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Forecasting and lean improvements in the product return management: Case study in Logistic warehouse
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Currently, manufacturing companies/organizations are exceedingly focused on the reverse logistics since it has its own share in the overall profitability and development of the organization. Proper management of the product returns are considered inevitable factor for success by many companies. Warehouses are important part of the reverse logistic chain where major part of the logistic management often require. In order to manage the product returns in an efficient manner in a warehouse, it is very important to have proper planning and proficient method to deal with any uncertain situations. Along with this updating technology, better staff allocation, proper communication etc. are considered as very important for the better function of the product returns management in an organization. 

The study was conducted in returns management section of a warehouse facility. The aim of the thesis is to tackle the uncertainty with the help of an efficient forecasting method to predict rate of product returns and further to understand the importance of forecasting in upbringing the performance of the warehouse. The first phase of the study also investigates through the current trend of the rate of reverse flow and proposal of the best suited method for forecasting of the future state. The second aim of the thesis is to improve the current method utilized for managing the product returns in the warehouse and improve the overall cycle time of the system under study. Second phase of the research also focuses towards lean warehousing by eliminating the warehouse wastes in the return management section. Finally, the results obtained in the study is linked with building and improving the key performance indicators (KPI’s) in the return management section of the case company. 

Place, publisher, year, edition, pages
2019.
Keywords [en]
Reverse logistics, return management, lean warehousing, key performance indicators, forecasting, ARIMA
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hj:diva-47330ISRN: JU-JTH-PRS-2-20200068OAI: oai:DiVA.org:hj-47330DiVA, id: diva2:1384829
Available from: 2020-01-13 Created: 2020-01-10 Last updated: 2020-01-13Bibliographically approved

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1415161718192017 of 31
CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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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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