Intelligent Order Scheduling and Release in a Build to Order Environment

Dell's computer manufacturing process involves a complex system of material flow and assembly. This includes intelligent replenishment of sub-components from local warehouses according to the manufacturing schedule, just-in-time manufacturing of custom configured computer systems including hard-drive image and custom software download, packaging the unit for delivery, order accumulation, and finally, distribution and shipping to the customer. This thesis examines Dell's current order fulfillment process and suggests methods that can help Dell meet or exceed customers' delivery time expectations at minimum logistics cost in the justin-time environment. By manufacturing and shipping products based on certain times of the day, air shipments to certain destinations could be converted to less expensive ground shipments. However, this is only possible when the entire fulfillment process is integrated in such a way that eligible ground shipments meet their appropriate shipping windows. This analysis shows that optimizing these windows not only requires an examination of the average cycle time in each phase but also of the impact that cycle time variations have on the success of this air-to-ground conversion strategy. Through the use of simulation models I found that the key factors in reducing logistics cost require setting appropriate scheduling rules for each order size and reducing the cycle time variation. Thesis Supervisors: Thomas Roemer Assistant Professor of Management David Simchi-Levi Professor of Civil and Environmental Engineering Acknowledgements The author wishes to acknowledge the support and resources made available by the Leaders for Manufacturing Program. This project would not have been possible without support and learning provided by the LFM program and my classmates. The past two years have been truly unique; the knowledge, experience, personal insight, resources, and relationships I have gained over this time are beyond comparison. Dell Inc. provided a rich environment to further my understanding of operations and to work in a truly world-class organization. Dell employees showed a wonderful enthusiasm for teaching and sharing. Special thanks goes to Wayne Zorn whose support and insightfulness enabled my progress during my time at Dell. Additionally, there are many others at Dell who enriched my learning experience and patiently answered many of my questions, including Bill Long, Steve Cook, Alexis Takvorian, Vida Killian, Tina Hameen-Anttila and Ye Mao. Thank you all for your patience and for making my learning experience so enjoyable. To my colleagues and mentors at ABB, my thanks to the many that helped make LFM a possibility. I appreciate your faith in my ability and for sponsoring my education at the LFM Program. Special thanks goes to Kirsi for her hard work. I am grateful for the opportunity and look forward to returning to ABB and working with such a great group of people. I would like to thank my two MIT advisors. Thomas Roemer from Sloan, who endured the Texas heat twice when visiting and who exhibited patience beyond comparison and inspired me in ways that will most certainly shape my future. Thanks also goes to David Simchi-Levi from MIT's Engineering School for his technical insights and support. I also wish to thank my classmates, who taught me the most during my two years at MIT. Their wealth of knowledge, experience and humor will always be a part of my memorable experiences at MIT. I wish you all the greatest success in life. Special thanks goes to Sara and Steve. I learned so much more and had so much more fun because you were in Austin with Mikko and me. Finally, my most heartfelt gratitude is reserved for my friends and family, both new and old, for their support and encouragement. Most of all, I would like to thank my husband and best friend, Mikko who has supported me in every way possible during the highs and lows of the LFM program.