14 research outputs found

    Investigating maintenance decisions during initial fielding of rolling stock

    Get PDF
    Successful organizations align technology with their competitive strategy. The challenge is first to make the right and timely decisions when acquiring new technology. Next, organizations must make decisions that help configure the maintenance services to fit the technology they acquired. Ideally, new technology should fit seamlessly with company practices and ways of working. In practice, this is rarely the case and there is misalignment. For maintenance service providers, the problem of fitting maintenance of new capital assets to traditional ways of working is especially important. This paper examines the decisions made by a maintenance service provider to maximize cost efficiency during initial fielding of rolling stock. We explore the different decisions made to design the support organization around newly acquired trains used for passenger service

    Defining line replaceable units

    Get PDF
    Defective capital assets may be quickly restored to their operational condition by replacing the item that has failed. The item that is replaced is called the Line Replaceable Unit (LRU), and the so-called LRU definition problem is the problem of deciding on which item to replace upon each type of failure: when a replacement action is required in the field, service engineers can either replace the failed item itself or replace a parent assembly that holds the failed item. One option may be fast but expensive, while the other may take longer but against lower cost. We consider a maintenance organization that services a fleet of assets, so that unavailability due to maintenance downtime may be compensated by acquiring additional standby assets. The objective of the LRU-definition problem is to minimize the total cost of item replacement and the investment in additional assets, given a constraint on the availability of the fleet of assets. We link this problem to the literature. We also present two cases to show how the problem is treated in practice. We next model the problem as a mixed integer linear programming formulation, and we use a numerical experiment to illustrate the model, and the potential cost reductions that using such a model may lead to
    corecore