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Evolved Expendable Launch Vehicle (EELV) Discrete Event Simulation: Ensuring the Buck Results in a Bang

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An accurate cost estimate is an essential prerequisite when considering expansion or modification of a major government system. To make an informed decision, cost must be considered in light of the expected benefit of the expenditure, to ensure the investment is justified. We describe one method of performing this analysis, using the EELV supply chain as a demonstrative example. We demonstrate the methodology of Discrete Event Simulation (DES), and its application in the cost community, as a tool to measure the current performance of and potential improvement in the EELV system. We provide a scientific method for analyzing performance and determining the benefit of investing in process improvement. This method could also be used to measure the inefficiency inherent in a process due to contract requirements and decision rules.

EELV is intended to replace legacy launch vehicles and improve the affordability and reliability of satellite launches through modular vehicle design based on common components and central management. Since its inception, the number of EELV launches per year has been lower than expected, but the reason for the lower-than-expected yield is unknown. One explanation for the difference between expected and demonstrated performance is that the system has been unable to run at an efficient level due to external effects (i.e., uncertainty in satellite production). An opposing argument suggests that the system is at full capacity and, in order to increase yield, resources must be increased. Yet a third argument attributes the system inefficiency to suboptimal decision-making rules necessary to conform to political policy. These arguments beg the question: What is the effective capacity of the EELV system, based on the availability of internal resources and necessary supplies?

Effective capacity accounts for the internal capacity and efficiency of the system, as well as the availability of required supplies and other external effects. Our simulation model enables one to determine effective capacity and examine the effect of alternative resource configurations and decision-making rules on total yield. By way of this analysis, inefficiencies in the current process are exposed, highlighting areas of potential improvement. Our results will allow decision-makers to select the most effective strategy for improving system performance, and ensure their investment yields the desired results. Both physical and political factors affecting the system are considered. Some political procedures are necessary to maintain national security, but our preliminary experiments suggest that alternative decision-making rules may be an effective way to improve performance. This is especially true when cost is considered, since procedural change is assumed to be less expensive than a major technology acquisition.

We demonstrate how DES can be utilized to determine system capacity and congestion and the expected benefit of process improvements under consideration. A brief introduction to the methodology will be provided, followed by a discussion of the EELV system and challenges experienced during the modeling process. A description of the ongoing data analysis and the challenges therein will be also given. Preliminary results and initial conclusions will be presented and planned future effort will be described.


Colleen Craig
Ms. Craig is a cost analyst at Technomics with experience in cost research, cost estimation and operations research. In her time at Technomics, she has supported the Air Force Cost Analysis Agency (AFCAA), OSD Cost Assessment and Program Evaluation (CAPE), Deputy Assistant Secretary of the Army-Cost & Economics (DASA-CE) and Department of Homeland Security’s Cost Analysis Division (CAD). For these customers, she has supported database development, EVM analysis, cost research, discrete event simulation, Independent Cost Estimates and development of a technical baseline document, with application areas including defense weapon systems (space systems, missiles, munitions, aircraft and electronics) and telecommunication systems. Prior to joining Technomics in 2009, Ms. Craig was an Industrial Engineer co-op at Walt Disney World Resort where she performed cost analyses and designed and implemented efficiency studies and process improvements. Ms. Craig holds a B.S. in Industrial and Systems Engineering from Virginia Tech and is a member of the Society of Cost Estimating and Analysis (SCEA).

Scott DeNegre
Technomics, Inc
Scott DeNegre has seven years of experience in operations research analysis, with a particular focus in the development of effective solutions for large-scale, real-world systems. Scott’s main application areas include supply chain management, network design, urban planning and security, interdiction problems, and hierarchical decision-making systems. In addition, Scott has over two years of cost analysis experience, during which his methodological focus has been on earned value management, competitive contract analysis, and project scheduling, with application areas including satellite design and development, launch systems, and wheeled and track vehicles. Prior to joining the Technomics team in September 2009, Scott has held positions as a visiting researcher in the Interventional Guidance Technology group at Philips Research North America, an actuarial analyst at Watson Wyatt, and a visiting researcher in the mathematics department at Ecole Polytechnique Federal de Lausanne in Switzerland. Scott received a B.S. in Mathematical Sciences from Johns Hopkins University in 2002, and a M.S. in Management Science from Lehigh University in 2005. He recently defended his doctoral research on critical infrastructure defense and discrete bilevel programming, and will be receiving his Ph.D. from Lehigh University in May 2011. Scott has coauthored several journal papers, presented at a wide variety of professional conferences, and is a member of the Society of Cost Estimating and Analysis (SCEA), the Institute for Operations Research and the Management Sciences (INFORMS), and the Society for Industrial and Applied Mathematics (SIAM).