Cycle-time analysis and improvement using lean methods within a retail distribution center

Fulfillment cycle-time, or the time it takes to pick an item from inventory, pack it into a box, and load it on a truck for shipment, is one of the main inputs in determining how quickly an online retailer can promise customer order delivery. The faster the fulfillment cycle-time, the later an order can be received and still make the appropriate truck for guaranteed, on-time arrival (e.g. same-day, next day, 3-5 business days). Thus, the customer experience is improved, as they are allowed to place an order later and still receive their purchases quickly. To take advantage of this, the retailer must first be able to measure cycle-time appropriately within their facility. This thesis examines the outbound fulfillment process within an under-performing Amazon fulfillment center (Site A) with the purpose of fully characterizing and measuring fulfillment cycle-time. Comparisons are drawn with like Amazon facilities, and a lean operations approach is taken to identify and eliminate major forms of waste in an effort to shorten cycle-time. The baseline analysis within this thesis provides evidence that current-state cycle-time at Site A is in fact 15% faster than originally thought. However, process improvements were still needed to bring cycle-time in line with the network standard. The remainder of the work within this thesis focuses on these process improvements and develops the following recommendations: 1. Standardize the pick process with a move closer to single piece flow. 2. Reduce and control queue length prior to the pack process in order to reduce non-value-added wait time. 3. Reduce batch size for critical items that must move through the facility the fastest. 4. Rearrange process steps to allow completion in parallel rather than series. The method for evaluating cycle-time and the implementation of lean solutions introduced throughout this thesis are useful as a template for similar analyses throughout the Amazon FC network, as well as within other warehousing and online retailer operations.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Churchill, Hugh (Hugh Edward)

Advisor dc:contributor.advisor

• Stephen Graves and Brian Anthony.

• Sloan School of Management.
• Mechanical Engineering.
• 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/1721.1/99018

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/99018