Please use this identifier to cite or link to this item: http://earsiv.odu.edu.tr:8080/xmlui/handle/11489/5124
Title: A two-stage stochastic model for workforce capacity requirement in shipbuilding
Authors: Kafali, Mustafa
Aydin, Nezir
Genc, Yusuf
Celebi, Ugur Bugra
Ordu Üniversitesi
0000-0002-2658-1291
0000-0002-8077-1686
0000-0003-3621-0619
0000-0002-4903-5015
Keywords: DESIGN, ASSIGNMENT, SYSTEM
Issue Date: 2022
Publisher: TAYLOR & FRANCIS LTD-ABINGDON
Citation: Kafali, M., Aydin, N., Genç, Y., Çelebi, UB. (2022). A two-stage stochastic model for workforce capacity requirement in shipbuilding. J. Mar. Eng. Technol., 21(3), 146-158. https://doi.org/10.1080/20464177.2019.1704977
Abstract: Studies have been being carried out to make production faster and more organised in the shipbuilding industry, as in other industry. The fact that automation-based works are limited in the shipbuilding industry is one of the biggest challenges encountered in block production as in other stages of shipbuilding. The blocks are time-consuming and difficult components to produce in the shipbuilding process. They are the structures formed by joining the cut metal sheets, profiles and other components. These activities are carried out at the different stations of shipyards. Labour planning is one of the crucial issues in shipbuilding. In this study, the allocation of the required capacity during the pre-production stations of the block production, namely C and D, is examined stochastically. The amount of work, revisions and worker performance under uncertainty factors to be experienced in the production process are included in the problem. A two-stage stochastic mathematical recourse model was established to determine the amount of workforce capacity requirement (man*day) of the planning period at the pre-production station depending on the factors. Scenarios are determined randomly and the near-optimum solution was tried to be obtained by the Sample Average Approximation (SAA) approach.
Description: WoS Categories: Engineering, Marine
Web of Science Index: Science Citation Index Expanded (SCI-EXPANDED)
Research Areas: Engineering
URI: http://dx.doi.org/10.1080/20464177.2019.1704977
https://www.webofscience.com/wos/woscc/full-record/WOS:000503745400001
http://earsiv.odu.edu.tr:8080/xmlui/handle/11489/5124
ISSN: 2046-4177
2056-8487
Appears in Collections:Makale Koleksiyonu

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