2012-MMT109

A Canadian F-35A Joint Strike Fighter Cost Estimation Model

Methods and Models I Track

MMT109_Presentation_CanadianF-35AJointStrikeFighterCostEstModel_Kaluzny

MMT109_Paper_CanadianF35AJointStrikeFighterCostEstModel_Kaluzny

Abstract:

The F-35 Joint Strike Fighter (JSF) is a single-engine, stealthy (radar-evading), supersonic multi-role fighter. Canada intends to purchase 65 F-35A-conventional takeoff and landing variant (CTOL) – jets for delivery between 2016 and 2022. In order to secure production, Canada will likely have to commit to procurement as early as 2012. Until recently, Canada relied on the United States (U.S.) JSF Program Office (JPO) for projected costs. In early 2011, the Department of National Defence (DND) F-35A cost estimate came under public scrutiny as a result of a Parliamentary Budget Officer report (Canada’s equivalent to the U.S. Congressional Budget Office) claiming that the cost would be double the DND estimate. In response, DND presented the JPO projected cost figures and production plans and argued that, although current unit recurring flyaway (URF) costs are high, as the production line becomes more efficient and production capacity increases, the URF costs will go down and Canada will buy at around the peak of production efficiency. By relying on the U.S. JPO, Canada’s DND lacked the ability to independently scrutinize JPO estimates in detail or provide Canadian decision-makers a complete understanding of the cost projections and associated risk/uncertainty. Even the claim that Canada would buy at around the peak of production efficiency lacked independent proof. Canada’s F-35A cost became a major issue of the 2011 federal elections.

To enable due diligence, Defence Research & Development Canada (DRDC) developed an independent F-35A cost estimation model based on quantity effects methods employed by the Research and Development (RAND) Corporation. The model combines cost improvement and production rate effects: In theory, a large quantity ordered over time will lead to accumulated experience in producing the same system year after year, reducing the unit cost. Similarly, high production rates likely reduce the unit cost through greater operating efficiency and the spreading of fixed costs over more units.

Canada’s model was employed in various ways to enhance senior decision making:

1. Given JPO’s production profile and actual costs ((the latest estimate-at-completion (EAC) cost data) of completed Low-Rate-Initial-Production lots, the model outputted a secondary, independent cost estimate of the average unit recurring flyaway (URF) cost that Canada will likely pay for their F-35A CTOL aircraft on a year-by-year basis.
2. The model was used to reverse engineer anticipated U.S learning slope percentages from JPO cost projections and compare them to historical observations.
3. The model facilitated sensitivity analysis, such as determining the fiscal impact on Canada should international partners cancel or downsize their F-35A orders. Similarly, sensitivity to changes to learning slope percentages was analyzed.
4. The model was used to evaluate the optimality of JPO’s/Lockheed Martin’s production profile.

The model provided the Canada with the means to scrutinize JPO cost projections and rigorously defend the Canadian Department of National Defence cost estimates. Using a U.S. Naval Centre for Cost Analysis (NCCA) model based on historical cost growth, risk and uncertainty analysis of the predictions was analyzed, facilitating the selection of an appropriate level of confidence (in the baseline estimate) for appropriate contingency planning and decision-maker awareness.

Author:

Bohdan L. Kaluzny
Defence Research & Development Canada Centre for Operational Research & Analysis
Bohdan L. Kaluzny is a defence scientist with Defence Research & Development Canada, Centre for Operational Research & Analysis. Dr. Kaluzny obtained his doctorate degree in computer science from McGill University and his research interests include polyhedral computation, combinatorial optimization, multi-criteria decision analysis, and operations research.