USE OF ADVANCED MODELING AND SIMULATION TECHNIQUES TO IMPROVE PERFORMANCE AND ACCELERATE ACQUISITION OF ARMY VEHICLE SYSTEMS

2024-01-3770

11/15/2024

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

An increasing pace of technology advancements and recent heavy investment by potential adversaries has eroded the Army’s overmatch and spurred significant changes to the modernization enterprise. Commercial ground vehicle industry solutions are not directly applicable to Army acquisitions because of volume, usage and life cycle requirement differences. In order to meet increasingly aggressive schedule goals while ensuring high quality materiel, the Army acquisition and test and evaluation communities need to retain flexibility and continue to pursue novel analytic methods. Fully utilizing test and field data and incorporating advanced techniques, such as, big data analytics and machine learning can lead to smarter, more rapid acquisition and a better overall product for the Soldier. Logistics data collections during operationally relevant events that were originally intended for the development of condition based maintenance procedures in particular have been shown to provide substantial opportunities to apply advanced data analytics.

Citation: R. Heine, B. Frounfelker, L. Salins, C. Wang, “Use of Advanced Modeling and Simulation Techniques to Improve Performance and Accelerate Acquisition of Army Vehicle Systems”, In Proceedings of the Ground Vehicle Systems Engineering and Technology Symposium (GVSETS), NDIA, Novi, MI, Aug. 13-15, 2019.

Meta TagsDetails
DOI
https://doi.org/10.4271/2024-01-3770
Pages
5
Citation
Heine, R., Frounfelker, B., Salins, L., and Wang, C., "USE OF ADVANCED MODELING AND SIMULATION TECHNIQUES TO IMPROVE PERFORMANCE AND ACCELERATE ACQUISITION OF ARMY VEHICLE SYSTEMS," SAE Technical Paper 2024-01-3770, 2024, https://doi.org/10.4271/2024-01-3770.
Additional Details
Publisher
Published
Nov 15
Product Code
2024-01-3770
Content Type
Technical Paper
Language
English