The Concept and Requirements Exploration process us ed at Virginia Tech is based on a Multi-Objective Optimization approach that explores the design space to produce a NonDominated set of ship design solutions ranked objec tiv ly by Cost, Risk, and Effectiveness. Prior research and effort has also been made to lev erage the validation and verification of the U.S. Navy’s ship synthesis design tool, ASSET, into the Virginia Tech Ship Synthesis Model. This thesis applies Design Structure Matrix theory t analyze and optimize the ASSET synthesis process by reducing or removing the feedb ack dependencies that require the iterative convergence process. This optimized ASSE T synthesis process is used as the basis to develop a new Simplified Ship Synthesis Model (S SSM) using Commercial Off-The-Shelf (COTS) software, ASSET Response Surface Models (RSM s) and simplified parametric equations to build the individual synthesis modules . The current method of calculating an Overall Measur e of Effectiveness (OMOE) used at Virginia Tech is based on expert opinion and pairwi se comparison. This thesis researches methods for building a Design Reference Mission (DR M) composed of multiple operational situations (OpSits) required by the ship’s mission. The DRM is defined using a Model Based Systems Engineering (MBSE) approach and an overall Ship Design System Architecture to define and understand the relationships between var ious aspects of the ship design. The system architecture includes the DRM and enables th e development of Operational Effectiveness Models (OEMs) as an alternative to an expert opinion-based OMOE. The system architecture also provides the means for red efining and optimizing the entire ship design process by capturing the entire process and all related data into a single repository. This thesis concludes with a preliminary assessment of the utility of these various system engineering tools to the naval ship design process.
[1]
Daniel Todd Demko.
Tools for Multi-Objective and Multi-Disciplinary Optimization in Naval Ship Design
,
2005
.
[2]
Alan Brown,et al.
Risk Metric for Multi‐Objective Design of Naval Ships
,
2004
.
[3]
Shmuel Shahak.
Naval ship concept design : an evolutionary approach
,
1998
.
[4]
K. K. Hockman,et al.
Design of experiments
,
1995
.
[5]
Cliff Whitcomb,et al.
A military effectiveness analysis and decision making framework for naval ship design and acquisition
,
2005
.
[6]
Tyson R. Browning.
Process integration using the design structure matrix
,
2002
.
[7]
Fred R. Skolnick,et al.
Laying the foundation for successful systems engineering
,
2000
.
[8]
William A. Hockberger,et al.
Total System Ship Design in a Supersystem Framework
,
1996
.
[9]
Alan Brown,et al.
Methods for Naval Ship Concept and Propulsion Technology Exploration in a CGX Case Study
,
2009
.
[10]
C. J. Baker,et al.
An Analysis of X-Band Calibrated Sea Clutter and Small Boat Reflectivity at Medium-to-Low Grazing Angles
,
2008
.
[11]
R Fisher,et al.
Design of Experiments
,
1936
.
[12]
V. Belton.
A comparison of the analytic hierarchy process and a simple multi-attribute value function
,
1986
.
[13]
T. Saaty,et al.
The Analytic Hierarchy Process
,
1985
.
[14]
Timothy Stephen Mierzwicki,et al.
Risk Index for Multi-Objective Design Optimization of Naval Ships
,
2003
.
[15]
Alan Brown,et al.
Revisiting DDGX/DDG-51 Concept Exploration
,
2007
.
[16]
Alan Brown.
Reengineering the Naval Ship Concept Design Process
,
1998
.
[17]
Swaroop Narasimha Neti.
Ship Design Optimization Using Asset
,
2005
.