A model for scheduling the resource deployment in a multi-stage ramp-up production system
- Authors
- Kim, Taebok; Glock, 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.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 산업공학과 > 1. Journal Articles

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.