Supply chain network design to minimize total landed cost

In recent years, markets and supply chains have become increasingly global in nature. Increased competition has driven the need for more efficient and cost-effective supply chain strategies and production methods. Firms have effectively used analytical techniques to develop manufacturing and supply chain solutions at the strategic, tactical, and operational levels. One such analytical technique for assisting in the development of a strategic network design is the use of a supply chain network optimization model. As part of this study, a supply chain network optimization model was implemented for use by an undisclosed company. This company is in the middle of a cultural shift in focus, from that of manufacturing for economies of scale to manufacturing in support of an integrated and efficient supply chain. As part of this transition, the company must develop analytical techniques and tools to support decision-making on questions ranging from strategic to operational in nature. The primary question posed in this study is "How can this company assess supply chain strategies with the goal of minimizing total landed cost?" To address this question, and support strategic discussions on the topic, a supply chain network optimization model was developed using the IBM ILOG LogicNet Plus software package. The model addresses this question by outputting a supply chain network design that minimizes the total landed cost of supplying products to customers. Case studies were conducted to demonstrate the model's ability to inform strategic decision-making. Inputs to the comprehensive total landed cost function were manipulated to show the impacts and tradeoffs associated with the various cost components and to assist in finding robust and sustainable solutions.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Noday, Daniel A. (Daniel Alexander)

Advisor dc:contributor.advisor

• Donald Rosenfield and David Simchi-Levi.

• Sloan School of Management.
• Engineering Systems Division.
• Leaders for Global Operations 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/1721.1/90793

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/90793