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Optimizing Flow at a Distribution Center: A Case-Study

Graduate #116
Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering

Corliss Best - Savannah State University


Currently a distribution center in Savannah, GA is undergoing an expansion by adding a new building to their existing distribution center (DC) by adding an additional space of 220,000 square foot building which is slated to have double deep storage space. The new building will have automatic storage retrieval system (ARS) installed, currently the DC has one building that uses ARS, and the proposed new building will be connected with the existing ARS to make it one big storage. The challenge would be to connect the old ARS and new ARS together in a way that they work seamlessly, and more importantly studying the flow of the entire system that includes all four buildings of the DC, three old and one proposed new building. Simulation will be utilized to study the follow of the system and measure various key performance metrics of the system as prescribed by IKEA, including throughput and utilization. The DC receives three types of pallets which are categorized as big, euro, and half, majority of which are stored and others are cross-docked. The primary hypothesis of this project is to optimize the flow in such a way that the storage and retrieval time across the two ARS is at a minimum, and the best utilization and productivity is maintained. Thus the overall cost of internal transportation of pallets that arrive in the DC is at its minimum best. The current research uses simulation to mimic the processes at the distribution center, more specifically we utilize discrete-event simulation. The model has been verified and validated, which is being used to simulate various scenarios which involve random demand and random supply. Additionally, the simulation would provide insight on information like: optimal places for double deep storage, best unloading and loading positions for the ARS, optimal gate assignments for the trucks. The results include internal transportation cost broken down by various scenarios, appropriate maximum service level for each scenario, maximum space utilization best vacancy rates keeping in mind the productivity. SIMIO and Opt Quest are used to simulate and optimize the current system under study. The future research will focus on optimizing flow beyond the two ARS (new and old), this research is particularly important since this case can easily apply to similar distribution centers which face a similar challenge of optimizing their flow.

Funder Acknowledgement(s): This study was supported, in part, by a grant from NSF awarded to Jonathan Lambright, Dean of College of Sciences and Technology; and Suman Niranjan, Associate Professor for Operations Management, Director for Interdisciplinary Transportation Studies, Savannah State University, Savannah, GA, 2015.

Faculty Advisor: Suman Niranjan, niranjans@savannahstate.edu

Role: Working with the company on understating the current system better, building the simulation model, modifying and editing the model for accuracy and validity, presenting the research to the company to make sure the model is mocking the reality, running the simulation and compiling the results.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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