Assessing the Operational Value of Situational Awareness for AEGIS and Ship Self Defense System (SSDS) Platforms through the Application of the Knowledge Value Added (KVA) Methodology

摘要

As the United States Navy strives to attain a myriad of situational awareness systems that provide the functionality and interoperability required for future missions, the fundamental idea of open architecture (OA) is beginning to promulgate throughout the Department. To make rational, informed decisions concerning the processes and systems that will be integrated to provide this situational awareness, an analytical method must be used to identify process deficiencies and produce quantifiable measurement indicators. The objective of this research is to analyze the AEGIS and Ship Self Defense System (SSDS) track management systems to determine potential operational benefits that could be realized through the application of an OA approach to system design. Through an application of a knowledge value-added (KVA) methodology, knowledge assets inherent in the core processes of a system can be identified, quantified, and subsequently valued. The methodology provides a return on knowledge or ROK (a ratio which measures the knowledge assets resident in a system). This commonality can then be used in the assessment of multiple systems within a common domain. This thesis will model the current track management processes found within the AEGIS and SSDS platforms and apply the KVA methodology to them to determine an 'As Is' process performance baseline. The processes for the current systems will be derived from process flow diagrams, use-case diagrams, interviews with subject matter experts, and a literature review of pertinent documents. The resulting ROK will be analyzed from an operational perspective with respect to a 'To Be' process generated from an OA design. Both the 'As Is' and 'To Be' process analysis will be conducted utilizing the 'learning time' approach to KVA. The core elements of time-to-learn, number of personnel involved, and times fired will produce a ratio of the performance of knowledge assets in each process.