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Sustainable production scheduling in open innovation perspective under the fourth industrial revolutionopen access

Authors
Shim, Sang-OhPark, KyungBaeChoi, SungYong
Issue Date
Sep-2018
Publisher
MDPI
Keywords
open innovation; sustainability; Fourth Industrial Revolution; scheduling; simulation; setup time; automation; manufacturing system; operation; smart factory
Citation
Journal of Open Innovation: Technology, Market and Complexity, v.4, no.4, pp.1 - 5
Indexed
SCOPUS
Journal Title
Journal of Open Innovation: Technology, Market and Complexity
Volume
4
Number
4
Start Page
1
End Page
5
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/16075
DOI
10.3390/joitmc4040042
ISSN
2199-8531
Abstract
This research addresses a specific issue in the field of operation scheduling. Even though there are lots of researches on the field of planning and scheduling, a specific scheduling problem is introduced here. We focus on the operation scheduling requirements that the Fourth Industrial Revolution has brought currently. From the point of view of open innovation, operation scheduling is known as the one that is using the Internet of Things, Cloud Computing, Big Data, and Mobile technology. To build proper operation systems under the Fourth Industrial Revolution, it is very essential to devise effective and efficient scheduling methodology to improve product quality, customer delivery, manufacturing flexibility, cost saving, and market competence. A scheduling problem on designated parallel equipments, where some equipments are grouped according to the recipe of lots, is considered. This implies that a lot associated with a specific recipe is preferred to be processed on an equipment among predetermined (designated) ones regardless of parallel ones. A setup operation occurs between different recipes of lots. In order to minimize completion time of the last lot, a scheduling algorithm is proposed. We conducted a simulation study with randomly generated problems, and the proposed algorithm has shown desirable and better performance that can be applied in real-time scheduling.
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