Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules

Picking operations is the most time-consuming and laborious warehousing activity. Managers have been seeking smart manufacturing methods to increase picking efficiency. Because storage location planning profoundly affects the efficiency of picking operations, this study uses clustering methods to pr...

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Autores principales:	Tzu-An Chiang, Zhen-Hua Che, Ching-Hung Lee, Wei-Chi Liang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	smart manufacturing storage location planning hierarchical clustering K-means clustering consolidated picking strategy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/4c9bcd9ea31647fb8b76b2b0aea55f57
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spelling	oai:doaj.org-article:4c9bcd9ea31647fb8b76b2b0aea55f572021-11-11T15:00:07ZApplying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules10.3390/app112198952076-3417https://doaj.org/article/4c9bcd9ea31647fb8b76b2b0aea55f572021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9895https://doaj.org/toc/2076-3417Picking operations is the most time-consuming and laborious warehousing activity. Managers have been seeking smart manufacturing methods to increase picking efficiency. Because storage location planning profoundly affects the efficiency of picking operations, this study uses clustering methods to propose an optimal storage location planning-based consolidated picking methodology for driving the smart manufacturing of wireless modules. Firstly, based on the requirements of components derived by the customer orders, this research analyzes the storage space demands for these components. Next, this research uses the data of the received dates and the pick-up dates for these components to calculate the average duration of stay (DoS) values. Using the DoS values and the storage space demands, this paper executes the analysis of optimal storage location planning to decide the optimal storage location of each component. In accordance with the optimal storage location, this research can evaluate the similarity among the picking lists and then separately applies hierarchical clustering and K-means clustering to formulate the optimal consolidated picking strategy. Finally, the proposed method was verified by using the real case of company H. The result shows that the travel time and the distance for the picking operation can be diminished drastically.Tzu-An ChiangZhen-Hua CheChing-Hung LeeWei-Chi LiangMDPI AGarticlesmart manufacturingstorage location planninghierarchical clusteringK-means clusteringconsolidated picking strategyTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9895, p 9895 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	smart manufacturing storage location planning hierarchical clustering K-means clustering consolidated picking strategy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	smart manufacturing storage location planning hierarchical clustering K-means clustering consolidated picking strategy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Tzu-An Chiang Zhen-Hua Che Ching-Hung Lee Wei-Chi Liang Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules
description	Picking operations is the most time-consuming and laborious warehousing activity. Managers have been seeking smart manufacturing methods to increase picking efficiency. Because storage location planning profoundly affects the efficiency of picking operations, this study uses clustering methods to propose an optimal storage location planning-based consolidated picking methodology for driving the smart manufacturing of wireless modules. Firstly, based on the requirements of components derived by the customer orders, this research analyzes the storage space demands for these components. Next, this research uses the data of the received dates and the pick-up dates for these components to calculate the average duration of stay (DoS) values. Using the DoS values and the storage space demands, this paper executes the analysis of optimal storage location planning to decide the optimal storage location of each component. In accordance with the optimal storage location, this research can evaluate the similarity among the picking lists and then separately applies hierarchical clustering and K-means clustering to formulate the optimal consolidated picking strategy. Finally, the proposed method was verified by using the real case of company H. The result shows that the travel time and the distance for the picking operation can be diminished drastically.
format	article
author	Tzu-An Chiang Zhen-Hua Che Ching-Hung Lee Wei-Chi Liang
author_facet	Tzu-An Chiang Zhen-Hua Che Ching-Hung Lee Wei-Chi Liang
author_sort	Tzu-An Chiang
title	Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules
title_short	Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules
title_full	Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules
title_fullStr	Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules
title_full_unstemmed	Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules
title_sort	applying clustering methods to develop an optimal storage location planning-based consolidated picking methodology for driving the smart manufacturing of wireless modules
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/4c9bcd9ea31647fb8b76b2b0aea55f57
work_keys_str_mv	AT tzuanchiang applyingclusteringmethodstodevelopanoptimalstoragelocationplanningbasedconsolidatedpickingmethodologyfordrivingthesmartmanufacturingofwirelessmodules AT zhenhuache applyingclusteringmethodstodevelopanoptimalstoragelocationplanningbasedconsolidatedpickingmethodologyfordrivingthesmartmanufacturingofwirelessmodules AT chinghunglee applyingclusteringmethodstodevelopanoptimalstoragelocationplanningbasedconsolidatedpickingmethodologyfordrivingthesmartmanufacturingofwirelessmodules AT weichiliang applyingclusteringmethodstodevelopanoptimalstoragelocationplanningbasedconsolidatedpickingmethodologyfordrivingthesmartmanufacturingofwirelessmodules
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Applying Clustering Methods to Develop an Optimal Storage Location Planning-Based Consolidated Picking Methodology for Driving the Smart Manufacturing of Wireless Modules

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