OPTIMIZING BASE CAMP RESOURCE EFFICIENCY THROUGH SYSTEMS ENGINEERING

2024-01-3693

11/15/2024

Features
Event
2024 NDIA Michigan Chapter Ground Vehicle Systems Engineering and Technology Symposium
Authors Abstract
Content
ABSTRACT

The Product Director for Contingency Base Infrastructure (PD CBI) is chartered to bring a system-of-systems approach to contingency basing. PD CBI has four major lines of effort to accomplish the mission. This paper briefly touches on the Strategic Recommendations, Analytical Support, and Stakeholder Collaboration and Integration lines of effort and focuses on the Contingency Basing Interface to the Warfighter line of effort. The paper outlines the Model-Based Systems Engineering (MBSE) approach employed by the CBI team, detailing the application of a common set of tools to address each part of the problem. The paper also addresses the use of existing models and simulations, modifying them for use with base infrastructure materiel, and developing new tools as needed, to conduct analyses treating a contingency base as a system of systems (similar to a ground vehicle system). The results of the analyses will provide the Army with materiel investment recommendations for decision makers, optimized base infrastructure-materiel set recommendations, and resource-efficient camp designs. Issues addressed include determining what capabilities the Army should invest in to increase operational/mission effectiveness, reduce risk, and increase operational reach. The analytical results will help identify the optimal mix of capabilities and standardized base camp configurations, cost/benefit in terms of dollars, manpower, resource impacts, etc. The MBSE approach demonstrates the power of bringing together key organizations and mature analytic methods and tools to characterize and quantify critical mission requirements.

Meta TagsDetails
DOI
https://doi.org/10.4271/2024-01-3693
Pages
14
Citation
Moravec, J., "OPTIMIZING BASE CAMP RESOURCE EFFICIENCY THROUGH SYSTEMS ENGINEERING," SAE Technical Paper 2024-01-3693, 2024, https://doi.org/10.4271/2024-01-3693.
Additional Details
Publisher
Published
Nov 15
Product Code
2024-01-3693
Content Type
Technical Paper
Language
English