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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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