An Examination of Force-on-Force Simulation Integration with Cost and Logistics Analysis in Support of Complex Systems Studies
Bruce Munro, Jason Ruser, Christopher Adams, Brett Malone, Michael Haisma
September 2003
Abstract
A process and software approach has been developed to integrate force-on-force modeling with cost and logistics analysis to provide rapid technology trade-off studies. This technique involves distributed simulation and system performance modeling to evaluate complex sensor scenarios within a battlefield scenario. The work has resulted in a systems methodology that supports cost and logistics optimization. Multiple dissimilar analysis models have been integrated using a software framework. Supporting trade-space studies were then conducted by comparing sensor cost and resulting tactical performance within pre-defined engagement. Several key figures of merit were analyzed to arrive at an overall analysis of alternatives.
CASTFOREM was wrapped and integrated with a Raytheon-proprietary cost/logistics model to create the base capability. Multiple scenarios were constructed for various sensor types using Design of Experiments (DOE) techniques. The complete scenario/sensor combination matrix was run using the automation capabilities of the software framework. Finally, a decision support environment was used to capture the results of the DOE run and compare key figures of merit in context. As a result of this work, crucial decision-making information is quickly rolled-up to key planners for cost and performance evaluation. For example, it was demonstrated that while a candidate sensor’s procurement cost was higher, the overall cost of the battle was much lower, and the resulting loss exchange rate (LER) was improved.
Introduction
Modeling and Simulation can be used in analysis for a wide variety of applications in a wide variety of disciplines. These simulations operating in a isolation can produce a vast body of evidence pertaining to performance, cost, mission effectiveness, reliability, availability, and many others. There is a tremendous opportunity to develop insight from the information if this body of evidence can be mined for trends and expected results. However, most of this information goes under-analyzed because the mechanisms to draw clear and concise relationships between cause and effect do not exist. Even if the relationships are well understood, the analyst in many cases, must manipulate and transcribe this data by hand from one model into another which can be very time consuming.
This concept is well understood by the Simulation and Modeling for Acquisition, Requirements, and Training (SMART) community. There are several ways in which they attempt to bridge these gaps. One way is to create collaborative environments like the Future Combat System's ACE which attempts to unite models, simulations, and their data sets in one digital realm. Another method is High Level Architecture (HLA) AMSO SMART Conference, Detroit, MI - September 2003
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