A model and solution algorithm for the Repair Kit Problem: An empirical application

Companies selling durable goods should guarantee their availability for the whole lifecycle. When on-site maintenance is required, as in several cases ranging from washing machines to large-sized machineries, field service engineers carry a stock of service parts in their vehicles to carry out repair interventions. The Repair Kit Problem (RKP) aims at determining the stock of service parts to be carried on the vehicles in order to optimize costs and/or customer service level. A literature review highlights that the models developed so far tend to neglect features that are important for practitioners. We propose a deterministic mathematical formulation of the RKP, where the objective function minimizes inventory holding, ordering, delivery and shortage costs subject to budget and service level constraints. We solve to optimality the problem on a set of real instances for the case of a multinational firm that needs to determine the stock of service parts for each of its field engineers. A discrete event simulation model is then developed to test ex-post the performance of the model on actual data. Preliminary results of the application are presented and discussed in the paper.