Managing configuration options for build-to-order highly customized products with application to specialty vehicles

In the past decades there has been a shift in customer expectations that has had a significant effect in the business models of manufacturing companies. Customer requirements have shifted from accepting standardized products to demanding highly customized products that satisfy their specific requirements. To cope with this change companies have quickly increased the variety of products that they offer in the market place. Unfortunately, often this variety is provided without understanding the implications of the added complexity on the different internal processes. This thesis research focuses on analyzing this fundamental conflict that exists in manufacturing and tries to answer the question: Is there a middle way? A compromise that will balance variety and complexity with the need for efficient production processes. A large data set containing more than 27,000 records was obtained from a software product configuration tool in use by a specialty vehicle company. This data was evaluated utilizing several methods including statistical and network analysis. It was observed that option proliferation was common during the vehicle configuration process which had an option approval rate of more than 50%. In addition, options tended not to be shared among vehicles and reused in vehicle designs. Overall there were 6,848 dormant options out of a total of 17,007. This complexity resulted in low and often negative margins for the vehicles manufactured. An option strategy model was created to aid firms in managing complexity. The model was tested using the available data and it was observed that in general improvements in option management were obtained.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2010

Author dc:creator

• Amador Gallardo, Jorge Enrique

Advisor dc:contributor.advisor

• Olivier de Weck and John Williams.

• Engineering Systems Division.

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/1721.1/62765

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/62765