Quantitative selection of inspection plans for variation risk management

Over the last decade, the importance of quality has increased significantly. Quality improvement efforts involve mitigating the impact of manufacturing variation through robust design, statistical process control (SPC), and inspection. This thesis focuses on the last: how to choose an inspection plan to remove the most variation at the lowest cost. The optimal inspection plan balances the cost of inspection and rework against the cost of increased quality. This thesis describes an empirical analysis and prototype software that employs Monte Carlo simulation and simulated annealing to identify the optimal inspection plan. This thesis demonstrates the functionality of the theory and the software through an example from the aircraft industry.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

1999

Author dc:creator

• Chen, Tony J. (Tony Jeng-Horng), 1975-

Advisor dc:contributor.advisor

• Anna Thornton.

• Mechanical Engineering

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/1721.1/9407

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/9407