Structuring AHP-based maintenance policy selection

Goossens, A.J.M.; Basten, R.J.I.; Hummel, J.M.; vd Wegen, L.L.M.

Published: 01/01/2015

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Structuring AHP-based maintenance policy selection

A.J.M. Goossens R.J.I. Basten J.M. Hummel

L.L.M. van der Wegen

Beta Working Paper series 488

BETA publicatie WP 488 (working paper)

ISBN ISSN NUR

804

Eindhoven September 2015

Structuring AHP-based maintenance policy selection

A.J.M. Goossens · R.J.I. Basten · J.M.Hummel · L.L.M. van der Wegen

Abstract We aim to structure the maintenance policy selection process for ships,using the Analytic Hierarchy Process (AHP). Maintenance is an important contributorto reach the intended life-time of capital technical assets, and it is gaining increasinginterest and relevance. A maintenance policy is a policy that dictates which parametertriggers a maintenance action and it appears that selecting the right maintenance policyis a difficult group decision. To investigate maintenance policy selection (MPS), weuse an eight stage method to structure the multiple criteria decision making process,and build on previous research to propose a refined decision hierarchy, aiming fora structured abstraction of MPS to reveal the core of the MPS problem. After apreliminary MPS session, this decision hierarchy is applied at a multi-company MPSsession, where a group of companies from the same maintenance chain is present.We conclude that the chosen methodology, using our previous results as a starting

A.J.M. GoossensUniversity of Twente, Faculty of Engineering Technology, P.O. Box 217, 7500 AE, Enschede, The Nether-landsTel.: +31 6 25075772E-mail: a.j.m.goossens@utwente.nl

R.J.I. BastenEindhoven University of Technology, School of Industrial Engineering, P.O. Box 513, 5600 MB, Eindhoven,The NetherlandsE-mail: r.j.i.basten@tue.nl

J.M. HummelUniversity of Twente, Faculty of Behavioural, Management and Social sciences, P.O. Box 217, 7500 AE,Enschede, The NetherlandsE-mail: j.m.hummel@utwente.nl

L.L.M. van der WegenUniversity of Twente, Faculty of Behavioural, Management and Social sciences, P.O. Box 217, 7500 AE,Enschede, The NetherlandsE-mail: l.l.m.vanderwegen@utwente.nl

2 A.J.M. Goossens et al.

point, greatly improves the workability of the decision hierarchy. Also, it turns out thatdiscussing the exact meanings of the criteria plays a crucial role in the group decisionprocess.

Keywords Maintenance · maintenance policy selection · analytic hierarchy process ·group decision making

1 Introduction

How to maintain technical capital assets is a question gaining increasing attentionand relevance (Zio 2009), as maintenance is an important contributor to reach theintended life-time of these expensive assets. By technical capital assets we meancapital intensive, technologically advanced systems that have a designed life-time ofat least 25 years, such as trains, ships and aeroplanes. Maintenance can be definedas all activities which aim to keep a system in or restore it to the condition deemednecessary for it to function as intended (Duffuaa et al 1999; Pintelon and Parodi-Herz2008).

Based on Pintelon and Parodi-Herz (2008) and Tinga (2010), we define a mainte-nance policy as a policy that dictates which parameter triggers a maintenance action,a parameter can, for example, be elapsed time or amount of use. Selecting the rightmaintenance policy is an important group decision in maintenance decision making.In practice, current selection methods do not always fit companies well, and current,mostly quantitative, maintenance optimization and decision models have low appli-cability. Hence, the need for tailored maintenance models and concepts is raised inthe literature (Waeyenbergh and Pintelon 2002; Zio 2009). Several authors argue thatpractical studies are under-represented, strongly encouraging efforts to close this gapbetween theory and practice (Nicolai and Dekker 2008; Horenbeek et al 2011; Zio2009).

We look at maintenance policy selection (MPS) through the use of the AnalyticHierarchy Process (AHP), a multiple criteria decision making (MCDM) method inwhich the decision problem is structured in a hierarchic way, developed by ThomasSaaty in the 1970s (Saaty 1980). The use of the AHP for (group) decision making hasbeen growing ever since (Ossadnik et al 2015), and its use for maintenance decisionmaking has been recognized (Triantaphyllou et al 1997; Labib et al 1998; Ramadhanet al 1999).

To research maintenance policy selection for ships in a relevant way, we needto draw from two research paradigms, where a research paradigm can be defined asthe combination of research questions asked, the research methodologies allowedto answer them and the nature of the pursued research products (Van Aken 2004).These two paradigms are, on the one hand, organisational research, which will help tounderstand MPS in organisations, and, on the other hand, design research, which willenable the development of an MPS method.

A full integration of these different paradigms is not possible. However, severalauthors propose a combination of and collaboration between specifically these twoparadigms, in which they argue for a design approach to organisational research(Romme 2003; Van Aken 2004). The aim of this approach is to create knowledge

Structuring AHP-based maintenance policy selection 3

that is both actionable and open to validation, and, by that, is reducing the relevancegap between theory and practice. This approach relies on developing and testingsolutions in practice as well as grounding the solutions in empirical findings. Hence,this approach cannot deliver conclusive proof (in the formal scientific sense) for thesolutions found; however, it generates increasingly supporting evidence by iterationand refinement, which is tested in context, for an increasing confidence in the solutionsfound.

To apply the proposed design approach to organisational research, and to accu-mulate the supporting evidence, both Romme (2003) and Van Aken (2004) suggestthe multiple case method. This method comprises an iterative cycle of cases in closecollaboration with people in the field. After the initial case is chosen, each new case:

– is refined by the findings of the previous research;– tests the knowledge gained during the previous research and the implemented

refinements;– provides new knowledge and refinements to be tested in subsequent cases; and– thus contributes to the supporting evidence for, and increases the confidence in the

solution to the research problem under investigation.

Applying this approach, we take the following three steps.

1. Investigate methodologies to refine the decision hierarchy and to structure theMCDM process.

2. Methodologically refine the decision hierarchy, using the results and feedbackfrom practice.

3. Use this renewed hierarchy at a final, multi-company MPS session with participantsfrom various companies within the same maintenance chain (from supplier to user).

Following these steps, we build on previous research, in which we have investigatedthe most important criteria and considerations for ship maintenance policy selection(MPS), while generalizing our AHP-based MPS approach from naval ships towardsships in general (Goossens and Basten 2015a,b). This research shows that crew safetyis the most important criterion for ship MPS, followed by reliability and availability.Furthermore, we found that softer, qualitative criteria play an important role andshould be included in ship MPS (see Appendix A for an overview of these results).

In this paper, we shift the focus back on naval ships. To keep these ships operationaland up to date throughout their life-time, maintenance plays a crucial role. In theNetherlands, the owner, operator and foremost maintainer of these ships is the RoyalNetherlands Navy (RNLN). At the time of writing, detailed information on 27 of theRNLN’s fleet of ocean going vessels is publicly available. With a designed life-timeof 25 years, the average age of the vessels is 17 years, of which the oldest vesselwent into service in 1985 and the youngest in 2015 (Ministry of Defence 2013; RoyalNetherlands Navy 2013).

The current paper builds on this multiple case cycle and focusses on refinementby means of a structured abstraction of the AHP-based MPS approach in order toreveal the core of ship MPS. Insight in the core of ship MPS provides the means toexpand the investigation by shaping our findings into a refined decision hierarchy andby testing this new decision hierarchy in a final, multi-company group session, as

4 A.J.M. Goossens et al.

opposed to the single company sessions in the previous research. Hence, this papercontributes in two ways.

1. We methodologically refine the decision hierarchy. We do so based not only on theresults and outcomes of the six sessions in general ship practice, but also on thefeedback of the practitioners. This adds to the literature, as such a methodologicalapproach to structuring decision hierarchies has not been encountered in theliterature.

2. We organize a multi-company group AHP session with participants from fourdifferent companies within the same maintenance chain, where in previous researchwe used a single hierarchy of criteria at multiple companies, one at a time.

This paper is structured according to the steps explained above. In Section 2, weexplore various methods to renew the decision hierarchy and explain the implemen-tation thereof in the research. Next, the decision hierarchy is reviewed after whichwe construct a renewed decision hierarchy in Section 3. The set-up and results of themulti-company MPS session are presented in Section 4. We then draw conclusionsand propose recommendations for further research in Section 5.

2 Structuring MCDM

To methodologically refine the decision hierarchy, choosing the most relevant criteriawith which to make a decision hierarchy, a method or structure is needed. Althoughit seems that organizing and structuring criteria and objectives, and subsequentlydesigning a decision hierarchy, is more an art than a science (Saaty and Peniwati2013; Hammond and Keeney 1999), several structured approaches have already beenformalized in the literature. We discuss three of such approaches that we could use inour research.

First, Saaty and Peniwati (2013, p. 71) state that there is one basic principle tofollow for structuring an AHP decision hierarchy. It is to see if one can answer thefollowing question: “can I compare the elements on a lower level using some or allof the elements on the next higher level as criteria or attributes of the lower levelelements?”

According to Saaty and Peniwati (2013), the elements (being criteria, sub-criteriaand alternatives) should be clustered into homogeneous groups of at least three, wherethe AHP often uses clusters of 7 ± 2 elements. The hierarchy should include as muchdetail as needed to understand the decision problem, as unimportant criteria will beeliminated by the judgement process. This means that seemingly unimportant criteriathat are nonetheless needed to understand the problem should be included. The onlyrestriction is that the elements in a cluster must be related to the element beneathwhich they are clustered, because it is this element that is used to assess the impact ofthe cluster beneath it.

Second, a method called value-focussed thinking promotes that values, whichdefine all that one cares about in a specific decision situation, should be the primaryfocus of decision making. Value-focussed thinking aims at identifying the underlyingvalue system for a decision situation and it involves clearly defining these values in

Structuring AHP-based maintenance policy selection 5

terms of objectives that have influence on the decision (Keeney 1994). It provides fivesteps for systematically identifying and organizing these objectives (Hammond andKeeney 1999).

1. Write down all the concerns, considerations, and criteria you want to addressthrough your decision.

2. Convert your general concerns into succinct objectives and organize them.3. Separate ends from means to establish your fundamental objectives.4. Clarify what you mean by each objective.5. Test your objectives to see if they capture your interests.

Third, the most comprehensive and complete method that we are aware of, pro-poses a methodology not only for designing and structuring criteria trees (i.e., decisionhierarchies), but also for the entire MCDM process (Brugha 2004). It aims to replacethe several structuring ways into a single way of structuring. The method presentsMCDM as an eight-stage process of shaping information that satisfies eight corre-sponding criteria: the information should be accessible, differentiable, abstractable,understandable, verifiable, measurable, refinable and usable. For each criterion acorresponding guideline is presented to clarify the stage. These are as follows.

1. Accessible: access the basic information of the decision problem. To access theright information, the decision should concern a real problem, involve the actualdecision makers, and the information should be accessed at a time when the intentto solve the problem is real (i.e., the problem should be current).

2. Differentiable: differentiate the criteria from one another to form a criteria tree. Tocheck differentiability, the alternatives should be comparable with each other, theformed clusters should be separable from each other, and the alternatives shouldhave measurable aspects.

3. Abstractable: ensure robustness and usability under changing circumstances. Thismeans that the criteria incorporated in the decision tree should be based on a setof empirical criteria that can be used to identify and abstract the actual and realcriteria for the decision problem at hand and its underlying processes.

4. Understandable: construct a criteria tree, having several levels with no more thanfour sub-criteria for any criterion. By understanding the underlying processes,a meaningful and appropriate criteria tree can be formed, in which the criteriawordings clearly reflect what the criteria mean.

5. Verifiable: verify the criteria tree with decision makers. Start by verifying thenames and phrasing of the criteria, extend this to the criteria tree as a whole, andend by revealing the underlying processes back to the decision makers.

6. Measurable: facilitate the measurement of the preferences. Start by scoring thealternatives, where the alternatives’ scores should have meaning at every levelof the criteria tree, then use an appropriate method to produce criteria weights.Together, the scores and weights develop the decision makers’ preference scores.

7. Refinable: facilitate interactive refinement of scores and weights. For the decisionmakers to ‘own’ the process, allow modifiable scores and weights. Furthermore, itshould be possible to exclude truly unwanted alternatives.

8. Usable: check the usability of the developed MCDM system. The most obviousaspect is that the system provides preferences. Furthermore, to make a new MCDM

6 A.J.M. Goossens et al.

system usable it should relate to the generics of the decision problem at hand.Lastly, it should be made usable to distribute decisions throughout the company.

The structuring method proposed by Brugha (2004) provides the most completemethod to structure an MCDM process, it is highly workable and offers an overarchingset of eight criteria with eight accompanying stages. Therefore, we use this methodto structure our efforts. How we implement this structure is presented in Table 1,in which the eight stages, along with their corresponding criteria are linked to ourresearch. Stages 1 – 4 consider the renewal of the decision hierarchy and are discussedin Section 3. Stages 5 – 8 are covered in the two MPS sessions that we have conductedand are discussed in Section 4.

Table 1 The MCDM structuring stages and the implementation thereof.

Stage Criteria Implementation

1 Accessible Use the general ship hierarchy from previous research as startingpoint.

2 Differentiable Use the participants’ evaluations of the previous hierarchy.3 Abstractable Use the results of the six general ship sessions.4 Understandable Restructure and reformulate the hierarchy.5 Verifiable Organize a preliminary session, using the renewed hierarchy.6 Measurable Elicit the participants’ preferences during the actual session using

the AHP.7 Refinable Allow the participants to discuss and refine their judgements

before the final results are displayed.8 Usable Present and explain the final preferences to the group of partici-

pants.

3 The decision hierarchy

The starting point, and Stage 1 of the structuring method, is the general ship decisionhierarchy as used by Goossens and Basten (2015b). To restructure the hierarchy wetake into account the following (see also Appendix A):

– the average relative priorities of the lowest level criteria;– criteria with similar, discriminant policy scores, which might be clustered;– the inconsistency ratios per session for each comparison matrix, which could

indicate that participants do not understand these comparisons; and– comparisons matrices where participants indicated equal importance for every

comparison (i.e., give only judgement scores of 1), which could also indicate thatparticipants do not understand the comparisons or find them irrelevant.

Structuring AHP-based maintenance policy selection 7

3.1 Restructuring the decision hierarchy

Our aim is to construct a decision hierarchy that is as concise and balanced as webelieve possible, based on the feedback and results from practice. For Stages 2 and 3we look at the results of the previous sessions, from which several facts stand out:

– crew safety, reliability and availability are the three most important criteria;– relative to the other criteria, cost minimization is only of mediocre importance; and– the three criteria that we previously clustered under fit to relations are of relatively

little importance (the first, second and fifth most unimportant criteria).

Regarding inconsistent comparisons and comparisons receiving equal importances(i.e., judgements scores of 1), the following facts are noteworthy:

– fit to relations and its three sub-criteria obtain the highest amount of only 1s (twoand six respectively); and

– some inconsistencies did occur during the sessions; however, looking at all thesessions, there is no comparison that is uniformly inconsistent, the inconsistentcomparisons seem to be spread out evenly.

This gives reason to consider availability, safety and reliability as the top-levelcriteria, and to eliminate the cluster fit to relations. Besides these three, it appears thatthe following three discriminant clusters can be formed from criteria favouring thesame maintenance policy.

1. A costs cluster, favouring condition-based maintenance, combining:– cost minimization; and– spare parts cost.

2. A fit to system cluster, favouring time/use-based maintenance, combining:– commonality presence;– redundancy presence;– consequences of poor maintenance;– spare parts availability;– mission profile; and– criticality of parts.

3. A fit to company operations cluster, also favouring time/use-based maintenance,combining:

– crew educational level;– crew size;– experience with maintenance;– compliance with existing policies; and– planability.

The criterion criticality of parts scores marginally higher on condition-basedmaintenance than on time/use-based maintenance, yet seems to belong to the fit tosystem cluster. Because the difference of favour is so small and non-discriminating,we feel it would indeed fit best under the fit to system cluster.

The criterion drive for innovation needs special attention, since it does not fit inone of the clusters. After careful consideration, we feel that innovation is not a true

8 A.J.M. Goossens et al.

driver for maintenance, but in itself always is driven by either an innovative system, aninnovative company or innovative operations. Hence, we feel it is justified to excludedrive for innovation as separate criterion.

To summarize, these efforts result in three main criteria and three clusters of sub-criteria. These three clusters of sub-criteria seem to be relevant considerations for allthree main criteria. This notion leads to the highly balanced structure for the renewedhierarchy, as presented in Table 2: three main criteria with three considerations percriterion and three alternatives.

Table 2 The conceptual 3 × 3 hierarchic structure.

Criteria Considerations Alternatives

Availability Fit to system Failure-based maintenanceReliability Fit to company operations Time/use-based maintenanceSafety Costs Condition-based maintenance

3.2 The final decision hierarchy

For Stage 4 of the structuring method, we further develop this 3 × 3 structure, since itprovides both conciseness and balance. Compared to the general ship hierarchy, thisstructure reduces the total number of criteria and sub-criteria in the hierarchy from 29to 12. Furthermore, it also reduces the total number of required pairwise comparisonsfrom 98 to 39.

Continuing Stage 4, we formulate the criteria and considerations such that thehierarchy can operate as a stand-alone decision hierarchy. The final decision hierarchyobtained in this way is presented below and shown in Figure 1.

The criteria are as follows, their definitions are drawn from relevant standardizationnorms:

– availability realisation: to realise the desired availability, where availability is theability to be in a state to perform as and when required, under given conditions,assuming that necessary external resources are provided (definition based onEuropean Committee for Standardization (2010));

– reliability realisation: to realise the desired reliability, where reliability is theability to perform a required function under given conditions for a given timeinterval (definition based on European Committee for Standardization (2010));and

– safety assurance: to assure the desired level of safety for everyone involved,where safety considers the ability of a machine to perform its intended function(s)during its life cycle where risk of physical injury or damage to health has been ade-quately reduced (definition based on International Organisation for Standardization(2010)).

The considerations we define as follows:

Structuring AHP-based maintenance policy selection 9

– what best suits the system: from a system point of view, think about: critical-ity, commonality, redundancy, use profile, spare parts and maintenance inducedfailures;

– where the expertise lies: from a company point of view, think about: companyexperience, educational levels, personnel and planning; and

– what the cheapest option is: from a financial point of view, think about: mainte-nance costs, maintenance budgets and austerity measures.

The maintenance policies are the same as in previous research:

– failure-based maintenance: corrective maintenance, where a failure triggers themaintenance;

– time/use-based maintenance: planable maintenance, where either the elapsed timeor the amount of use triggers the maintenance; and

– condition-based maintenance: preventive maintenance, where a measured condi-tion triggers the maintenance.

Best maintenance policy

Availability realisation

Reliability realisation

Safety assurance

Failure-basedmaintenance

Time/use-based maintenance

Condition-based maintenance

What best suits the system

Where the expertise lies

What the cheapest option is

What best suits the system

Where the expertise lies

What the cheapest option is

What best suits the system

Where the expertise lies

What the cheapest option is

Fig. 1 The decision hierarchy.

4 The MPS session

The MPS sessions cover Stages 5 – 8 of the structuring method. Stage 5, the verifica-tion, is executed by performing a preliminary session. Stages 6 – 8 are incorporated in

10 A.J.M. Goossens et al.

the structure of the multi-company session. To incorporate the judgement refinementof Stage 7, the session structure is:

1. An introductory presentation on planning of the session and the nature of ourresearch.

2. A fictitious example case to get the participants acquainted with the AHP.3. The selection and the execution of the company case (Stage 6):

(a) selection of the group case;(b) individual judgements by the participants where they manually fill out the

pairwise comparisons;(c) discussing the individual judgements in the group, focussing on where the

participants disagree most, while allowing refinement (Stage 7); and(d) aggregation of the individual judgements into the group preference.

4. Presentation and discussion of the final results including a sensitivity analysis forthe three main criteria (Stage 8).

5. An evaluation of the session by means of a questionnaire, in order to check Stage8, focussing on the session itself, the hierarchy of criteria and the final decision(see Appendix B).

When using the AHP in a group setting, the AHP prescribes that the geometricmean

ag = n√a1 · a2 · · · an =

(n∏

i=1

ai

)1/n

(1)

must be used to synthesize individual comparisons (Saaty 2008), where ai is the scoreor weight per pairwise comparison, given by participant i, with i ∈ {1, . . . , n} andn being the number of participants present at the session. The geometric mean, notthe common arithmetic mean, is proven to be the correct way to aggregate individualjudgements, due to the ratio scale used for the pairwise comparisons are rated on (seealso Saaty 2013, ch. 7).

The geometric standard deviation can then be used to investigate where the partici-pants agree and disagree most in the pairwise comparisons:

σg = exp

√∑n

i=1(ln ai

ag )

n

(2)

where ag is the geometric mean of the scores or weights ai per pairwise comparison,given by participant i, with i ∈ {1, . . . , n} and n being the number of participantspresent at the session.

To draw the relative priorities from the aggregated comparison matrices the socalled geometric means approach is used to approximate the principal eigenvector(Hummel et al 2014; Williams and Crawford 1980). The software that we use duringthe session is a regular spreadsheet program (LibreOffice Calc).

Structuring AHP-based maintenance policy selection 11

4.1 Preliminary session

To validate the refined decision hierarchy, a preliminary session is organized at theDutch pilot service, the Loodswezen. The case concerns their three 81.2 m long pilotvessels that operate as pilot stations at sea, from which pilots are brought to and fromships or shore. This is the second session held at the Dutch pilot service and oneparticipant had also been present during the previous session (on which we report in(Goossens and Basten 2015b)). The session was attended by five participants withvarious roles throughout the company.

In their evaluations of the hierarchy, all five participants are unanimous. They statethat the hierarchy is clear and understandable and matches the sector. The divisionsinto clusters are clear and logical, one participant explicitly praises the definitions.In contrast to the evaluation on which we reported in previous research, none of theparticipants indicate lacking or excludable criteria. One participant states that morecriteria would make the hierarchy unclear, and another participant states that thishierarchy is better than the lengthy previous one.

For the final policy preferences, as shown in Table 3, the participants feel thatthe detailed comparisons quantify their gut feelings. They do not see time/use-basedmaintenance as the ‘winner’, but recognise the final policy preferences as the rightmix and quantification of maintenance policies for the pilot vessels, towards whichthe company is already working.

Based on these promising evaluations, we keep the hierarchy as it is for the finalsession.

Table 3 Final preferences of alternative maintenance policies at the Loodswezen session.

Failure-based Time/use-based Condition-based

Pilot vessel 0.133 0.447 0.421

4.2 Set-up of the final session

For the final session, we go back to the first ship type that we have investigated: navalships. We have already encountered the maintenance chain of naval ships. However,instead of organizing a session at each individual company as we did in previousresearch (Goossens and Basten 2015a), we organize one multi-company session. Ofthese companies, two participants per company attend the session. An overview of thecompany, the roles and the participants is given in Table 4.

During the case selection within the context of the maintenance chain of theparticipants, debate arose on the most relevant level in the system. The discussionconsidered the complete Thales radar system or a line replaceable unit (LRU) of theradar system, both as installed on ships of the Royal Netherlands Navy built by DamenSchelde Naval Shipbuilding. To correspond to the high level in the system for which

12 A.J.M. Goossens et al.

our AHP-based MPS approach seems to work best, the radar system itself is chosenas case.

4.3 Results of the final session

After the participants individually filled out the pairwise comparisons, their judgementsare compared and discussed within the group. This discussion proved to be extensive,with the participants giving and defending their views, each from their own area ofexpertise. As revealed in the next sections, this discussion had great influence on thesession and the evaluations of the session.

Although the debate was extensive, no refinements have been made by the partici-pants. The final judgements are remarkably consistent; the highest consistency ratio is4%. This results in the final policy preferences that are presented in Table 5. The resultsshow that failure-based maintenance is the least preferred policy, while time/use-basedmaintenance and condition-based maintenance obtain a similar preference.

Table 4 Final session companies, roles and participants.

Role Company Participants

OEM Thales Netherlands 2Shipbuilder Damen Schelde Naval Shipbuilding 2Owner/regulator Ministry of Defence – Defence Materiel Organisation 2Owner/maintainer Royal Netherlands Navy – Directorate of Materiel Support 2

Table 5 Final preferences of alternative maintenance policies.

Failure-based Time/use-based Condition-based

Radar system 0.220 0.383 0.398

These results are in line with our previous findings that the actual consideration isbetween time/use-based maintenance and condition-based maintenance (Goossens andBasten 2015b). The relatively high preference of failure-based maintenance, comparedto the previous sessions, can be explained by the high number of electrical componentswithin the system. These components have a constant failure rate, which means thattheir probability of failure does not change over time and that thus time/use-based andcondition-based maintenance cannot reasonably be applied.

4.4 Evaluation of the final session

As the final part of the session, all participants are handed an evaluation form (seeAppendix B). The evaluation is divided into three categories: the session itself, thehierarchy of criteria, and the final choice made.

Structuring AHP-based maintenance policy selection 13

The first part of the evaluation considers the session itself. This part consists ofquestions about the session in general, its usefulness and the groups with which thesessions are held.

– All participants enjoy doing the session and find the session useful. They indicatethat it was interesting and insightful. They particularly like sharing knowledgethroughout the maintenance chain and the discussions that took place. Learningfrom the different points of view on the problem from the different companiesand their position in the maintenance chain is seen as one of the main benefits.However, these different points of view also led to interpretation issues regardingthe definitions of the criteria, the chosen case, and on how to judge the pairwisecomparisons. This made some participants doubt the accuracy, and thus usefulness,of the final policy preferences.

– To do such a session again, the participants indicate that the session should bemore result oriented, with a clearer goal and more concrete results, perhaps withan adjusted hierarchy. The right moment to do such a session seems to be at thestart of significant developments concerning the system, such as at the start of thedesign phase of a system, the start of a new materiel project, or at the introductionof new systems within the fleet.

– The diversity and size of the group with which the session was held are highlyregarded. One participant even states that the group was almost perfect, but twoparticipants pitied the lack of actual end users of the system (i.e., naval crewmembers).

The second part of the evaluation is about the hierarchy of criteria. The questionsare meant to determine if the hierarchy is clear and understandable, and if any criteriaare lacking or redundant.

– The hierarchy is generally well received and understandable. However, afterconsiderable discussion on the criteria, the participants seem to agree on thefollowing four comments:1. although safety plays an important role within maintenance, safety should

be a pre-condition for maintenance, so that the inclusion of safety within thehierarchy is debatable;

2. a focus on life-cycle costs would be more relevant than the current focus onmaintenance costs;

3. availability and reliability are too much alike, including either one would besufficient; and

4. the definitions are too generic and using more precise definitions, such asformulas, could help.

– Several suggestions are made regarding lacking criteria: maintainability, function-ality, sustainability and performance.

The third and final part of the evaluation considered the decision. Here the ques-tions focus on the final maintenance policy selected during the session, insight gainedduring the session, and the level in the system for which a policy was selected.

14 A.J.M. Goossens et al.

– The participants indicate that they would not have chosen for the same final policypreference and four participants specifically indicate that they would intuitivelyhave given failure-based maintenance a higher preference.

– However, six participants indicate that they now better understand how the finalselection was made. Two participants are indifferent.

– After the initial debate and the session, for the ideal level in the system for which amaintenance policy can be selected using such a session, the participants indicateeither system level or line replaceable unit (LRU) level equally. Again, the designphase of the system is mentioned as a suitable moment to conduct a session.

– Two participants draw a comparison with Reliability Centred Maintenance (RCM),a widely used maintenance concept (Smith and Hinchcliffe 2004). Feeling thatthe uses differ, they are interested in how the AHP-based MPS approach couldcomplement RCM.

These evaluations are partly in line with the results from our previous research.Based on the comments by the participants, we think that the differences relate to theparticipation of multiple companies, each with their own background and view on themaintenance chain. The increased amount of different views seem to lead to moreinsightful discussions, but to less usable final policy preferences.

Furthermore, it is remarkable that the renewed decision hierarchy as well as thefinal policy preferences obtain such different evaluations from the preliminary sessionand from the multi-company session. At the preliminary session, the hierarchy wasundisputed and the results proved accurate. At the final session, the hierarchy wasextensively debated and the accuracy of the results was doubted. An explanationcould lie in the homogeneity (or diversity) of the group. It seems that a diversegroup allows for more learning from extensive debate on the different views, while ahomogeneous group (already holding similar views) provides more accurate resultsfor actual decision making.

5 Conclusions

This paper set out to structure our AHP-based MPS approach by following the MCDMmethod proposed by Brugha (2004). We have refined the decision hierarchy andvalidated it by organizing and evaluating a final multi-company group session, inwhich participants from four different companies participated. Based on the resultsand evaluations of both the preliminary session and the multi-company session, severalconclusions can be drawn.

– The methodology proposed by Brugha (2004) provides a workable set of 8 stagesand guidelines to structure an MCDM process.

– This structure, in combination with our previous results, enabled us to successfullycreate a workable and concise decision hierarchy. The renewed decision hierarchyretains the core of ship MPS, while greatly reducing the total number of criteriaand sub-criteria and the amount of pairwise comparisons required.

– However, the reactions to this hierarchy are mixed. Most importantly, the roleof the safety criterion is debatable. If safety should act as a pre-condition for

Structuring AHP-based maintenance policy selection 15

maintenance, it could arguably be removed from the hierarchy. However, theimpact that safety has on maintenance should not be neglected. Furthermore, insome cases, such as in the multi-company case, the line between availability andreliability seems to fade. In this case a straightforward explanation was given bythe participants: a naval system has to finish its mission and, therefore, can onlybe considered available if it is reliable enough to finish its mission.

– The preliminary and multi-company sessions suggest that there is a trade-offbetween group diversity and usefulness of the results. A diverse group will havevarious points of view that allow a broader discussion, while a more uniformand like-minded group will have less interpretation issues that will result in moreaccurate final preferences. The former could be used to emphasize on learning, thelatter to emphasize on the actual decision.

– Our previous research revealed that the strength of the AHP-based MPS approachlies in high system level strategic maintenance thinking. This paper adds nuanceto these previous findings. It seems that the best moment to use this approachis at the start of ‘something’, where that ‘something’ can be the design phase,an acquisition project, the introduction of new systems or the development of amaintenance philosophy.

The research and its conclusions give rise to several recommendations for furtherresearch.

– The relations and interdependency of the three top-criteria can be investigatedusing the Analytic Network Process—however, at the cost of a higher complexityof the model.

– Although availability and reliability are clearly defined in literature, an empiricalinvestigation into their actual uses and roles in practice is recommended.

– Finally, a continuation of this research and further investigation into the decisionhierarchy, and new iterations in practice, could create an even more concisedecision hierarchy.

Acknowledgements The authors gratefully acknowledge the hospitality and cooperation of the sessionparticipants: Isaac Barendregt, Hidde Hylarides, David Janse, Desmond Kramer, Chris de Ron, ArjenSchaper, Ferit Serti and Rindert Ypma.

The first and second authors further gratefully acknowledge the support of Lloyd’s Register Foundation.Lloyd’s Register Foundation helps to protect life and property by supporting engineering-related education,public engagement and the application of research.

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A Criteria weights and policy scores

The idealised average global weights of the lowest level criteria and their average policy scores, used as thebasis for this paper, are shown in Figure 2.

Fig. 2 Idealised average global weights of the lowest level criteria and their average policy scores, fromGoossens and Basten (2015b).

18 A.J.M. Goossens et al.

B Evaluation form questions

1. The session(a) What did you think of the session?(b) Did you find it useful? Why or why not?(c) Did you enjoy it? Why or why not?(d) What do you think of the duration of the session?(e) Would you want to do such a session more often? Why or why not?(f) If so, at which kind of moments, and at which intervals?(g) What did you think of the group? For example, of the number of participants and their various

roles.(h) Do you have any suggestions for improvement?

2. The hierarchy of criteria(a) Do you think the hierarchy is clear and understandable? Why or why not?(b) What do you think of the groupings and divisions made in the hierarchy?(c) Are any criteria lacking? If so, which?(d) Are any criteria redundant or unnecessary? If so, which?

3. The decision(a) During the session, one of the maintenance policies emerged as the best. Would you yourself have

chosen for the same policy? Why or why not?(b) Do you feel that you now better understand how the choice is made? How come?(c) For which level in the system would you ideally select a maintenance policy during a session like

this one?4. Do you have any other remarks?

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373 2012 Service differentiation in spare parts supply through dedicated stocks

E.M. Alvarez, M.C. van der Heijden, W.H.M. Zijm

372 2012 Spare parts inventory pooling: how to share the benefits? Frank Karsten, Rob Basten

371 2012 Condition based spare parts supply X. Lin, R.J.I. Basten, A.A. Kranenburg, G.J. van Houtum

370 2012 Using Simulation to Assess the Opportunities of Dynamic Waste Collection

Martijn Mes

369 2012 Aggregate overhaul and supply chain planning for rotables J. Arts, S.D. Flapper, K. Vernooij

368 2012 Operating Room Rescheduling J.T. van Essen, J.L. Hurink, W. Hartholt, B.J. van den Akker

367 2011 Switching Transport Modes to Meet Voluntary Carbon Emission Targets

Kristel M.R. Hoen, Tarkan Tan, Jan C. Fransoo, Geert-Jan van Houtum

366 2011 On two-echelon inventory systems with Poisson demand and lost sales

Elisa Alvarez, Matthieu van der Heijden

365 2011 Minimizing the Waiting Time for Emergency Surgery J.T. van Essen, E.W. Hans, J.L. Hurink, A. Oversberg

Nr. Year Title Author(s)364 2012 Vehicle Routing Problem with Stochastic Travel Times

Including Soft Time Windows and Service CostsDuygu Tas, Nico Dellaert, Tom van Woensel, Ton de Kok

363 2011 A New Approximate Evaluation Method for Two-Echelon Inventory Systems with Emergency Shipments

Erhun Özkan, Geert-Jan van Houtum, Yasemin Serin

362 2011 Approximating Multi-Objective Time-Dependent Optimization Problems

Said Dabia, El-Ghazali Talbi, Tom Van Woensel, Ton de Kok

361 2011 Branch and Cut and Price for the Time Dependent Vehicle Routing Problem with Time Windows

Said Dabia, Stefan Röpke, Tom Van Woensel, Ton de Kok

360 2011 Analysis of an Assemble-to-Order System with Different Review Periods

A.G. Karaarslan, G.P. Kiesmüller, A.G. de Kok

359 2011 Interval Availability Analysis of a Two-Echelon, Multi-Item System

Ahmad Al Hanbali, Matthieu van der Heijden

358 2011 Carbon-Optimal and Carbon-Neutral Supply Chains Felipe Caro, Charles J. Corbett, Tarkan Tan, Rob Zuidwijk

357 2011 Generic Planning and Control of Automated Material Handling Systems: Practical Requirements Versus Existing Theory

Sameh Haneyah, Henk Zijm, Marco Schutten, Peter Schuur

356 2011 Last time buy decisions for products sold under warranty Matthieu van der Heijden, Bermawi Iskandar

355 2011 Spatial concentration and location dynamics in logistics: the case of a Dutch province

Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. Fransoo

354 2011 Identification of Employment Concentration Areas Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. Fransoo

353 2011 BPMN 2.0 Execution Semantics Formalized as Graph Rewrite Rules: extended version

Pieter van Gorp, Remco Dijkman

352 2011 Resource pooling and cost allocation among independent service providers

Frank Karsten, Marco Slikker, Geert-Jan van Houtum

351 2011 A Framework for Business Innovation Directions E. Lüftenegger, S. Angelov, P. Grefen

350 2011 The Road to a Business Process Architecture: An Overview of Approaches and their Use

Remco Dijkman, Irene Vanderfeesten, Hajo A. Reijers

349 2011 Effect of carbon emission regulations on transport mode selection under stochastic demand

K.M.R. Hoen, T. Tan, J.C. Fransoo, G.J. van Houtum

348 2011 An improved MIP-based combinatorial approach for a multi-skill workforce scheduling problem

Murat Firat, Cor Hurkens

347 2011 An approximate approach for the joint problem of level of repair analysis and spare parts stocking

R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten

346 2011 Joint optimization of level of repair analysis and spare parts stocks

R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten

345 2011 Inventory control with manufacturing lead time flexibility Ton G. de Kok

344 2011 Analysis of resource pooling games via a new extension of the Erlang loss function

Frank Karsten, Marco Slikker, Geert-Jan van Houtum

343 2011 Vehicle refueling with limited resources Murat Firat, C.A.J. Hurkens, Gerhard J. Woeginger

342 2011 Optimal Inventory Policies with Non-stationary Supply Disruptions and Advance Supply Information

Bilge Atasoy, Refik Güllü, Tarkan Tan

341 2011 Redundancy Optimization for Critical Components in High-Availability Capital Goods

Kurtulus Baris Öner, Alan Scheller-Wolf, Geert-Jan van Houtum

340 2011 Making Decision Process Knowledge Explicit Using the Product Data Model

Razvan Petrusel, Irene Vanderfeesten, Cristina Claudia Dolean, Daniel Mican

339 2010 Analysis of a two-echelon inventory system with two supply modes

Joachim Arts, Gudrun Kiesmüller

Nr. Year Title Author(s)338 2010 Analysis of the dial-a-ride problem of Hunsaker and

SavelsberghMurat Firat, Gerhard J. Woeginger

335 2010 Attaining stability in multi-skill workforce scheduling Murat Firat, Cor Hurkens334 2010 Flexible Heuristics Miner (FHM) A.J.M.M. Weijters, J.T.S. Ribeiro333 2010 An exact approach for relating recovering surgical patient

workload to the master surgical scheduleP.T. Vanberkel, R.J. Boucherie, E.W. Hans, J.L. Hurink, W.A.M. van Lent, W.H. van Harten

332 2010 Efficiency evaluation for pooling resources in health care Peter T. Vanberkel, Richard J. Boucherie, Erwin W. Hans, Johann L. Hurink, Nelly Litvak

331 2010 The Effect of Workload Constraints in Mathematical Programming Models for Production Planning

M.M. Jansen, A.G. de Kok, I.J.B.F. Adan

330 2010 Using pipeline information in a multi-echelon spare parts inventory system

Christian Howard, Ingrid Reijnen, Johan Marklund, Tarkan Tan

329 2010 Reducing costs of repairable spare parts supply systems via dynamic scheduling

H.G.H. Tiemessen, G.J. van Houtum

328 2010 Identification of Employment Concentration and Specialization Areas: Theory and Application

Frank P. van den Heuvel, Peter W. de Langen, Karel H. van Donselaar, Jan C. Fransoo

327 2010 A combinatorial approach to multi-skill workforce scheduling M. Firat, C. Hurkens

326 2010 Stability in multi-skill workforce scheduling M. Firat, C. Hurkens, A. Laugier325 2010 Maintenance spare parts planning and control: A framework

for control and agenda for future researchM.A. Driessen, J.J. Arts, G.J. van Houtum, W.D. Rustenburg, B. Huisman

324 2010 Near-optimal heuristics to set base stock levels in a two-echelon distribution network

R.J.I. Basten, G.J. van Houtum

323 2010 Inventory reduction in spare part networks by selective throughput time reduction

M.C. van der Heijden, E.M. Alvarez, J.M.J. Schutten

322 2010 The selective use of emergency shipments for service-contract differentiation

E.M. Alvarez, M.C. van der Heijden, W.H.M. Zijm

321 2010 Heuristics for Multi-Item Two-Echelon Spare Parts Inventory Control Problem with Batch Ordering in the Central Warehouse

Engin Topan, Z. Pelin Bayindir, Tarkan Tan

320 2010 Preventing or escaping the suppression mechanism: intervention conditions

Bob Walrave, Kim E. van Oorschot, A. Georges L. Romme

319 2010 Hospital admission planning to optimize major resources utilization under uncertainty

Nico Dellaert, Jully Jeunet

318 2010 Minimal Protocol Adaptors for Interacting Services R. Seguel, R. Eshuis, P. Grefen317 2010 Teaching Retail Operations in Business and Engineering

SchoolsTom Van Woensel, Marshall L. Fisher, Jan C. Fransoo

316 2010 Design for Availability: Creating Value for Manufacturers and Customers

Lydie P.M. Smets, Geert-Jan van Houtum, Fred Langerak

315 2010 Transforming Process Models: executable rewrite rules versus a formalized Java program

Pieter van Gorp, Rik Eshuis

314 2010 Working paper 314 is no longer available ----313 2010 A Dynamic Programming Approach to Multi-Objective Time-

Dependent Capacitated Single Vehicle Routing Problems with Time Windows

S. Dabia, T. van Woensel, A.G. de Kok

312 2010 Tales of a So(u)rcerer: Optimal Sourcing Decisions Under Alternative Capacitated Suppliers and General Cost Structures

Osman Alp, Tarkan Tan

311 2010 In-store replenishment procedures for perishable inventory in a retail environment with handling costs and storage constraints

R.A.C.M. Broekmeulen, C.H.M. Bakx

310 2010 The state of the art of innovation-driven business models in the financial services industry

E. Lüftenegger, S. Angelov, E. van der Linden, P. Grefen

Nr. Year Title Author(s)309 2010 Design of Complex Architectures Using a Three Dimension

Approach: the CrossWork CaseR. Seguel, P. Grefen, R. Eshuis

308 2010 Effect of carbon emission regulations on transport mode selection in supply chains

K.M.R. Hoen, T. Tan, J.C. Fransoo, G.J. van Houtum

307 2010 Interaction between intelligent agent strategies for real-time transportation planning

Martijn Mes, Matthieu van der Heijden, Peter Schuur

306 2010 Internal Slackening Scoring Methods Marco Slikker, Peter Borm, René van den Brink

305 2010 Vehicle Routing with Traffic Congestion and Drivers' Driving and Working Rules

A.L. Kok, E.W. Hans, J.M.J. Schutten, W.H.M. Zijm

304 2010 Practical extensions to the level of repair analysis R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten

303 2010 Ocean Container Transport: An Underestimated and Critical Link in Global Supply Chain Performance

Jan C. Fransoo, Chung-Yee Lee

302 2010 Capacity reservation and utilization for a manufacturer with uncertain capacity and demand

Y. Boulaksil; J.C. Fransoo; T. Tan

300 2009 Spare parts inventory pooling games F.J.P. Karsten; M. Slikker; G.J. van Houtum

299 2009 Capacity flexibility allocation in an outsourced supply chain with reservation

Y. Boulaksil, M. Grunow, J.C. Fransoo

298 2010 An optimal approach for the joint problem of level of repair analysis and spare parts stocking

R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten

297 2009 Responding to the Lehman Wave: Sales Forecasting and Supply Management during the Credit Crisis

Robert Peels, Maximiliano Udenio, Jan C. Fransoo, Marcel Wolfs, Tom Hendrikx

296 2009 An exact approach for relating recovering surgical patient workload to the master surgical schedule

Peter T. Vanberkel, Richard J. Boucherie, Erwin W. Hans, Johann L. Hurink, Wineke A.M. van Lent, Wim H. van Harten

295 2009 An iterative method for the simultaneous optimization of repair decisions and spare parts stocks

R.J.I. Basten, M.C. van der Heijden, J.M.J. Schutten

294 2009 Fujaba hits the Wall(-e) Pieter van Gorp, Ruben Jubeh, Bernhard Grusie, Anne Keller

293 2009 Implementation of a Healthcare Process in Four Different Workflow Systems

R.S. Mans, W.M.P. van der Aalst, N.C. Russell, P.J.M. Bakker

292 2009 Business Process Model Repositories - Framework and Survey

Zhiqiang Yan, Remco Dijkman, Paul Grefen

291 2009 Efficient Optimization of the Dual-Index Policy Using Markov Chains

Joachim Arts, Marcel van Vuuren, Gudrun Kiesmuller

290 2009 Hierarchical Knowledge-Gradient for Sequential Sampling Martijn R.K. Mes; Warren B. Powell; Peter I. Frazier

289 2009 Analyzing combined vehicle routing and break scheduling from a distributed decision making perspective

C.M. Meyer; A.L. Kok; H. Kopfer; J.M.J. Schutten

288 2010 Lead time anticipation in Supply Chain Operations Planning Michiel Jansen; Ton G. de Kok; Jan C. Fransoo

287 2009 Inventory Models with Lateral Transshipments: A Review Colin Paterson; Gudrun Kiesmuller; Ruud Teunter; Kevin Glazebrook

286 2009 Efficiency evaluation for pooling resources in health care P.T. Vanberkel; R.J. Boucherie; E.W. Hans; J.L. Hurink; N. Litvak

285 2009 A Survey of Health Care Models that Encompass Multiple Departments

P.T. Vanberkel; R.J. Boucherie; E.W. Hans; J.L. Hurink; N. Litvak

284 2009 Supporting Process Control in Business Collaborations S. Angelov; K. Vidyasankar; J. Vonk; P. Grefen

283 2009 Inventory Control with Partial Batch Ordering O. Alp; W.T. Huh; T. Tan282 2009 Translating Safe Petri Nets to Statecharts in a Structure-

Preserving WayR. Eshuis

Nr. Year Title Author(s)281 2009 The link between product data model and process model J.J.C.L. Vogelaar; H.A. Reijers

280 2009 Inventory planning for spare parts networks with delivery time requirements

I.C. Reijnen; T. Tan; G.J. van Houtum

279 2009 Co-Evolution of Demand and Supply under Competition B. Vermeulen; A.G. de Kok

278 2010 Toward Meso-level Product-Market Network Indices for Strategic Product Selection and (Re)Design Guidelines over the Product Life-Cycle

B. Vermeulen, A.G. de Kok

277 2009 An Efficient Method to Construct Minimal Protocol Adaptors R. Seguel, R. Eshuis, P. Grefen

276 2009 Coordinating Supply Chains: a Bilevel Programming Approach

Ton G. de Kok, Gabriella Muratore

275 2009 Inventory redistribution for fashion products under demand parameter update

G.P. Kiesmuller, S. Minner

274 2009 Comparing Markov chains: Combining aggregation and precedence relations applied to sets of states

A. Busic, I.M.H. Vliegen, A. Scheller-Wolf

273 2009 Separate tools or tool kits: an exploratory study of engineers' preferences

I.M.H. Vliegen, P.A.M. Kleingeld, G.J. van Houtum

272 2009 An Exact Solution Procedure for Multi-Item Two-Echelon Spare Parts Inventory Control Problem with Batch Ordering

271 2009 Distributed Decision Making in Combined Vehicle Routing and Break Scheduling

C.M. Meyer, H. Kopfer, A.L. Kok, M. Schutten

270 2009 Dynamic Programming Algorithm for the Vehicle Routing Problem with Time Windows and EC Social Legislation

A.L. Kok, C.M. Meyer, H. Kopfer, J.M.J. Schutten

269 2009 Similarity of Business Process Models: Metics and Evaluation Remco Dijkman, Marlon Dumas, Boudewijn van Dongen, Reina Kaarik, Jan Mendling

267 2009 Vehicle routing under time-dependent travel times: the impact of congestion avoidance

A.L. Kok, E.W. Hans, J.M.J. Schutten

266 2009 Restricted dynamic programming: a flexible framework for solving realistic VRPs

J. Gromicho; J.J. van Hoorn; A.L. Kok; J.M.J. Schutten;

Working Papers published before 2009 see: http://beta.ieis.tue.nl