Creating a continuous outbound flow at the flower auction

A case study at Royal FloraHolland Naaldwijk

Master thesis (2024)

Authors

A. Gerritsen Civil Engineering & Geosciences

Contributors

J Vleugel (mentor)
M.B. Duinkerken Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (mentor)
R.R. Negenborn Transport Engineering and Logistics - Mechanical, Maritime and Materials Engineering (mentor)
Ingrid Abels Royal FloraHolland (graduation committee member)
Oscar Binneveld Royal FloraHolland (graduation committee member)
Faculty
Civil Engineering & Geosciences, Civil Engineering & Geosciences
Copyright: © 2024 Anouk Gerritsen
More Info
expand_more

Published Date

05-03-2024

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Civil Engineering & Geosciences

Abstract

This paper investigates how two sequential sub-processes at a flower auction can be well aligned to efficiently execute the overall auction process. Existing literature mainly focuses on warehouses without perishable goods and warehouses where all orders are known before the outbound process is started. However, at a flower auction, the gathering of goods and distribution takes place while the auction is still ongoing. In addition, flowers are vulnerable goods that must be handled with care.
During a case study at Royal FloraHolland Naaldwijk, the current process of order picking and in-house delivery is investigated to find the main strengths and bottlenecks. This is done physically and with data. From this analysis,
it has been found that the main issues are the spread and share of waiting times in the in-house delivery process and the output of the order-picking process that is too low. To improve the overall process based on the found issues, a calculation model has been built in Python to test possible improvements. It has been found that implementing limited waiting times and other alterations to increase efficiency results in a more reliable and better predictable
process that can be executed with approximately the same number of work hours or slightly more than in the current situation.