Multi-objective optimization scheduling for manufacturing process based on virtual workflow models

Z Quan, Y Wang, Z Ji - Applied Soft Computing, 2022 - Elsevier
Currently, processing time, energy consumption and processing quality are three significant
optimization objectives for manufacturing process. The variety of optimization objectives and …

Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey

J Fang, B Cheang, A Lim - Sustainability, 2023 - mdpi.com
Machine scheduling problems associated with semiconductor manufacturing operations
(SMOs) are one of the major research topics in the scheduling literature. Lots of papers have …

Practical reinforcement learning for adaptive photolithography scheduler in mass production

E Kim, T Kim, D Lee, H Kim, S Kim, J Kim… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
This work introduces a practical reinforcement learning (RL) techniques to address the
complex scheduling challenges in producing Active Matrix Organic Light Emitting Diode …

Bayesian Optimization for the Vehicle Dwelling Policy in a Semiconductor Wafer Fab

B Kang, C Park, H Kim, S Hong - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Many semiconductor fabrication plants (fabs) prefer simulation-based decision making for
vehicle dwelling policies because it can capture a fab's scalability and complexity. Vehicle …

[HTML][HTML] An Auction-Based Approach for Multi-Agent Uniform Parallel Machine Scheduling with Dynamic Jobs Arrival

Y Liu, S Sun, G Shen, XV Wang, M Wiktorsson, L Wang - Engineering, 2024 - Elsevier
This paper addresses a multi-agent scheduling problem with uniform parallel machines
owned by a resource agent and competing jobs with dynamic arrival times that belong to …

Imitation learning for Real-Time job shop scheduling using Graph-Based representation

JH Lee, HJ Kim - 2022 Winter Simulation Conference (WSC), 2022 - ieeexplore.ieee.org
Scheduling of manufacturing systems in practice is challenging due to dynamic production
environments, such as random job arrivals and machine breakdowns. Dispatching rules are …

Machine learning-based periodic setup changes for semiconductor manufacturing machines

JH Lee, HJ Kim, Y Kim, YB Kim, BH Kim… - 2021 Winter …, 2021 - ieeexplore.ieee.org
Semiconductor manufacturing machines, especially for photo-lithography processes, require
large setup times when changing job types. Hence, setup operations do not often occur …

DEVELOPMENT OF SIMULATION-BASED SCHEDULER FOR BACK-END STAGES IN SEMICONDUCTOR FOUNDRY.

DH Moon, J Sim, W Ro, DO Kim - International Journal of …, 2023 - search.ebscohost.com
As one of the fastest growing industries, the manufacturing processes of semiconductors
have become more complex, given the need to flexibly and rapidly respond to various …

Dynamic Scheduling Method of Multi-objective Job Shop Based on Reinforcement Learning

Z Zhang, L Qiao, Z Huang - China Intelligent Networked Things …, 2022 - Springer
Aiming at the dynamic scheduling problem in workshop production, we propose a multi-
objective scheduling method. By analyzing the actual dynamic scheduling problem, a …

[PDF][PDF] 시뮬레이션기반반도체포토공정스케줄링을위한샘플링대안비교

윤현정, 한광욱, 강봉권, 홍순도 - 한국시뮬레이션학회논문지, 2023 - koreascience.kr
요 약반도체 제조라인 (FAB) 은 복잡하고 불확실한 운영환경에서 작동하는 대규모의
제조시스템 중 하나로 반도체 설비 운영을담당하는 엔지니어들은 직관적이고 신속한 공정 …