Timely delivery of the required spare parts plays an important role in meeting theavailability target and reducing the downtime of production facilities. Spare parts logistics isaffected in complex ways while operating in the Arctic, since the area is sparsely populated andhas insufficient infrastructure. It is also greatly affected by the distinctive operationalenvironment of the region, such as cold temperature, varying forms of sea ice, blizzards, heavyfog, etc. Therefore, in order to have an effective logistic plan, the effect of all influencingfactors, called covariates, on the transportation of the spare parts need to be identified, modelledand quantified by the use of an appropriate dynamic model. The traditional models, however,lack the comprehensive integration of the effect of covariates on the spare parts transportation.The purpose of this paper is to introduce the concept of a dynamic model for spare partstransportation in Arctic conditions by considering the time-independent and time-dependentcovariates. The model continuously updates the prior probabilities according to the most recenttime-dependent covariates to provide posterior probabilities. The application of the model isillustrated using a case study.
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