Title

Modeling Decision Flow Dynamics For The Reliable Assessment Of Human Performance, Crew Size And Total Ownership Cost

Keywords

Decision dynamics; Human performance; Total ownership cost

Abstract

This chapter aims to demonstrate research progress and current understanding of the impact of acquisition technology selection and manning decisions on maintenance, sustainment, training and total ownership costs for the increasingly complex naval platform. The chapter demonstrates a comprehensive approach based on system dynamics modeling to model complex processes and technology insertion alternatives, with the emphasis on constructing a reliable system dynamics model of the total ownership cost (TOC) and related major human-system components categorized in two groups: human-system performance and manpower skill model to support conducting tradeoff analysis and, technology integration and insertion processes. The system dynamics models presented as the building blocks to ultimately help management determine the required skills and manpower needs in order to meet long term strategic goals of reduced manning and reduced total ownership cost, and avoiding performance risks and hazards. Along with this core model, this chapter three illustrates interaction matrices, redundancy level matrix, crew flexibility matrix and technology interaction matrix. The benefit of the models approach process is to identify the critical factors that lead to unwanted and unforeseen results or behaviors which can affect the attainment of new and/or desired capabilities and total systems readiness. In conclusion, simulated model results demonstrate the ability to track both total ownership cost and the performance of the underlying processes for enhanced decision flow models and reliable assessment.

Publication Date

1-1-2017

Publication Title

Advances in Intelligent Systems and Computing

Volume

481

Number of Pages

117-129

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-319-41627-4_12

Socpus ID

84986209222 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84986209222

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