Quality function deployment as a tool for including customer preferences in optimising vehicle dynamic behaviour
Expert simulation can solve difficult problems that are beyond the power of even the most insightful designers. However, it also suggests the potential for equipping designers with tools that enhance their insight. This paper proposes a combined application of the Quality Function Deployment (QFD) design technique and a Genetic Algorithm-based (GA) optimisation method to a multi-criteria optimisation design problem to reduce the dimensionality of the problem and, most importantly, to help make choices based on customer preference because the success of the design depends on how well it addresses the wants and needs of the consumers - both internal and external. To illustrate that, a complex vehicle multi-body model that has a significant number of design variables is used. Vehicle performance is assessed using a number of different performance measures calculated over a number of different scenarios. Results show excellent improvements in the vehicle handling performance over three open loop manoeuvres. (A)
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/14775360
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Authors:
- HAGHIAC, H A
- Haque, I
- Publication Date: 2005
Language
- English
Media Info
- Pagination: 311-30
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Serial:
- International Journal of Vehicle Design
- Volume: 39
- Issue Number: 4
- Publisher: Inderscience Enterprises Limited
- ISSN: 1477-5360
- Serial URL: http://www.inderscience.com/jhome.php?jcode=IJVD
Subject/Index Terms
- TRT Terms: Design; Dynamics; Evaluation and assessment; Simulation; Vehicles
- Uncontrolled Terms: Selection
- ITRD Terms: 9011: Design (overall design); 5473: Dynamics; 9020: Evaluation (assessment); 9072: Selection; 9103: Simulation; 1255: Vehicle
- Subject Areas: Design; Vehicles and Equipment; I90: Vehicles;
Filing Info
- Accession Number: 01018472
- Record Type: Publication
- Source Agency: Transport Research Laboratory
- Files: ITRD
- Created Date: Feb 2 2006 8:25AM