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A model for scheduling the resource deployment in a multi-stage ramp-up production system

Authors
Kim, TaebokGlock, Christoph H.Jaber, Mohamad Y.
Issue Date
May-2025
Publisher
Taylor & Francis
Keywords
Production ramp-up; multi-stage production; learning effect; capacity planning; resource deployment; production planning; SDG 9: Industry; innovation and infrastructure
Citation
International Journal of Production Research, v.63, no.10, pp 3630 - 3654
Pages
25
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Production Research
Volume
63
Number
10
Start Page
3630
End Page
3654
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/208561
DOI
10.1080/00207543.2024.2426694
ISSN
0020-7543
1366-588X
Abstract
Rapid and continuous changes in customer product requirements affect demand, requiring the supply chain to be more responsive. A new product ramp-up is integral to responsiveness, where it is paramount to implement it successfully and manage it effectively. A smooth ramp-up process minimises problems and delays, leading to lower costs and higher profitability. This study develops and analyses a model that describes a multi-stage ramp-up production system to identify the most cost-effective policy for controlling multiple ramp-ups. We propose a search-based optimisation approach to solve the problem. Through numerical analyses, we develop a decision framework to classify the patterns of resource deployment and planning, aiming to make the ramp-up process efficient and responsive to increasing demand. Additionally, we conduct sensitivity analyses to examine how variations in input parameters affect system behaviour. Our findings offer managerial implications and insights based on the numerical results.
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COLLEGE OF ENGINEERING (DEPARTMENT OF INDUSTRIAL ENGINEERING)
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