Advanced aerospace procurement models with sensitivity analysis and optimized demand allocation

The impact of the sourcing function on the profitability of U.S.-based manufacturing firms is more significant than ever. Today, the purchased component of the cost of goods sold for many firms is more than fifty-percent of sales.' As the volume of purchased material grows every year, and the sourcing function impacts corporate profitability more and more, it has become critical that effective analysis techniques and cost models are used in the development and execution of sourcing strategies. Perhaps the most critical element of the sourcing process is the determination of the optimal supplier or portfolio of suppliers who will be responsible for providing purchased materials. This thesis explores the allocation of outsourced material demand to the supply base in the aerospace industry. A significant portion of this research involves the development of a framework to support a strategic sourcing organization in the determination of the most appropriate portfolio of suppliers for a group of similarly manufactured parts. This framework combines total cost sensitivity analysis and demand allocation programming.

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

• Kary, Jason R

Advisor dc:contributor.advisor

• Donald B. Rosenfield and David Simchi-Levi.

• Sloan School of Management.
• Engineering Systems Division.
• 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/1721.1/37126

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/37126