects.

The exact mechanism how performance measurement and feedback influence behavior is a subject that is left to occupational psychology. What is important to know is that performance metrics and already the collection of data without necessarily linking any further action or feedback can actually influence the system, either good or bad. Using the scheme previously used, this would constitute of system where the act of measuring already influences the system (NB without feedback, see Figure 4).

Figure 4 Simply measuring to control a system?

Well documented (Van Dooren, 2006) phenomena in literature include hypertrophy, overly focusing on those items measured. Van Dooren explains that mere measuring, without offering feedback, let alone intervention) may lead to hypertrophy, because humans implicitly assume they will be rewarded and assessed based on that what is measured (Figure 5). Atrophy is the reverse where people neglect that what is not measured. This leads to myopia. Van Dooren gives a comprehensive overview of how performance measurement influences humans, whether it be positive or negative.

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The somewhat abstract phenomenon described above is not only formally recognized in the field of occupational psychology. Without explicitly using the terminology, examples in maintenance literature can be found that perfectly adhere to the theory. An example of the above is actually seen in (Mather, 2004), who describes a case of mining. How a production KPI (output in tonnage over a period) led to overly focus (hypotrophy) on the output (tonnage), thereby neglecting safety (atrophy) which led to an unacceptably low level of safety. This effect was consciously brought about by the workers in chase of higher output figures (i.e. pursuance of improving on KPI).

(Zuashkiani et al., 2011) also describes a case where a DuPont plant was faced with a low uptime compared to other companies in a benchmark study, despite spending way more money on

maintenance. It was revealed that overly focusing (hypotrophy) on production related metrics (such as uptime) caused preventive maintenance to be compromised (atrophy). This ultimately led to more breakdowns, in turn leading to more corrective maintenance (i.e. unplanned and far more costly downtime). Opposed to the case (Mather, 2004) describes this effect was unintentionally and unconsciously brought about by people in the production system.

Finally, remember how it was mentioned in paragraph 1.3 that (Kroha, 2003) stated that the area of outsourcing struggles when using KPI based contracts, as non KPI (i.e. non contracted) items are perceptive to neglecting. Note how this corresponds with the above theory.

Concluding, it must be acknowledged that KPIs can drive behavior and thus improvement.

Performance measurement and feedback are powerful tools for a manager. One must be aware of unintentional side effects. Careful considerations must be made especially in the use and

implementation phase of performance measurement. Notwithstanding the precautions, the possibility to positively influence behavior and performance is a major reason to seek for an indicator for maintenance performance.

This has also been acknowledged in maintenance literature by (Muchiri et al., 2010) who also found companies are most satisfied with measurement systems (KPIs) that actually (explicitly) trigger decisions, as compared with KPIs that do not trigger anything. Furthermore (Tomlingson, 2007) stresses the value of KPI as a motivational tool, when properly used. (Kumar et al., 2011) also

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indicates KPI as being important in motivating people and driving good behavior. A sense of

ownership is a prerequisite for an indicator to effectively drive good behavior. Specifically he mentions KPIs are only useful when they (i.e. their value) can be influenced. This directly fits the generic control theory mentioned earlier.

The metric as management tool should be balanced to prevent dis- or hypotrophy. After all that would harm a reason of having a performance metric, optimization. Incomprehensive or unbalanced metrics were identified to actually compromise performance.

• A maintenance performance metric should be comprehensive.

1.5

Conclusion

Studying literature on maintenance practice, four reasons were established giving rise to need for a means of measuring and expressing maintenance performance. These do not only indicate the need for a performance indicator allowing performance measurement, but also indicate what a performance indicator should reveal. The reasons fueling the need for maintenance performance metric were identified to be:

• Maintenance is viewed as cost function

• Performance measurement is a prerequisite for optimization • Maintenance serves as risk mitigation

• A performance measure acts as management tool

From the four reasons, four conditions sprung that a maintenance performance metric should adhere to:

• A maintenance performance metric should reveal the added value of maintenance. • A maintenance performance metric should reveal optimal maintenance.

• A maintenance performance metric should disclose Safety, Health an Environment effects of maintenance.

• A maintenance performance metric should be comprehensive.

The four conditions identified actually show coherence. Although distinct, the conditions are not disparate.

The first condition states that the benefits of maintenance should be disclosed. However, added value is defined as the benefits supplied, after subtraction of costs. In other words, showing the added value of maintenance may be rearticulated as the condition that a performance metric reveals the cost and benefits of maintenance.

The second condition, that a metric is usable for optimization implies that it needs to cover all benefits and costs of maintenance, exactly what was identified as first reason of having a performance metric.

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These costs and benefits need to be simultaneously assessed to determine optimal tradeoffs and performance levels.

Disclosing the added value of maintenance enables optimization. After all, optimization is no more than maximizing the added value. Therefore we note that our quest for a performance metric capable showing the added value, or be used for optimization is equivalent.

Furthermore, the explicit demand that a performance metric should include risk and SHE, can, strictly speaking, be regarded as obsolete since it was already stated that a performance metric should disclose all benefits. Risk mitigation was identified to be one of these merits.

Lastly, the use of performance measurement was established to influence of said performance. To prevent the performance to be harmed, performance measurement should be balanced. Again, this leads to the conclusion that a performance metric should cover both costs and benefits and be comprehensive.

Therefore the four reasons for, and subsequent condition on maintenance performance measurement lead to the conclusion that:

1) Metric should include all costs and benefits

2) Metric should allow simultaneous assessment of costs and benefits 3) Metric should include SHE and risks

The explicit mentioning of SHE related risks is due to the special nature of risks; they are latently present and as such often overlooked, even though this merit was identified distinctly as being of strategic importance.

Since performance measurement apparently revolves around disclosing costs and benefits, to show added value and allow optimization, the research question is established:

Research question: How to measure the added value of maintenance?

The three condition (1)-(3) are identified as conditions that any means of measuring added value of maintenance should adhere to. To be able to find a metric that meets such requirements, we first need to establish:

Sub question 1: What are the costs and benefits of maintenance?

Chapter 3 is dedicated to establishing the cost and benefits of maintenance through inventorying literature on maintenance performance (measurement). This will allow determining whether currently used maintenance metrics (Paragraph 3.5) and maintenance performance measurements methods (Chapter 4) meet our three conditions.

Before embarking on said inventory of costs and benefits of maintenance, chapter Error! Reference source not found. will elaborate some more on the subject of maintenance.

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2. Maintenance

Before elaborating further on the cost and benefits of maintenance, and before finding a suitable performance metric, we will elaborate more on the concept of maintenance. In doing so, relevant terminology will be dealt with, which will prove useful when tacking stock of maintenance cost and benefits.

Paragraph 2.1 will define what maintenance is. Following the definition found, paragraph 2.2 will study the association between maintenance and the production system it serves.

Having established what maintenance is, paragraph 2.3 will determine exactly how large the area of maintenance is, to appreciate the importance.

Having gained understanding of the subject of maintenance, and its role in the production system it serves, paragraph 2.4 sets out to further define optimal maintenance, elucidated with an example in paragraph 2.5.

Before ending the chapter with a conclusion, the penultimate paragraph 2.6 will show that the parsimonious view on maintenance is changing, albeit ever so slightly.

2.1

Definition

Looking at the definitions of maintenance found in literature, it is apparent that no single strict definition exists. A variety of definitions is pitched. The commonly cited British Standards Institute defines maintenance ‘’as a combination of all technical and associated administrative activities required to keep equipment, installations and other physical assets in the desired operating condition or to restore them to this condition” (BSI, 1984, p. 1). This definition indicates maintenance should return the required operating condition. Other definitions explicitly mention a (desired) capacity as the return of maintenance, as well as levels of quality and safety. These more comprehensive views on maintenance include (Tsang et al., 1999, p. 692) who mentions maintenance to be “engineering decisions and associated actions that are necessary for the optimization of specified equipment capability, where capability is the ability to perform a specified function within a range of performance levels that may relate to capacity, rate, quality, safety and responsiveness”. Kelly identifies best practice maintenance to be: “to achieve the agreed plant operating pattern, availability and product quality within the accepted plant condition (for longevity) and safety standards, and at minimum resource cost” (Kelly, 2006b, p. 26).

Another definition mentions “those activities required to keep a facility in “as built” condition and therefore continuing to have its original productive capacity” (Sharma et al., 2011, p.5). Or “the combination of technical maintenance and associated administrative actions intended to retain an item in a system or restore the system to a normal state (Wang & Hwang, 2004, p.154). Ensuring the plant achieves the desired performance at an optimal cost, is what (Muchiri et al., 2010, p. 5906) conclude maintenance to be.

These definitions all acknowledge interplay between the act of maintenance and the plant output in terms of a variety of facets. (Kelly, 2006b) expresses the explicit demand to achieve adherence (to an agreed level) at the lowest resource costs. This definition therefore corresponds with the tension that was identified above between maintenance as a cost or an added value. Similarly, (Muchiri et al.,

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2010) mentions achieving a desired performance at ‘optimal’ cost.

The above definitions all incorporate an object of maintenance. This object is the primary production system. Depending on the definitions it is referred to as equipment, plant, (item in) a system, facility etc. Furthermore, it is apparent that the merits of maintenance materialize in connection to this primary production system.

A difference between the various definitions is that e.g. (Tsang et al., 1999) includes engineering decisions. The omission thereof in the e.g. British Standards Institute’s (BSI, 1984) definition would imply a more operational view on maintenance. Other definitions do not specify the tasks (e.g. Muchiri et al., 2010, Sharma et al., 2011), but only mention the goal of maintenance. With regard to the goal of maintenance all definitions align fairly well. To restore or preserve the functionality of a production system.

On top of that, an important conclusion is that all of the above definitions assume a fixed goal state of the production system (e.g. ‘’agreed capability’’, “accepted level” or “normal state”, “as-built”, “original productive capacity” or “desired operating condition’’). Maintenance serves such a production system in achieving those predetermined goals. This proves relevant as (in Paragraph 2.4) it will be motivated how this definition could indeed incur viewing maintenance eligible to cost cutting, and in a position to react, as was found in the paragraph 1.1.

To determine optimal maintenance, and disclose the added value of maintenance, we need to establish both the yields as well as the costs of maintenance. This will be investigated further in chapter Error! Reference source not found.. To understand these costs and befits, we need to view maintenance in correlation with the primary production system it serves, as the definitions above already indicated that the yields of maintenance materialize through the production system it serves. The correlation between maintenance and the production system is elaborated on in paragraph 2.2. Although comprehensive, the above definitions are rather abstract and perhaps trivial. More insight in current maintenance practice is gained through elaboration on the most commonly used typology of maintenance practices. These maintenance practices will be referred to in the remainder of this article.

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2.1.1 Maintenance typology: Planned versus unplanned

An important and most prevalent distinction is made between planned and unplanned maintenance. This dichotomy is also referred to as proactive and reactive maintenance. Note that the above distinction is not the same as classifying maintenance in (the well-known classes of) preventive or corrective maintenance. Indeed these two types of maintenance are examples of the former categories. However they are only two of the examples of the myriad of maintenance practices that are identified within planned and unplanned maintenance.

Unplanned maintenance takes place after a failure has occurred and the object has to be restored to its desired condition (corrective maintenance), or when maintenance is suddenly required to stop an immediate hazardous situation from occurring (emergency maintenance).

Especially the field of planned maintenance has seen an increase in attention in recent years. From the 1950s3 onwards maintenance has seen the shift to preventive maintenance, abandoning the adagio of “they break it, we make it”.

This is due to the fact that in many cases preventing a breakdown by planned maintenance is regarded to be more cost effective than a breakdown that occurs and requires unplanned corrective maintenance. A completely analog vision exists with respect to maintenance as means of risk aversion, as specified in paragraph 1.3. Risk aversion (prevention) by means of maintenance is seen as ultimately being cheaper than the occurrence of such risks. A famous quote in the science of Safety, Health and Environment illustrates this: “If you think safety is expensive, try an accident!”4_.

Indeed, looking back at the examples given earlier (such as BP oil spill) one must value this quote. Within planned maintenance a distinction is made between preventive and predictive maintenance. Preventive maintenance aims at applying timely maintenance actions before a failure occurs. Alternatively it is explained to be the prevention of recurrence of failure, in other words apply continuous improvement actions to prevent the recurrence of failure at all. In either case, preventive

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According to many literature studies, preventive maintenance originates in 1951 in USA and was adopted in Japan that year. All literature seems to copy this statement regarding 1951 from one another (often literally citing, without stating a source) without questioning. Tracing back all sources mentioned, no primary source was found that originated this widely adopted statement. Nor was it mentioned in any of the literature found why 1951 is specifically seen as the origin of preventive maintenance? Was the term never pitched before, or merely corrective maintenance applied? Probably not.

Most likely, the statement above, as found in many literature, pertains to the year when U.S. Statician Dr. W. Edwards Deming (1900-1993) contributed greatly to Japanese industry and initiated developments of concepts that would ultimately evolve to Total Productive Maintenance, TPM. Preventive maintenance was introduced as a concept to continually improve to prevent failures.

Nothwithstanding the unclear genesis of preventive maintenance, the widespread use grew from the sixties onwards. Japanese Toyota subsidiary Nippondenso was the first factory to apply plant wide preventive maintenance in 1960.

4

Original quote attributed to Trevor Kletz, The Chemical Engineer No. 569 (1994). Nowadays commonly used in chemical industry, aerospace and other high risk industries.

The quote has met with criticism as well, as it is often (mis)used to compare the prevention expenses directly with the cost occurring only if and when a specific uncertain risk actually materializes (Helsloot, I. Veiligheid als

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maintenance does not measure the actual condition or occurrence of a failure but rather applies maintenance based on calendar (interval) or age (age based). It is believed that these preventive maintenance actions save costs due to the fact that maintenance activities (and thus downtime) can be planned and catastrophic failure is prevented.

Preventive maintenance has seen a large increase in application since it was first conceived. The exact extent to which preventive maintenance is applied over corrective maintenance varies per industry. For example, (Koo & Van Hoy, 2000) state that in real estate, 30% to 50% of maintenance spending relate to preventive maintenance. A (rather simplistic) rule that is often cited in general industry is the six to one rule, stating that only one in six maintenance actions should be corrective (Call, 2007). Quite veraciously, (Narayan, 2004) indicates that the actual (ideal) ratio depends on the nature of the industry. In processes which have buffer stock or redundant capacity, corrective maintenance may be appropriate (often called a run-to-failure regime). In tightly coupled processes, preventive

maintenance is preferable. Indeed, a survey of literature shows varying ratios. (Jonsson, 1997), states that corrective maintenance should comprise no more than 30 to 40% of maintenance actions, although his study indicates true numbers to be higher. (Ben-Daya et al., 2009) and (Kelly, 2006a) agree that at most 20% of maintenance actions may be corrective.

Besides preventive maintenance as counterpart of corrective maintenance, predictive maintenance is a type of planned maintenance that is witnessing a strong increase in application. It combines the mentioned benefits of preventive maintenance whilst reducing the number of maintenance actions to a minimum. Predictive maintenance takes into account the state of the equipment. The most common type of predictive maintenance is condition based maintenance. By measuring the state of an object one is able to better predict the remaining lifetime and therefore better able to time maintenance. All of the above categories assume perfect maintenance, i.e. after maintenance the object is restored to its as-built condition. Opposed to this, imperfect maintenance is distinguished. This type of

maintenance levers the state of the object from an unacceptable (failure state) to an acceptable state. Both planned and unplanned maintenance can be either perfect or imperfect.

The above typology is not exhaustive. Many subdivisions exist in addition to the abovementioned. Many niche types of maintenance or maintenance types that combine preventive and predictive maintenance exist. The typology of maintenance discussed here (Figure 6) does encompass all subtypes of maintenance (Veldman et al., 2011). Therefore a more detailed discussion of the typology of maintenance is not deemed relevant.

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Note how the matter of planned versus unplanned maintenance implicitly touches upon the question raised earlier what optimal maintenance is. Planned maintenance (preventive) is generally believed to be economic since it offers yield such as less catastrophic failure, unplanned downtime etc. On the other hand one cannot gainfully apply unlimited preventive maintenance beyond a certain point (of optimal maintenance). Determining optimal maintenance (which concerns more than just the balance of planned versus unplanned maintenance) requires insight in all costs and benefits of maintenance. Furthermore, although apparently acknowledged that (preventive) maintenance prevents costly breakdowns, it was apparent from paragraph 1.1 that maintenance is especially prone to be applied too stingily rather than too liberally.

2.2

Maintenance in the production function

As already apparent from the definitions given in paragraph 2.1 we need to view maintenance in coherence with its object, the production system it serves. This paragraph will elaborate on this coherence. Whilst doing so, some definitions will be explained which will prove relevant, later on in chapter Error! Reference source not found., when taking stock of the costs and benefits of maintenance.

2.2.1 Performance of production system: Effectiveness, efficiency,

productivity

A performance measure for maintenance calls for a definition of what performance constitutes. True to the definitions cited earlier, maintenance is applied in order for a production system, whether it is a bridge, plane or a production line, to be able to fulfill its primary function: to produce. So, a

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Although it was stressed that maintenance is more than a cost function, one must also acknowledge that maintenance in itself is not an intrinsic activity. Maintenance is always applied in order to serve a productive system. Maintenance can only add value through its contribution to allow the production system to operate properly, by offering the necessary conditions. Maintenance thus adds value in an indirect way. Opposed to the production system that directly adds value.

For example, the output of maintenance could be a well lubricated bearing. This has no direct value. It adds value because it reduces energy consumption and wear in a production system, and ultimately allows the production to fulfill its value adding function.

All in all, it is necessary to review the role of maintenance not in isolation, but in conjunction with the production system.

The primary function of a production system is a transformation. Temporary elements enter the system and leave the systems transformed. For example people in a plane are temporary elements that are transported. Flat pieces of steel are transformed in shape after leaving a die press.

An asset, piece of equipment or production system at large performs a transformation process on the temporary elements. This transformation directly adds value. The asset or equipment is the

permanent element of such a production system, subject to maintenance actions (Figure 8).

Maintenance actions may include inspections, replacement, repair, cleaning etc. Before elaborating on the maintenance function, some remarks about the primary process of a production system (NB as opposed to the maintenance system).

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The productivity of a production system is historically one of the most relevant metrics. It is directly linked to the fulfillment of the primary function. Maintenance is associated with the productivity of a production system and therefore this concept is clarified here.

The term productivity is often loosely defined and used freely. Improving productivity, efficiency or effectiveness are concepts which are often used interchangeably. In reality the three terms correlate. Production systems intend to have an output which is a yield. This result should adhere to a standard. In order to produce the intended result, a certain input is needed. These sacrifices can be time, money, energy or for example raw material. A certain amount of sacrifices is the input.

Productivity is a ratio of the output (yield) and the input (sacrifices).

To illustrate, the example of a water boiler is given. It has the function to boil 1000 liter/hour using 30 kg/hour of pit coal. The productivity is thus 1000/30 = 33 liters of boiled water per kg of coal.

The concept of effectiveness is the ratio of the realized result over the intended result. When the boiler, due to clogging on the inner wall for example, only produces 900 liters of boiled water per hour, its effectiveness is 90%. Note that effectiveness can be larger than unity when the boiler produces more than what is necessary and intended.

The efficiency is the ratio of the expected sacrifices over the sacrifices actually made. When coal consumption turns out to be 40 kg/hour instead of 30 kg/hour the boiler is said to have an efficiency of 30/40 = 75%

Since productivity was defined to be the ratio of the result over the sacrifices it can be deduced that productivity = effectiveness x efficiency.

In our example the productivity has decreased to 900 liters/40 kg = 22.5 liters of boiled water per kg of coal. This is 22.5/33 = 68% of nominal productivity. This corresponds with an effectiveness of 90% multiplied by an efficiency of 75%.

The ratio of the realized productivity and the nominal productivity was seen to be 68%. This ratio is formally dubbed performance. In our case, the boiler clearly underperforms.

It was mentioned that the concepts of effectiveness and efficiency are often loosely used. In this respect, special caution is called for concerning performance. In maintenance literature, the term productivity (of the production system) is used in a roughly similar fashion as our example. It is concerned with the primary production process’ in- and outputs and can be readily quantified. Especially in more recent literature on maintenance, performance of a production system is used holistically to represent achievements in terms of productivity, job satisfaction, customer satisfaction safety, ethics, shine, environmental care, legal compliance etc.(Parida & Chattopadhyay, 2007). Almost none of the literature reviewed for this paper has given a (strict) definition of what constitutes performance, an exception being (Mather, 2004) who states performance to be “the way assets do what we require of them”. Even terms such as effectiveness, efficiency or productivity are seldom defined, or very loosely and informally (e.g. effectiveness is doing the right thing, and efficiency is doing things right). Exceptions are (Kodali et al., 2009) who defines the concepts of effectiveness, efficiency and productivity. The former two are defined by (Crespo Marquez et al., 2009) as well, as do (Parida & Kumar, 2008). It is surprising to see how few papers on maintenance actually define these concepts, whilst they do proclaim these concepts to be affected by maintenance (see chapter Error! Reference source not found.).

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Relieving the incriminating nature of the omission somewhat is the fact that the definitions found,

including the informal ones, are in line with those formally defined here (Figure 9). Authors

presumably assume a sanctioned discourse regarding the definitions.

Figure 9 Coherence between efficiency, effectiveness and productivity op a production system

The concepts of efficiency and effectiveness are linked together. The concepts of effectiveness and efficiency will be mentioned in the remainder of this text. A clear understanding of their exact

meaning is important therefore. This is especially invaluable in order to distinguish between efficiency of a production system, or of a maintenance system.

2.2.2 Performance of maintenance system: effectiveness and

maintenance

As explicitly expressed in the various definitions, the goal of a maintenance system is to ensure a production system fulfills its function (Figure 10). Combining this with the concepts of effectiveness and efficiency, we can state that the goal of a maintenance system is to ensure a production system realizes its nominal productivity. Maintenance can influence both the effectiveness and the efficiency of a production system, thus influencing productivity.

This implicitly defines the concepts of efficiency and effectiveness of maintenance that make up maintenance performance.

Effective maintenance is concerned with successfully maintaining or restoring the equipment to fulfill its function. In other words, it is concerned with offering the necessary conditions for the primary production function to convert input into output. In terms of our example boiler effective maintenance successfully restores/retains both effectiveness and efficiency of the boiler, so as to produce 1000 liters of boiled water again, using only 30 kg/hours of coal again.

Productivity primary system = f (effectiveness of maintenance)

For completeness it is noted that the productivity of a production system does not depend solely on maintenance

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Efficient maintenance is concerned with the sacrifices made to execute the maintenance (e.g. man hours, spare parts, resources). When, for example, maintenance is badly planned and workers experience a lot of idle time this means maintenance is not efficient.

As will be seen in the literature, maintenance is believed to have profound influence on efficiency and effectiveness of production systems. In other words the productivity of the production system is influenced.

Moreover since facets such as safety and the environment are influenced, it is said that maintenance influences the performance of a business (note that performance is used corresponding to the wide-ranging definition as mentioned above (Parida & Chattopadhyay, 2007)).

The efficiency and effectiveness of the production system is influenced by maintenance because it makes equipment run better, and maintenance decreases the downtime of equipment. The concept of reliability and availability are therefore important in this respect. Increasing reliability or availability will prove to be mentioned often, as being one of the merits that maintenance brings (chapter Error! Reference source not found.). Therefore it is relevant to further define these concepts as well.

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2.2.3 Reliability and availability of production system

It was stated that maintenance adds value by influencing the performance of the primary production process. In chapter Error! Reference source not found., a record is made of all ways in which maintenance influences the primary production function. In this respect, some specific definitions are given to aid understanding.

Reliability is the probability that a production system or single piece of equipment can fulfill its function over a period of time. The mean time between failures (MTBF) is therefore a direct indicator for reliability. The availability of a piece of equipment is the average fraction of time that an

equipment or piece of machinery can fulfill its function. The mean time between failures and the mean time to repair (MTTR) together determine the availability. The mean time to repair includes all time to restore a failed system to reclaim its functionality. A planned preventive downtime is, from a

functional view, seen as a failure. After all, whether planned or not, the system is unable to fulfill its function:

Availability = MTBF / (MTTR + MTBF)

In other words, when repair time becomes nil, a very unreliable piece of equipment can still have a high availability. Imagine an automatic electric fuse that ‘’trips’’ very often but can be restored (reset) with the touch of a button. Vice versa, a system with a high reliability but very long repair time results in a subsequently low availability.

The time that a system cannot fulfill its function is noted as downtime, of which uptime is the opposite.

Availability = Uptime/ (Uptime + Downtime)

The above formulas thus do not disclose information on the planned or unplanned nature of the downtime. Note however that the above formulas are often adapted to cater for a split between planned and unplanned downtime. In that view, only unplanned (forced) failures are seen as failures; When maintenance is planned on a fixed interval (e.g. an annual plant stop at a chemical plant), the reliability is only examined (defined) over the period in between. That way, only unexpected failures influence the reliability metric.

Compare:

• A piece of equipment that receives preventive maintenance twice a year to completely exclude failures, and each maintenance action lasts a day

• A piece of equipment with no possibility for preventive (predictive) maintenance, that fails on average twice a year, incurring a day of corrective maintenance each time.

When strictly applying the definitions both pieces of equipment have similar reliability, after all both have a half year MTBF, and are expected to ‘fail’ twice over the cause of a year. The average

availability is equal as well. In maintenance practice, the first option is more preferable since it is more predictable (i.e. the skedacity of MTBF is lower). Given the importance of predictability, reliability is often measured within the planned maintenance interval. When taking this viewpoint the first piece of equipment is deemed more reliable.

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Predictability is favorable because work can be completed faster and cheaper since workers and parts can be prepared and planned. Furthermore unexpected failures often cause collateral downtime up- and downstream of the failing equipment. Or result in a lot of work in progress to be scrapped. Availability and reliability are associated with statistics and can be mathematically modeled. This paper will make an inventory of all facets that maintenance is believed to influence. Since (improving) availability and reliability improvement are often mentioned as merits of applying maintenance the concepts were explained here. Although this paper does not aim to give a mathematical analysis the following can be readily seen from the definition and is worth noting:

Availability is a measure for how much fraction of time a system can produce. In an uncoupled process availability is of prime interest. Whether the system is down for an hour once, or down for 15 minutes four times, results in the same production time (uptime or availability). Leaving startup effects and assuming four small repairs cost as much as one big one, both situations are equivalent. In a highly coupled process (line production, Just-in-Time, Just-in-Sequence), the downtime of one machine influences the downtime of other machines and vice versa. In these cases not just the availability counts, but the reliability and especially predictability as well. A higher reliability and predictability is favorable.

2.3

The size of maintenance

Whether maintenance can be viewed upon as cost function or as added value, fact is that

maintenance costs are a large portion of the operational cost in industry. Numbers differ per industry, with high CAPEX5 _{industry such as the process industry having more expenses than for example retail}

industry. Industry wide estimates indicate that between 10 and 70 percent of production costs are the costs of maintenance (Maggard & Rhyne, 1992, Bevilacqua & Braglia, 2000). In line with this range of estimates, (Al Turki, 2011) claims that in today’s manufacturing industry maintenance costs take up 30 percent of all running costs. More conservative (perhaps outdated) studies report that in

manufacturing industry around 25 percent of all operational costs are maintenance related (Komonen, 2002. Cross, 1988).

The mining, petrochemical and electrical power industries have especially been identified as industries where maintenance costs outnumber all other operational costs (Eti et al., 2006. De Groote, 1995. Raouf, 1993). Also in aviation, maintenance costs are identified to be 30 percent of all costs (Linser, 2005) facing airline operators.

The vast amount of money concerned with maintenance emphasizes the importance of improvement of the efficiency and effectiveness of maintenance. Thus rendering the need for a performance indicator. This is even more apparent when considering alarming reports such as (Wiremann, 1998) who states that as much as one third of maintenance budget are spent in a wasteful or unnecessary manner.

Given the vast turnover in industry, the abovementioned percentages add up to astonishing absolute values. When accumulated, maintenance budgets in Europe are estimated to amount to 1500 billion euro per year (Parida & Kumar, 2006). A study on the Swedish industry revealed that maintenance budget accumulated to represent over six percent of total industry turnover, or 20 billion euro per

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