Jhamb, Arpan (2021) Optimization of Supply Chain Workflow in Food Industry. Masters thesis, Dublin, National College of Ireland.
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Abstract
Maintaining the freshness of perishable items like cheese is essential especially for restaurant business. This research is aimed at solving a problem of the restaurant and improving the workflow of the restaurant. Based on the historical sales data, the pizza sales for the next day is predicted, the Cheddar cheese used for making the pizza is calculated using forecasting methods Auto Regressive Integrated Moving Average (ARIMA) and TBATS. The performance of both the models are compared using different evaluation parameters where ARIMA outperformed TBATS and used to forecast the sales for the next day. An automated email system is created for sending the notification to the owner of the restaurant stating the quantity of cheese required for the next day. Based on the results obtained, this research can be deployed in the real world for solving the limited space constraints and providing timely information to the restaurant owner.
Item Type: | Thesis (Masters) |
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Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Food Industry |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Clara Chan |
Date Deposited: | 03 Dec 2021 17:26 |
Last Modified: | 03 Dec 2021 17:26 |
URI: | https://norma.ncirl.ie/id/eprint/5169 |
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