Gaining an operational edge : piece-picking process optimization

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 66-67). === Order-picking is an integral operation in warehouses and distribution centers (DC), consumi...

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Main Authors: Chen, Stephanie Hsuan-Chia, Han, Eunji
Other Authors: Bruce C. Arntzen.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2017
Subjects:
Online Access:http://hdl.handle.net/1721.1/107522
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-1075222019-05-02T16:18:41Z Gaining an operational edge : piece-picking process optimization Chen, Stephanie Hsuan-Chia Han, Eunji Bruce C. Arntzen. Massachusetts Institute of Technology. Engineering Systems Division. Massachusetts Institute of Technology. Supply Chain Management Program. Massachusetts Institute of Technology. Engineering Systems Division. Supply Chain Management Program. Engineering Systems Division. Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 66-67). Order-picking is an integral operation in warehouses and distribution centers (DC), consuming considerable operating resources and expenses. Numerous studies have attempted to optimize the efficiency and reduce the cost of order-picking. In working with a partner company, this thesis evaluates a proposed mechanism for piece-picking that would achieve this end. The company has a shelf-pack number for each SKU, whereby the SKU must be piece-picked in a quantity that is a multiple of the number. The company has proposed to change this number from 1 to 2 to raise the number of units per pick and reduce the number of picks needed for a SKU. In this thesis, simulation is performed on the company's shipment data from DC to store to reveal the merits and demerits of this scheme. SKUs are segmented into different groups based on their suitability for this scheme as a means of mitigating the negative repercussions of the proposal. The scheme can reduce the number of picks and related costs needed, but it causes a shift of inventory from DC to store, thus creating an increase in store inventory. However, SKUs can be allotted into groups suitable or unsuitable for the scheme depending on the amount of savings generated for a given amount of impact on store inventory. The scheme's benefits and impact on store inventory are thoroughly examined, and their implications on DC inventory are also discussed. This thesis offers a novel perspective into piece-picking optimization, and it finds the proposed scheme viable, simple, and flexible. by Stephanie Hsuan-Chia Chen and Eunji Han. M. Eng. in Logistics 2017-03-20T19:38:15Z 2017-03-20T19:38:15Z 2016 2016 Thesis http://hdl.handle.net/1721.1/107522 962897556 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 67 pages application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Supply Chain Management Program.
Engineering Systems Division.
spellingShingle Supply Chain Management Program.
Engineering Systems Division.
Chen, Stephanie Hsuan-Chia
Han, Eunji
Gaining an operational edge : piece-picking process optimization
description Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 66-67). === Order-picking is an integral operation in warehouses and distribution centers (DC), consuming considerable operating resources and expenses. Numerous studies have attempted to optimize the efficiency and reduce the cost of order-picking. In working with a partner company, this thesis evaluates a proposed mechanism for piece-picking that would achieve this end. The company has a shelf-pack number for each SKU, whereby the SKU must be piece-picked in a quantity that is a multiple of the number. The company has proposed to change this number from 1 to 2 to raise the number of units per pick and reduce the number of picks needed for a SKU. In this thesis, simulation is performed on the company's shipment data from DC to store to reveal the merits and demerits of this scheme. SKUs are segmented into different groups based on their suitability for this scheme as a means of mitigating the negative repercussions of the proposal. The scheme can reduce the number of picks and related costs needed, but it causes a shift of inventory from DC to store, thus creating an increase in store inventory. However, SKUs can be allotted into groups suitable or unsuitable for the scheme depending on the amount of savings generated for a given amount of impact on store inventory. The scheme's benefits and impact on store inventory are thoroughly examined, and their implications on DC inventory are also discussed. This thesis offers a novel perspective into piece-picking optimization, and it finds the proposed scheme viable, simple, and flexible. === by Stephanie Hsuan-Chia Chen and Eunji Han. === M. Eng. in Logistics
author2 Bruce C. Arntzen.
author_facet Bruce C. Arntzen.
Chen, Stephanie Hsuan-Chia
Han, Eunji
author Chen, Stephanie Hsuan-Chia
Han, Eunji
author_sort Chen, Stephanie Hsuan-Chia
title Gaining an operational edge : piece-picking process optimization
title_short Gaining an operational edge : piece-picking process optimization
title_full Gaining an operational edge : piece-picking process optimization
title_fullStr Gaining an operational edge : piece-picking process optimization
title_full_unstemmed Gaining an operational edge : piece-picking process optimization
title_sort gaining an operational edge : piece-picking process optimization
publisher Massachusetts Institute of Technology
publishDate 2017
url http://hdl.handle.net/1721.1/107522
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