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An application of discrete event simulation on order picking strategies: A case study of footwear warehouses

  • K. Mongkut's Univ. Technol. Thonburi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

A footwear business is one of highly competitive markets. Footwear businesses must continuously improve three main key performance measures namely quality, cost and lead time. The case study is one of footwear businesses in Thailand. As customer demands are fragmented, the company needs to offer different products to serve customers' satisfaction. Customer orders are then small quantities, but contain serveral different product types. As a result, picking activities in its warehouse are becoming more difficult especially for sport shoes, fashion shoes and sandals. While individual order picking strategy was utilized, it caused long lead time in its picking process. Its delivery performance cannot be achieved. Discrete event simulation modeling using ARENA was conducted to investigate the performance of one order picking, batch picking and zone picking. It was found that the best alternative is zone picking with 4 orders per batch. The picking time can be shortened about 15%.

Original languageEnglish
Title of host publicationProceedings - 30th European Conference on Modelling and Simulation, ECMS 2016
EditorsThorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose
PublisherEuropean Council for Modelling and Simulation
Pages121-127
Number of pages7
ISBN (Electronic)9780993244025
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event30th European Conference on Modelling and Simulation, ECMS 2016 - Regensburg, Germany
Duration: 31 May 20163 Jun 2016

Publication series

NameProceedings - 30th European Conference on Modelling and Simulation, ECMS 2016

Conference

Conference30th European Conference on Modelling and Simulation, ECMS 2016
Country/TerritoryGermany
CityRegensburg
Period31/05/163/06/16

Keywords

  • Batch picking
  • Order picking
  • Simulation
  • Zone picking

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