Material evaluation and selection processes to enable design for manufacture

In order to optimize product designs it is necessary to quickly evaluate many candidate materials in terms of performance and processing costs. Evaluation using physical prototypes yields concrete results but is time intensive and costly when dealing with multiple optimization objectives. As an alternative, computer aided simulation is a reliable means of material evaluation and selection, is increasingly available to smaller companies due to the shrinking cost of computation, and is essential for handling the dual optimization objectives of manufacturability and performance in a timely and cost effective manner. To support this thesis, the author first examines iRobot Corporation's current process of experimental trial and error for evaluating and selecting a polymer material for use in the wheels of its robotic military vehicles. The author then demonstrates that the experimental derived performance results can be reasonably predicted using the viscoelastic properties of polymers, as captured in such models as the standard linear solid model, and that this predictability can be used to quickly simulate wheel performance with computer aided engineering (CAE) tools.

Department dc:contributor.department

Leaders for Manufacturing Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2006

Author dc:creator

• Abler, Craig Bennett, 1975-

Advisor dc:contributor.advisor

• Stephen C. Graves and Randolph E. Kirchain, Jr.

• Sloan School of Management.
• Materials Science and Engineering.
• Leaders for Manufacturing Program.

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

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/37131

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/37131