Design of a repairable item and its logistic support system requires consideration of several interrelated decision problems. These decision problems concern the variables, controllable by the design engineer and/or system manager, which affect system performance. This research develops a framework for integration of these decision problems and evaluation of system design tradeoffs. These design decision problems are represented in the model base of a decision support system (DSS). Interrelationships between decision problems are defined using data flow diagrams. Data flows within and between these decision problems are integrated in the DSS database. A simulation capability, imbedded into the DSS permits short-term, accelerated time excursions into possible futures for decision-making purposes. Alternative system designs are evaluated using a multicriteria decision model which considers reliability, maintainability, availability, and life cycle costs.

The logistic support system is modeled as a multilevel inventory system. These inventories include spare repairable items, spare parts, labor, maintenance equipment, and other support resources. Repairable item and logistic support system design decision problems affect the quantity and location of these inventories. Five decision problems identified by Moore [1986] were selected to demonstrate the utility of this framework. The selected decision problems are: 1) the equipment design problem; 2) the maintenance configuration problem; 3) the spare equipment problem; 4) the level of repair problem; and 5) the replacement policy problem.

The framework developed supports integration of these decision problems throughout the item’s life cycle. A repairable item can be systematically divided into subelements until individual repairable components are identified. This systematic subdivision of the item produces an inverted, tree-like structure. This structure is used as the representational view of the DSS database. As the life cycle progresses and the item design becomes more detailed, the structure expands. The DSS database is designed to accommodate this expansion so that the framework can be used throughout the item’s life cycle. The initial fielding and the retirement of the repairable item population produces nonstationary demands on the logistics support system. A multistream model captures the nonstationary aspects of demand, eliminating the need for item-by-item tracking within the model.

The framework developed is illustrated using a comprehensive case study. The case study addresses the design of a Side Loadable Warping Tug (SLWT) and its logistics support system. A population of SLWT’s must be deployed to meet demands in two different operating environments. The SLWT is a component of the U.S. Navy’s Container Offloading and Transfer System (COTS).