author Kim Hyun Jun 
2nd author Jinwoo Park
Sunghoon Kim
Sang Hyup Lee
Seung Jin Ha 
presenter Kim Hyun Jun 
info This conference paper has been presented by Kim Hyun Jun the Asia-Simulation Conference. The conference has been held in Jeju, Korea, Republic of, 2015/11/04 ~ 2014/11/07 . 
year 2015 
category IC 
start / end date 2015-11-04 ~ 2015-11-07 
city / nation Jeju / Korea 
학회 AsiaSim 
keywords Lay-out Planning, Priority Policy, Dynamic Programming, Simulation 
abstract Though numerous studies have dealt the lay-out planning methods for shipbuilding industry, in practice the lay-out planning is still done by people under the rule of thumb. It seems illogical to treat such key resource without any scientific management, however matters such as reliability, frequent modifications, and lack of data makes it hard to adapt an automated method in such spatial planning.
To investigate on this problem this paper examines a heavy industry company in Korea and executes a simulation study. The targeted company produces numerous types of offshore plants which all follows varying production processes. So it is told that there exists some special difficulties in predicting and managing newly given constructions. Also another characteristic that makes managing such work difficult is that there exists frequent change requests to design process, quantity, and schedule.
Like many other competitive companies, company H still relies solely on human resource to plan the lay-outs without using any automated systems. This could cause problems such as long hours spent in planning/evaluating the lay-out plan and the difficulty in attaining a substitute for such planning jobs. This is because the current lay-out planning process depends heavily on the experiences of the planner. The difficulty of training a worker to become such specialist is one thing, but to find a substitute in the case of emergency is a more serious problem.
To solve this problem this paper suggests a practical algorithm that can deploy the blocks under a short given time. The system would automatically prioritize the blocks that needs to be placed on the yards and find a location that could maximize the yard utilization and minimize the delays on the site. However because of the uncertainties in the field, such as assembly modifications, contract date delays, and variations in the processing time, it is extremely difficult to find an optimal solution in such short given time.
Studies done by Li(2005) have divided the lay-out process into two separate steps, prescheduling and spatial planning. Here the second step utilized the genetic algorithm. Other researches such as Raj(2007) treated this problem as a 3D bin packing problem, while Zheng(2011) approached this matter using greedy algorithm to minimize the makespan. However none of the previous works considered the uncertainties that exits on the spatial planning process.
So to aid the suggested problem this simulation study aims to find a priority rule to deploy the blocks while considering the uncertainties. Measures such as block size, delayed time of the selected block, and so on would be examined through simulation to find the best performing weights for such variables. Blocks will be prioritized under this rule and will be placed on the yards using the suggested algorithm.
A typical process of such simulation would go through following steps. The first step would be deciding the timeline of deployment. After selecting the timeline target project will be selected. The term project used here is a group of modules and blocks that needs to be placed on the yard. The next step would be choosing the weights for the priority rule. Measures such as delayed time, deployment time, and the size of the block would be considered. By simulating the model while varying the weights of such measures, we will be able to suggest the best performing block selecting policy rule for the spatial lay-out planning. 
번호 category 학회 제목 author presenter year
75 IC  ISCM  Integrated Models for Multi-level Planning and Scheduling in Supply Chain Haejoong Kim    2006 
74 IC  INFORMS-KORMS  Hybrid Algorithms in Integrated Quality Design & Scheduling Jonghan Kim    2000 
73 IC  INFORMS-KORMS  Development of capacitated event-driven MRP components using object oriented method Seunghyun Yoon    2000 
72 IC  INFORMS  A Study on emergency logistics problem after massive natural disaster Sumin Han  Sumin Han  2014 
70 IC  IIE  Development of a Grid-Enabled MRP Process in RFID-Based APS Hyoung-Gon Lee    2007 
69 IC  IFORS  A Closed-loop Supply Chain Coordination Model Considering the Effect of Regulation Alternatives Youngwoo Kim    2011 
68 IC  IFAC on IMS  A Weighted Load Balancing Heuristic that Minimizes Makespan in Alternative Routing and Machine Environment Kidong Kim    1997 
67 IC  IEOM  A Real-time Information System Using RFID for Visually Impaired Kyounghwi Tae    2011 
66 IC  IEOM  Designing an effective scheduling scheme considering multi-level BOM in hybrid job shop Sumin Han    2012 
65 IC  IEOM  Relieving electric power dependency during shortage with an on-site solar power supply CHOE SANG YUN  CHOE SANG YUN  2015 
64 IC  ICUT  A Framework for the Measurement of Supply Chain Performance in Ubiquitous Sensor Network Jaehyun Kong    2007 
63 IC  ICRA  An On-Line Production Scheduler using Neural Network and Simulator based on Manufacturing System State file Kitae Kim    2001 
62 IC  ICQT  A Token Pricing Scheme for Internet Services Dongmyung Lee    2011 
61 IC  ICPR  Business Process Modeling for developing a performance measurement system using the Internet of Things file Gyusun Hwang  Jinwoo Park  2015 
60 IC  ICPR  A Study on FMS Scheduling Problems Based on Priority Functions Generated by Genetic Programming ChangUk Kim    1997 
59 IC  ICPR  A Scheduling Algorithm considering Subcontract cost in MRP Environment Kichang Lee    1997 
58 IC  ICPR  An Algrorithm for Job Shop Scheduling Problem with Due Date Constraints Considering Operation Subcontract Daeyoung Chung    2000 
57 IC  ICPR  Development of a Decision Support System for the formulation of Manufacturing Kichang Lee    2001 
56 IC  ICPR  Combined production and distribution planning using demand based mixed Genetic Algorithm in a supply chain file Sungwon Jung    2003