This research investigates the development of a process for Design for Supply Chain (DFSC) a process that aims to reduce the product life cycle costs, improve product quality, improve efficiency, and improve profitability for all partners in the supply chain (SC). It focuses on understanding the impacts and benefits of incorporating the SC configuration problem into the product design phase. As the product design establishes different requirements on the manufacturability, cost, and similar parameters, the SC is also closely linked to product design decisions and impacted by them. This research uniquely combines the impacts of the product design and price decisions on the product demand and the impacts of the SC decisions on cost, lead time, and demand satisfaction.
The developed mathematical models are aimed at economically managing the SC for product design and support not only product design, but also redesign associated with process improvements and design changes in general. This research suggests development of a proactive approach to product design allowing impacts to the SC to be predicted in advance and resolved more quickly and economically. It presents two product and SC design approaches. The sequential approach examines the design of a product followed by the SC design where the simultaneous approach considers both the product and SC designs concurrently. By utilizing Mixed Integer Programming and a Genetic Algorithm, this research studies various research questions which examine modeling preferences and essential performance metrics, impacts of using a sequential versus simultaneous design approach on these performance metrics, the robustness of the resulting SC design, and relative importance of the product and SC design on the profits. To answer these questions, different models are developed, tested with illustrative data, and the results are analyzed.
The test results and industry experts validations conclude that the developed DFSC models add significant value to the product design procedure resulting in a useful decision support tool. The results indicate that the simultaneous DFSC approach captures the complex interactions between the product and supply chain decisions, improving the overall profit of a product across its life cycle.
| Identifer | oai:union.ndltd.org:PITT/oai:PITTETD:etd-11202007-161836 |
| Date | 30 January 2008 |
| Creators | Gokhan, Nuri Mehmet |
| Contributors | Kim LaScola Needy, Bryan Norman, Michael Lovell, Robert Ries, Brady Hunsaker |
| Publisher | University of Pittsburgh |
| Source Sets | University of Pittsburgh |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.pitt.edu/ETD/available/etd-11202007-161836/ |
| Rights | unrestricted, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to University of Pittsburgh or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
Page generated in 0.0018 seconds