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Increase resource utilization of Alfa Laval's Vertical Lift Modules by maximizing their order picking share
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2017 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Alfa Laval is currently world leaders within heat transfer, separation and fluid handling. One of their distribution centers is situated in Tumba, Stockholm, where they maintain a storage warehouse used for spare parts to their products. In the warehouse, there are currently 4 216 items located in so called Vertical Lift Modules, VLMs. The goal for DC Tumba is to reach an order line picking share of 40% provided by these VLMs, to decrease time spent on picking activities. The purpose of this project was to evaluate and improve current method for item location management of these VLMs by optimizing its resource utilization to reach a picking share of 40% of total order lines and thereby increase efficiency.

 

Data were provided by Alfa Laval containing item information and historical order lines. Additional data were also collected by measurement tests and observations in the warehouse. A mathematical optimization model was then developed and formulated as a binary Knapsack problem, using the collected data as input. The model was thereafter implemented via AMPL and solved with the Gurobi Optimizer solver and, upon request, by a modified Greedy Heuristic algorithm implemented via VBA in Excel. The Gurobi Optimizer solver generated an order linepicking share from the VLMs of 41,93% and the solution was used to verify the strength and credibility of the solution generated by the Greedy Heuristic solver. The Greedy Heuristic solution resulted in a picking share of 41,25%.

 

Improvement was achieved as the new solutions increased the order picking share from the VLMs with at least seven percentage points, which implies picking time savings of nearly 20% per year. The Greedy Heuristic solver also proved to be almost as good as the exact Gurobi Optimizer solver since the two solutions have 94,44 % of selected items in common. Therefore, the Greedy Heuristic solver is considered good and useful in the future for Alfa Laval

Place, publisher, year, edition, pages
2017. , 30 p.
National Category
Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-136013OAI: oai:DiVA.org:umu-136013DiVA: diva2:1108558
External cooperation
Alfa Laval AB
Educational program
Master of Science in Engineering and Management
Supervisors
Examiners
Available from: 2017-06-13 Created: 2017-06-12 Last updated: 2017-06-13Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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