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Improving warehouse picking efficiency using product families

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dc.contributor.advisor Aase, Gerald en_US
dc.contributor.author Shan, Xiaoyue, 1995-- en_US
dc.date.accessioned 2017-05-17T18:59:59Z
dc.date.available 2017-05-17T18:59:59Z
dc.date.issued 2017-05-03
dc.identifier.uri http://commons.lib.niu.edu/handle/10843/17628
dc.description.abstract This research explores how items are grouped into product families in a manner that reduces travel time (or distance) for operators picking orders in a warehouse. By identifying items commonly ordered together and locating those items together in the warehouse, operators can pick multiple items using a single trip rather than separate trips to different warehouse locations. Using secondary data source provided by our business sponsor, this research uses K-means clustering analysis and Market basket analysis as the primary analytic methodologies to generate SKU families. Other technical tools are MS Excel, MS Access and SAS University Edition. This final report gathers the various deliverables pertaining to the four analytic steps: 1) Getting & Exploring Data, 2) Cleaning Data, 3) Analyzing Data, and 4) Presenting Results. Final results reveal fifty items grouped into 6 families can reduce warehouse picking expenses of $420,000 by $40,134.85. This reflects a 9.6% reduction in total warehouse labor expenses. en_US
dc.format.extent 37 pages en_US
dc.language.iso en_US en_US
dc.publisher Northern Illinois University en_US
dc.rights NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors. en_US
dc.subject Product families en_US
dc.subject Improving warehouse picking efficiency en_US
dc.subject warehouse picking en_US
dc.subject Improving warehouse picking efficiency using product families en_US
dc.subject k-means en_US
dc.title Improving warehouse picking efficiency using product families en_US
dc.type.genre Dissertation/Thesis en_US
dc.type Dataset/Spreadsheet en_US
dc.type Image en_US
dc.type Text en_US
dc.contributor.department Department of Operations and Information Management en_US
dc.description.degree B.S. (Bachelor of Science) en_US


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