Al Hanbali, Ahmad

Rahimi-Ghahroodi, Sajjad

Zijm, Henk

NARCIS 

Integrated resource planning in maintenance logistics

University of Twente Research Information

Optimising vehicle fleet routingLocal search techniques are known tobe efficient at solving such problems -especially large problems. The CBLSengine of OscaR supports the modularspecification of routing problems byassembling problem elements (such asobjective functions, strong and weakconstraints, time windows, traffic jams,SLA as shown in Figure 2). On the otherhand, it provides a rich domain specificlanguage for working out powerfulsearch procedures combining a rich setof neighbourhoods (e.g. insertPoint,onePointMove, threeOpt) in a declara-tive style using movement, acceptor andmeta-heuristic operators (e.g. tabusearch, simulated annealing). This notonly results in very efficient search pro-cedures expressed at the logisticsdomain level but also reduces develop-ment time and facilitates maintenancewhen a problem evolves.Links: [L1] http://oscarlib.bitbucket.org[L2] http://www.simqri.com [L3] http://tango-project.euReferences: [1] Laurent Michel Pascal VanHentenryck. Constraint-based LocalSearch. MIT Press, 2009[2] Renaud De Landtsheer et al., ADiscrete Event Simulation Approachfor Quantifying Risks inManufacturing Processes, Int. Conf. onOperations Research and EnterpriseSystems, February 2016[3] Renaud De Landtsheer et al.,Combining Neighborhoods into LocalSearch Strategies, 11th MetaHeuristicsInternational Conference, June 2015Please contact:Renaud De LandtsheerCETIC, BelgiumTel: +32 472 56 90 99renaud.delandtsheer@cetic.beERCIM NEWS 105   April 2016 35In many Western countries, mainte-nance and overhaul of capital assetsconstitute some 15 % of their GDP.Smart sensor and data gathering tech-niques, as well as advanced decisionsupport  systems, are exploited todesign integrated logistics support(ILS) systems. In the MLOG projectwe focus on an integrated planning ofresources needed for asset mainte-nance rather than the piecemealapproach usually considered in the lit-erature and in practice. The goal is tominimize overall resource investmentssubject to agreed service level con-straints. Exact methods are only com-putationally feasible for very smallproblems, hence we have developedfast but highly accurate approximationmethods. In an actual case study, ourresults show that integrated planningcan achieve an overall cost reductionof up to 27 % without sacrificing theoffered service quality, when com-pared with the common practice solu-tion used in companies. Combining ourapproach with smart sensor and condi-t ion monitoring data (Internet ofThings) may further enhance assetavailability and hence industrial pro-duction both in Qatar and in theNetherlands.Maintenance logistics has received con-siderable attention in recent decadesowing firstly to the significant invest-ments associated with capital-intensiveassets, which in turn require a highoperational availability, and secondly tothe need to prevent environmentaldamage – for example, the BP accidentin 2010 in the Gulf of Mexico - or safetyincidents – for example in medicalequipment and aircraft. Unplanneddowntime of advanced capital equip-ment can be extremely expensive; foran average aircraft it is estimated atsome S10,000 per hour and for a high-tech lithography system in the semicon-ductor industry it may amount up to$100,000 per hour. Consequently,unplanned downtime should be pre-vented as much as possible, forexample, by exploiting advanced condi-tion monitoring techniques and preven-tive maintenance policies, and if theyoccur, they should be kept as short aspossible by using optimal correctivemaintenance policies [1]. The latterimplies that malfunctioning parts orcomponents causing the system break-down are immediately replaced byready-for-use ones, since repair of thecomplete system on site induces unac-ceptable long downtimes. Typically, asystem failure induces a set of actions asdepicted in Figure 1.  Integrated Resource Planning in MaintenanceLogisticsby Ahmad Al Hanbali, Sajjad Rahimi-Ghahroodi, and Henk ZijmThe MLOG (Optimal Exploitation of Resources in Maintenance Logistics) project, executed jointly bythe University of Twente and the University of Qatar, focuses on an integrated planning of resourcesneeded for asset maintenance.Figure1:IntheMLOGproject,wearedevelopingfastapproximationalgorithmstooptimizeservicesupplychains,whilereducingtheoverallcostswith27%inanactualcasestudy.ERCIM NEWS 105   April 201636Special Theme: Logistics and Planning  The availability of resources needed forrepair (spare parts, service engineers, andtools) in fact defines the operationalavailability of the complete asset.However, both spare parts and skilledservice engineers often require highinvestments (parts worth $50,000 are noexception for capital-intensive assets),hence there is a trade-off betweenresource investments and service pro-vided. Much research has been carriedout on spare parts management see [2].So far the planning of resources haslargely been performed independently(per resource) while their simultaneousavailability is essential to minimizedowntimes.ContributionAs part of this project, we have beenstudying a service region in which alocal spare parts inventory suppliesdifferent types of parts. Failures occurrandomly and are often due to onemalfunctioning part that needsreplacement. In addition, a skilledservice engineer is needed to com-plete the repair and replace the defec-tive part. Malfunctioning parts arerepaired off-line and subsequentlystocked for future use. The focus hereis on the integrated, multi-resourceapproach, for which different servicepolicies are available: (i) completebacklog in case of unavailability ofeither parts or engineers, (ii) an emer-gency service fulfillment from anexternal source in case of unavailabil-ity of either parts or engineers, (iii)and the heterogeneous policy withbacklogging for one resource andemergency for the other. The most realistic heterogeneous policywould involve having parts supplied byan emergency service and engineersbacklogging. This is due to the longspare parts replenishment time that isoften encountered compared with theengineers’ service time.  To evaluatesuch a heterogeneous policy, we havedeveloped accurate methods usingMean Value Analysis and LaplaceTransform techniques that can handlepractical problems with a high numberof different types of parts [3]. Ourmethods can tackle these problemsquickly as opposed to the standardMatrix-Geometric approach, which isonly computationally feasible for verysmall problems. This is due to thedetailed description of the system stateneeded in the standard approach. Inaddition, we also consider the overalllogistic support system optimization,i.e., we determine optimal stock levelsand service engineer crew size, suchthat the average total costs (includingspare parts holding costs, hiring cost ofservice engineers, and emergency costs)are minimized subject to pre-specifiedservice level constraints. For real prob-lems with high number of part types,our methods yield solutions very fastwhile the total cost error is negligiblewhen compared with an exact method(only verifiable for small problems).The optimization algorithm demon-strated an overall cost reduction of 27%in an actual case study, when comparedwith the separated optimization, whichis common practice in companies.Future research may include advanceinformation based on condition moni-toring data (smart sensors, IoT) to moveto preventive maintenance, thereby fur-ther increasing asset productivity.  MLOG was awarded by the NPRP pro-gram, 7th cycle in 2014, and funded bythe Qatar National ResearchFoundation for a period of three years,starting from January 2015. References:[1] M.A. Cohen, N. Agrawal, V.Agrawal: “Winning in theaftermarket”, Harvard BusinessReview, 84(5), p.129, 2006[2] C. C. Sherbrooke: “Optimalinventory modeling of systems: multi-echelon techniques”, Springer, 2004.[3] S. R. Ghahroodi et al.: “IntegratedField Service Engineers and Spareparts Planning in MaintenanceLogistics”,. under review..Please contact:Ahmad Al Hanbali, Sajjad RahimiGhahroodi, Henk ZijmUniversity of Twente, The Netherlandsa.alhanbali@utwente.nl,s.rahimighahroodi@utwente.nl,w.h.m.zijm@utwente.nlTrain operators apply for trackcapacity in September each year, and itis the Transport Administration’s job tocombine the trains in the applicationsinto a yearly timetable. In order tomake the timetable problem manage-able for manual planning, only onetrain path is generally constructed foreach train. All conflicts that this trainfaces with some regularity should beresolved in this one train path.However, the traffic pattern is dif-ferent on different days, and to makethis one train path conflict-free for alldays the planner is forced to includeextra time both for conflicts that occur,for example, solely on Mondays, andalso for conflicts that occur solely onWednesdays, even if including extratime only once would have beenenough. This wastes capacity andresults in the train path having unnec-essary stops and time supplements onthe day of operation.Utilising the Uniqueness of operation days to better fulfil Customer Requirementsby Sara GestreliusNo two days are exactly the same on the Swedish railways. Despite this, most trains are grantedonly one train path that they are supposed to use every day of operation. Restricting each train to asingle train path wastes infrastructure capacity and prevents train operators from getting thecapacity they require. In a project funded by the Swedish Transport Administration, SICS Swedish ICTused optimization to plan for each operation day individually. The results show a major improvementin customer requirement fulfilment.

Integrated resource planning in maintenance logistics

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University of Twente Research Information