2026-09-19T23:50:54Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1327382026-06-06T00:56:32Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Stephen Graves.
Li, Yangyang,
M.Eng
Massachusetts Institute of Technology.
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2021-10-06T19:56:55Z
2021-10-06T19:56:55Z
2018
2018
https://hdl.handle.net/1721.1/132738
1263579838
Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, September, 2018
Cataloged from the PDF version of thesis.
Includes bibliographical references (pages 43-44).
Drinkworks is a joint venture between Anheuser-Busch InBev and Keurig Green Mountain, with a focus on developing an in-home alcohol system that can prepare different alcoholic beverages. The goal of this project is to forecast the demand for their new product, consisting of appliance and pods, without historical data. For appliance forecast, this paper focuses on an operational level model, SARIMA, which is a time series analysis that considers seasonality and has high accuracy in forecasting. The SARIMA model is implemented with grid search in Python via a demand planning tool, which saves client's time. Weighted consumption rate will be utilized with number of appliance sold to forecast future pods sales. SARIMA model proved to be an effective approach for appliance forecast within client's expectation. A systematic way to forecast pods is also proposed and demonstrated. It is hoped that the results presented here can serve as a basis and help the client with their new product launch.
by Yangyang Li.
M.Eng. in Advanced Manufacturing and Design
M.Eng.inAdvancedManufacturingandDesign Massachusetts Institute of Technology, Department of Mechanical Engineering
51 pages
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
New product forecasting of appliance and consumables : SARIMA model
Thesis
application/pdf
2021-10-06T19:56:55Z
Publication
Master
MechE
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="ac8e8d88-fcec-49d6-9a6b-85f7e6a3970d">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>New product forecasting of appliance and consumables : SARIMA model</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2018</PublicationDate>
<Authors>
<Author>
<DisplayName>Li, Yangyang,
M.Eng
Massachusetts Institute of Technology.</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Mechanical Engineering.</Keyword>
<Abstract>Drinkworks is a joint venture between Anheuser-Busch InBev and Keurig Green Mountain, with a focus on developing an in-home alcohol system that can prepare different alcoholic beverages. The goal of this project is to forecast the demand for their new product, consisting of appliance and pods, without historical data. For appliance forecast, this paper focuses on an operational level model, SARIMA, which is a time series analysis that considers seasonality and has high accuracy in forecasting. The SARIMA model is implemented with grid search in Python via a demand planning tool, which saves client's time. Weighted consumption rate will be utilized with number of appliance sold to forecast future pods sales. SARIMA model proved to be an effective approach for appliance forecast within client's expectation. A systematic way to forecast pods is also proposed and demonstrated. It is hoped that the results presented here can serve as a basis and help the client with their new product launch.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>