Massachusetts Institute of Technology
Uncovering and avoiding failure modes in driveline and tire/wheel NVH using a computational meta-model
Abstract
dc:description.abstractThe automotive industry has undergone significant changes in recent years with increased competition and the introduction of new manufacturers into the market. With this changing market, a more efficient approach to Noise Vibration and Harshness (NVH) development is needed to foster better decisions and support the compressed product development timing required by the market.To address this, the "Slider Bar" process and meta-model are presented. Based on the failure mode avoidance approach, the process and model allow the engineering teams to uncover and avoid potential tire/wheel and driveline NVH failure modes. Therefore, early in the product development process, development teams can identify control and noise factor limits and system level effects, avoid potential NVH failure modes, and develop appropriate countermeasures.Using insights from innovation diffusion theory, the process and tool were deployed systematically to NVH community, with user insights used to adapt and improve the process and tools. Based on this work, a strategy is introduced for the development and adoption of a failure mode avoidance initiative.
Degree
thesis:*- Department dc:contributor.department
- System Design and Management Program.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2007
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Braunwart, Paul R
- Advisor dc:contributor.advisor
-
- Dan Frey.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/43099
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/43099