Modeling Life Cycle Costs

Extending the life of aging weapons systems and designing new systems for affordability forces tradeoffs among performance and economic variables. Decision Dynamics, Inc.'s (DDI's) FleetSight modeling tool quantifies the cost and performance tradeoffs that accompany alternative operation scenarios, maintenance policies and technology upgrades. FleetSight traces the long-term dynamic behavior of systems as management actions, designed to extend the life and lower the support requirements of products, components and personnel, play out under various "what-if?" scenarios.

At the heart of the tool lies a system dynamics simulation model of a weapons system's aging and obsolescence cycle that replicates both the essential physical and operational characteristics of that system and its components. FleetSight simulates the interaction of each system component and attribute as it interacts with other system components and attributes, following each component of the system through years of use and abuse, repair and deterioration. The result is a model that can quantify the life cycle cost of a system as well as the cost and performance tradeoffs that accompany alternative design, upgrade and retirement options.

FleetSight differs from traditional life cycle cost models because it is grounded in causality, not data correlations. Figure 1 diagrams this causal structure.

Figure 1: Primary FleetSight Feedback Relationships

Note the complex feedback pattern that emerges as the forces of aging and obsolescence are matched against a changing maintenance capability. How this match plays out over time determines how well the system performs and how much it costs.

System dynamics simulation methods duplicate real-world behavior because the model follows the same causal logic that underlies reality. The transparency of the system dynamics modeling methodology and its flexibility in allowing users to quickly alter model assumptions or test alternative life extension options contributes to model credibility and encourages its application. Managers obtain more realistic projections than those generated by conventional, static forecasting methods. A dynamic model also enables management to explore the reasons why long-term life cycle support rises or falls in response to alternative technology decisions and support policies.

In many programs designed to support sophisticated weapons systems, the real risk of management lies in unwittingly creating a decision environment in which none of the cost and performance tradeoffs appear acceptable. Actions aimed at solving immediate problems can lead to unintended consequences that create new problems while, at the same time, seeming to limit management's options. Cost projections can begin to spiral out of control while performance inevitably suffers. By offering a control structure to test the consequences of alternative "what-if?" assumptions and scenarios, FleetSight can help managers to avoid ineffective actions, reduce program risk, lower support costs, and develop an affordable strategy to meet program requirements.

By itself, the model structure in Figure 1 is too aggregated to address complicated management issues that arise in such complex processes as maintaining aging aircraft or deciding on the technology to incorporate into a new ship. FleetSight replicates the single model dozens or hundreds of times to depict each component or subsystem, such as engines and compressors, within a larger system, such as an aircraft. An extremely sophisticated model, then, may be easily developed by linking a large number of simpler modules. The result is a complex, but realistic model that remains easy to understand.

Figures 2 and 3 provide two examples of FleetSight applications, the projected retirement of the DD-963 class fleet and the planned Romeo upgrade for the H-60 helicopter. Figure 2 plots the average condition of the remaining ships as retirements reduce the size of the fleet. The blue line plots a baseline projection while the red line plots an increased ops tempo scenario. Comparison of the two graphs shows that the higher ops tempo for the remaining ships will significantly degrade their condition. FleetSight also calculates the operations and maintenance cost for the two scenarios, showing in this case that increasing the ops tempo would add $700 million to the fleet cost over the 11-year retirement period. The capability to quickly examine many such tradeoff scenarios enables planners and decision-makers to identify the best retirement scenario from among hundreds of alternatives.

Figure 2: DD-963 Retirements

Figure 3 plots average condition and availability of the H-60 aircraft fleet. The model includes the Romeo upgrade and the acquisition of new CH-60 aircraft. While the H-60 fleet doubles in size over the 20-year period, the average condition remains relatively stable due to the continual introduction of new aircraft and upgraded aircraft. A stable aircraft average condition also controls the maintenance workload. By simulating dozens of alternative "what-if?" upgrade schedules and maintenance options, program planners can chose the best overall plan that optimizes cost, budgets, readiness and combat effectiveness.

Figure 3: H-60 Romeo Upgrade

FleetSight performs the following functions:

  • accommodates differing technology development cycles and program lifetimes,
  • assesses new technology opportunities,
  • tracks component operation and component failure costs,
  • identifies the links among interdependent subsystems,
  • traces the "what-if?" consequences of alternative service life extension program (SLEP) strategies,
  • adapts to rapidly changing requirements,
  • applies to past and current weapons systems as well as to future systems,
  • supports logistics planning, and
  • forecasts annual maintenance and support costs over the system lifetime.

FleetSight allows program managers to define and test alternative "what-if?" scenarios to trace the consequences among competing policy options, to quantify the impact of specific decisions, and to test the sensitivity of system response to different parameter assumptions. FleetSight offers an innovative simulation tool to support more effective program decision-making.


For further information, call or e-mail:
Victor J. Thombs
11718 Yates Ford Road
Fairfax Station, VA 22039
Phone: (703) 988-0623
Fax: (703) 250-2987