Jong Hun Woo
서울대학교 조선해양공학과 · 공학
Jong Hun Woo 교수의 연구실은 선박 건조 산업의 디지털 전환을 선도하는 분야에서 활동하고 있습니다. 주요 연구 방향은 산업 4.0 기반 스마트 팩토리 구현을 위한 지능형 계획 및 스케줄링 기술, 특히 강화학습과 시뮬레이션 기반 최적화를 활용한 복잡한 선박 생산 공정의 자동화입니다. 또한, 고변동성 환경에서의 생산 불확실성 대응을 위한 데이터 기반 분석 및 실시간 의사결정 기술 개발에도 집중하고 있습니다.
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
Abstract Multi-agent scheduling algorithm is a useful method for the flexible job shop scheduling problem (FJSP). Also, the variability of the target system has to be considered in the scheduling problem that includes the machine failure, the setup change, etc. This study proposes the scheduling method that combines the independent learners with the implicit quantile network by modeling of the FJSP with high variability to the form of the multi-agent. The proposed method demonstrates superior pe
For several decades, Asian nations such as Korea, Japan and China have been leading the shipbuilding industry since the decline in Europe and America. However, several developing countries such as India, Brazil, etc. are going to make an entrance into the shipbuilding industry. These developing countries are finding technical partners or information providers because they are in situation of little experiences and technologies. Now, the shipbuilding engineering companies of shipbuilding advanced
To maintain the competitiveness of shipyards in the current, difficult situation, further improvements to technology are necessary. Recently, various production technologies have been developed to advance the shipyard production environment under the influence of the Industry 4.0 toward automation, smart factories, and intelligent planning systems. To contribute to such efforts, we introduce a research case aimed at a simulation-based shipbuilding planning system. Shipbuilding planning processes
The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as
Currently, product technologies, information technologies, and market requirements vary rapidly to realise high productivity and reduce cost, creating many problems in the manufacturing industries. In particular, shipbuilding industries face serious scheduling problems owing to their complexity. The existing simulation-based methodology for shipbuilding is limited in that no systematic analysis method exists and complex shipbuilding processes cannot be simulated. This paper proposes a modelling
ABSTRACT During the shipbuilding process, a block assembly line suffers a bottleneck when the largest amount of material is processed. Therefore, scheduling optimization is important for the productivity. Currently, sequence of inbound products is controlled by determining the input sequence using a heuristic or metaheuristic approach. However, the metaheuristic algorithm has limitations in that the computation time increases exponentially as the number of input objects increases, and separate o
Abstract The failure of a subsea production plant could induce fatal hazards and enormous loss to human lives, environments, and properties. Thus, for securing integrated design safety, core source technologies include subsea system integration that has high safety and reliability and a technique for the subsea flow assurance of subsea production plant and subsea pipeline network fluids. The evaluation of subsea flow assurance needs to be performed considering the performance of a subsea product
Production planning is a key part of production management of manufacturing enterprises. Since computerization began, modern production planning has been developed starting with Material Requirement Planning (MRP), and today Enterprise Resource Planning (ERP), Advanced Planning and Scheduling (APS), Supply Chain Management (SCM) has been spreading and advanced. However, in the shipbuilding field, rather than applying these general-purpose production planning methodologies, in most cases, each sh
Shipbuilding competitiveness can be improved by implementing a production planning system that reflects production environments and can achieve a high degree of completion. Unfortunately, even South Korean shipbuilders, which are the world’s most competitive, lack relevant research on the objectives, and a comprehensive evaluation method for the systemisation of the production planning process and the results of production planning. This study proposes a comprehensive ship production planning pr
Today, many middle-sized shipbuilding companies in Korea are experiencing strong competition from shipbuilding companies in other nations. This competition is particularly affecting small- and middle-sized shipyards, rather than the major shipyards that have their own support systems and development capabilities. The acquisition of techniques that would enable maximization of production efficiency and minimization of the gap between planning and execution would increase the competitiveness of sm
Nowadays, the simulation technology aiming at preverifying extensively continues to develop in the manufacturing industry. Though it is possible to apply simulation methodology to various fields in various methods, in particular, the computer simulation of the production system in the manufacturing industry is applied most extensively. Lots of shipyards have made continual studies of the improvement plans on logistics operation of shipyards to cover the ship product constructed anew that consist
Typically, in the shipbuilding industry, several vessels are built concurrently, and a production plan is established through a hierarchical planning process. This process largely comprises strategic planning (long-term) and master planning (mid-term) aspects. The portion that requires the most manual work of the planner is the load balancing in the master planning stage. The load balancing of master planning is an area where optimization studies using mixed integer programming, genetic algorith
A shipyard's production plan has a hierarchical structure comprising a long-term plan and a mid-term or short-term plan. The mid-term schedule is established based on the major schedules of the long-term plan. However, in the long-term planning stage, the mid-term schedule is not considered owing to timing discrepancies and the lack of data. Therefore, even if a major schedule is changed to achieve production goals – such as workload balancing in the mid-term scheduling process – this is not ref
Recently, the speed of change related with enterprise management is getting faster than ever owing to the competition among companies, technique diffusion, shortening of product lifecycles and excessive supply in the market. For example, the requirements (such as delivery date, product quality, etc.) of the ship owner is getting particular and the needs for the new product are being emphasised. This paradigm shift emphasises the rapid response rather than the competitive price and also flexibili
In the shipbuilding industry, each production process has a respective lead time; that is, the duration between start and finish times. Lead time is necessary for high-efficiency production planning and systematic production management. Therefore, lead time must be accurate. However, the traditional method of lead time management is not scientific because it only references past records. This paper proposes a new self-organizing hierarchical particle swarm algorithm (PSO) with jumping time-varyi