JaeBong Cho
Research Subjects
JaeBong Cho has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Dohun Kim
Electronics and Telecommunications Research Institute (ETRI), 22, Daewangpangyo-ro 712beon-gil, Bundang-gu, Seongnam-si 13488, Gyeonggi-do, Republic of Korea
1 shared publication - Kyungmo Yang
HCNC, Seongnam 13486, Republic of Korea
1 shared publication - Soonil Jung
HCNC, Seongnam 13486, Republic of Korea
1 shared publication - Wonjong Kim
Electronics and Telecommunications Research Institute, Daejeon 34129, Republic of Korea
1 shared publication
Latest Publications
- Open Access
- 6 December 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (23) , 11396
Efficient Task Scheduling Using Constraints Programming for Enhanced Planning and Reliability
This paper presents an efficient schedule method for maintenance, repair, and overhaul (MRO) tasks for aircraft engines using a constraint programming algorithm. Using data obtained from Korean Air’s MRO maintenance logs, we analyze and predict the optimal scheduling of regular inspections and fault repairs for various engine types. By proposing a proper modeling of the problem and preparing data for the constraint programming algorithm, we demonstrate superior performance in scheduling efficiency and resource utilization. The experimental results show an average utilization of 99.35%, and the method can even achieve 100% utilization in some cases.
- 6 December 2024
- Published by MDPI AG in Applied Sciences
- Vol. 14 (23) , 11396
Open AccessEfficient Task Scheduling Using Constraints Programming for Enhanced Planning and Reliability
This paper presents an efficient schedule method for maintenance, repair, and overhaul (MRO) tasks for aircraft engines using a constraint programming algorithm. Using data obtained from Korean Air’s MRO maintenance logs, we analyze and predict the optimal scheduling of regular inspections and fault repairs for various engine types. By proposing a proper modeling of the problem and preparing data for the constraint programming algorithm, we demonstrate superior performance in scheduling efficiency and resource utilization. The experimental results show an average utilization of 99.35%, and the method can even achieve 100% utilization in some cases.