Forward thinking in reverse : design, implementation, and continuous monitoring of a closed-loop supply chain using optimization, simulation, and dashboard systems to maximize net recovery

Developed during our recent six-month engagement at Dell-a leading computer manufacturer and services provider with one of the world's leading supply chains--we discuss a network flow-based mixed-integer linear program (MILP) model to identify the critical factors in optimizing reverse supply chain design decisions to optimize profit. The model is fast, intuitive, flexible, and robust to uncertainty. Its outputs include specific design recommendations, financial impact estimates, dynamically generated product routing diagrams, and multi-scenario sensitivity analysis. Through two case studies, the first in U.S. smartphone returns and the second in Europe, Middle East and Africa (EMEA) Alienware-branded computer returns, we show how our model fosters standardized, robust strategic decision-making and serves as a platform upon which to build management systems for continuous improvement. We then discuss two such systems: a simulation-based reusable packaging cost-benefit analysis (CBA) calculator, and an automated dashboard for managing disassembly-for-parts decisions.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2011

Author dc:creator

• Vasil, Timothy J. (Timothy James)

Advisor dc:contributor.advisor

• Abbott Weiss and Charles H. Fine.

• Sloan School of Management.
• Electrical Engineering and Computer Science.
• 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/1721.1/66044

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/66044