Network and Workflow Design and Standardization in a Large Distribution Center

The retail industry is experiencing exploding growth in the digital segment and a shift in consumer delivery expectations. While distribution networks and the individual facilities were constructed to fulfill demand for the wholesale and retail channels, this growth is requiring companies to evaluate their network and facility operations to meet digital demand speed that consumers have come to expect. This thesis evaluates both the overall network design and the variability within daily operations that impact overall speed to customer. Optimization was used to evaluate the overall distribution network. The demand distribution was used to determine where to place facilities, which channels to ship from each facility, and where to ship product from to minimize transportation costs, transportation time to customer, and improve sustainability. The optimization reviews these key metrics for different potential network scenarios that could be implemented to improve the network. Within the distribution centers, variability in incoming orders causes variability in the time required to complete batches of orders (waves) before shipping them out. A model was developed based on standard times and wave data to capture real-time variability. This model can be used in conjunction with cross training to smooth the work across the major work areas and improve overall predictability.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Mechanical Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2021

Author dc:creator

• Frigo, Clare

Advisors dc:contributor.advisor

• Graves, Stephen
• Yang, Maria

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright retained by author(s)

Licence dc:rights.uri

• https://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/139457

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/139457