• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.450-457
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• 2018

The determination of assembly sequence in general mechanical assemblies plays an important role in terms of manufacturing cost, duration and quality. In the production of ships and offshore plants, the consideration of productivity factors and welding deformation is crucial in determining the optimal assembly sequence. In shipbuilding and offshore industries, most assembly sequence planning has been done according to engineers' decisions based on extensive experience. This may result in error-prone planning and sub-optimal sequence, especially when dealing with unfamiliar block assemblies composed of dozens of parts. This paper presents an assembly sequence planning method for block assemblies. The proposed method basically considers geometric characteristics of blocks to determine feasible assembly sequences, as well as assembly process and productivity factors. Then the assembly sequence with minimal welding deformation is selected based on simplified welding distortion analysis. The method is validated using an asymmetric assembly model and the results indicate that it is capable of generating an optimal assembly sequence.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1911-1919
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• 2012

In this paper, we focus on a robotic sealing process in which three robots are used. Each robot can be considered as a 7 axis redundant robot of which the first joint is prismatic and the last 6 joints are revolute. In the factory floor, robot path planning is not a simple problem and is not automated. They need experienced operators who can operate robots by teaching and playing back fashion. However, the robotic sealing process is well organized so the relative positions and orientations of the objects in the floor and robot paths are all pre-determined. Therefore by adopting robotic theory, we can optimally plan robot pathes without using teaching. In this paper, we analyze the sealing robot by using redundant manipulator theory and propose three different methods for path planning. For sealing paths outside of a car body, we propose two methods. The first one is resolving redundancy by using pseudo-inverse of Jacobian and the second one is by using weighted pseudo-inverse of Jacobian. The former is optimal in the sense of energy and the latter is optimal in the sense of manipulability. For sealing paths inside of a car body, we must consider collision avoidance so we propose a performance index for that purpose and a method for optimizing that performance index. We show by simulation that the proposed method can avoid collision with faithfully following the given end effector path.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.14-20
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• 1998

Cutting fluid is a factor which has big effects on both machinability and environment in machining process. The loss of cutting fluids may be reduced by the optimization of machining parameters in process planning. In this study, the environmental impact of fluid loss is analyzed. The fluid loss models in milling process are constructed with the machining parameters. The models are utilized to obtain the optimal machining parameters to minimize the fluid loss. The factors with significant effects on the fluid loss are analyzed by ANOVA test. Finally, optimal parameters are suggested considering both machining economics and environmental impact. This study is expected to be used as a part of a framework for the environmental impact assessment of machining process.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1163-1168
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• 2006

Manufacturing technology for the production of high value-added fine chemical products is emphasized and getting more attention as the diversified interests of customers and the demand of high quality products are getting bigger and bigger everyday. Thus, the development of advanced batch processes, which is the preferred and most appropriate way of producing these types of products, and the related technologies are becoming more important. Therefore, high-precision batch distillation is one of the important elements in the successful manufacturing of fine chemicals, and the importance of the process operation strategy with quality assurance cannot be overemphasized. Accordingly, proposing a process structure explanation and operation strategy of such processes including batch processes and batch distillation would be of great value. We investigate optimal operation strategy and production planning of multi-purpose plants consisting of batch processes and batch distillation for the manufacturing of fine chemical products. For the short-term scheduling of a sequential multi-purpose batch plant consisting of batch distillation under MPC and UIS policy, we proposed a MILP model based on a priori time slot allocation. Also, we consider that the waste product of being produced on batch distillation is recycled to the batch distillation unit for the saving of raw materials. The developed methodology will be especially useful for the design and optimal operations of multi-purpose and multiproduct plants that is suitable for fine chemical production.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.790-793
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• 2008

Recently, Intelligent Excavating System(IES) for earthwork automation is on progress since the end of 2006 as a part of construction technology innovation projects in Ministry of Land, Transport and Maritime Affairs. Task Planning System(TPS), one of the detail core technologies of IES, is an optimal work planning system in conditions of effectiveness, safety and economic efficiency by analyzing the work environment data based on earthwork design and work environment recognition technology. For effective earthwork planning, the location of platform must be the most optimal spot for minimization of time, maximization of productivity and reduction of overlapped work spaces and unnecessariness. Besides, the decision of optimal platform location is to be based on the specifications and then is able to be converted with the local area calculation algorithm. This study explains the decision of optimal platform location on the basis of local area from the work space separate process and judges the effectiveness.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.298-306
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• 2013

Nowadays, a transporter manager plans the schedule of the block transportation by considering the experience of the manager, the production process of the blocks and the priority of the block transportation in shipyard. The schedule planning of the block transportation should be rearranged for the reflection of the path blocking cases occurred by unexpected obstacles or delays in transportation. In this paper, the optimal block transportation path planning system is developed for rearranging the schedule of the block transportation by considering the damaged path. $A^*$ algorithm is applied to calculate the new shortest path between the departure and arrival of the blocks transported through the damaged path. In this algorithm, the first node of the damaged path is considered as the starting position of the new shortest path, and then the shortest path calculation is completed if the new shortest path is connected to the one of nodes in the original path. In addition, the data structure for the algorithm is designed. This optimal block transportation path planning system is applied to the Philippine Subic shipyard and the ability of the rapid path modification is verified.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• Journal of Ocean Engineering and Technology
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• v.37 no.3
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• pp.122-128
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• 2023

Autonomous berthing is a crucial technology for autonomous ships, requiring optimal trajectory planning to prevent collisions and minimize time and control efforts. This paper presents a two-phase, two-point boundary value problem (TPBVP) strategy for creating an optimal berthing trajectory for a twin-propeller, twin-rudder ship with autonomous berthing capabilities. The process is divided into two phases: the approach and the terminal. Tunnel thruster use is limited during the approach but fully employed during the terminal phase. This strategy permits concurrent optimization of the total trajectory duration, individual phase trajectories, and phase transition time. The efficacy of the proposed method is validated through two simulations. The first explores a scenario with phase transition, and the second generates a trajectory relying solely on the approach phase. The results affirm our algorithm's effectiveness in deciding transition necessity, identifying optimal transition timing, and optimizing the trajectory accordingly. The proposed two-phase TPBVP approach holds significant implications for advancements in autonomous ship navigation, enhancing safety and efficiency in berthing operations.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.