• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.315-320
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• 2010

Recently, there are environmental issues for sustainable transportation system to pursue the energy-efficient and environment-friendly public urban transit. These transportation system needs to offer demand-oriented high-quality service being on the same level with cab service for urban space. PRT(Personal Rapid Transit), small track-guided vehicle, is repeatedly mentioned as a possible alternative for the new urban public transportion system, but but there are not many researches on the operational optimal routing for PRT network. In this paper, the concept of PRT and general optimal routing methods are reviewed. And we suggest the optimal routing method for city-wide PRT network with multi-vehicles and stations, junctions and directional arcs. Futher research directions for PRT routing are presented.

• Journal of Construction Engineering and Project Management
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• v.4 no.4
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• pp.33-40
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• 2014

Maximizing the profitability and minimizing the duration of construction projects in extreme weather regions is a challenging objective that is essential for project success. An optimization model is presented herein for the time-profit trade-off analysis of construction projects under extreme weather conditions. The model generates optimal/near optimal schedules that maximize profit and minimize the duration of construction projects in extreme weather regions. The computations in the model are organized into: (1) a scheduling module that develops practical schedules for construction projects, (2) a profit module that computes project costs (direct, indirect, and total) and project profit, and (3) a multi-objective module that determines optimal/near optimal trade-offs between project duration and profit. One example is used to show the impact of extreme weather on construction time and profit. Another example is used to show the model's ability to generate optimal trade-offs between the time and profit of construction projects under extreme weather conditions.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.656-657
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• 2015

Recently, Multi-Objective Optimization of design elements is an important issue in building design. Design variables that considering the specificities of the different environments should use the appropriate algorithm on optimization process. The purpose of this study is to compare and analyze the optimal solution using three evolutionary algorithms and energy modeling simulation. This paper consists of three steps: i)Developing three evolutionary algorithm model for optimization of design elements ; ii) Conducting Multi-Objective Optimization based on the developed model ; iii) Conducting comparative analysis of the optimal solution from each of the algorithms. Including Non-dominated Sorted Genetic Algorithm (NSGA-II), Multi-Objective Particle Swarm Optimization (MOPSO) and Random Search were used for optimization. Each algorithm showed similar range of result data. However, the execution speed of the optimization using the algorithm was shown a difference. NSGA-II showed the fastest execution speed. Moreover, the most optimal solution distribution is derived from NSGA-II.

• Journal of Korean Society for Quality Management
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• v.40 no.4
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• pp.441-452
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• 2012

Purpose: In this paper, we have considered a problem of newsvendor model in an environment of random yields in quality and customer balking behavior, in which only the mean and the variance of the demand are known. In practice, the distributional information of the demand is very limited and only the mean and variance are guessed by experience. In addition, due to the customers balking behavior occurring when the available inventory level decreases, the product's demand becomes a function of inventory level so that the classical newsvendor's optimal order quantity is no longer optimal. Methods: We have developed an optimal order quantity model that enables us to incorporate the random yield of a product and the customer balking information such as a threshold inventory level of balking and the corresponding probability of a sale during the balking. Results: We illustrated the concepts developed here through simple numerical examples and showed the robustness of our model in a various setting of parameters. Conclusion: This paper provides a useful analysis showing that our distribution-specific and distribution-free approach to the optimal order quantity in the newsboy model can act as an effective tools to match supply with demand for these product lines.

• Journal of Korean Society for Quality Management
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• v.45 no.2
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• pp.293-306
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• 2017

Purpose: In this study, an optimal design level of influencing factors on semiconductor polishing process was determined to minimize flexion of both sides on wafers. Methods: First, significant interactions are determined by the stepwise regression method. ANOVA analysis on SN ratio and mean of dependent variable are performed to draw mean adjustment factors. In addition, the optimal levels of mean adjustment factors are decided by comparing means of each level of mean adjustment factors. Results: As a result of ANOVA, a mean adjustment factor was determined as a width of formed flexion on the plate. The mean of the difference has the nearest to 0 in the case when the width of formed flexion has level 2 (4mm). Conclusion: Optimal design levels of semiconductor polishing process are determined as follows; (i) load applied to the wafer carrier has a level 1 (3psi), (ii) load applied to the wafer has a level 1(3psi), (iii) the amount of slurry supplied during polishing has a level 3 (300 co/min), (iv) the width of formed flexion on the plate has level 2 (4mm).

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.177-185
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• 2016

In this paper, an optimal planning system for operating transporters in shipyard is developed. The system is designed to utilize the geometries of shipyard, and manage the data of blocks and transporters directly. There are four major menus such as shipyard map management based on GIS, block transportation request, transporter management, and optimal transportation planning in the system. The geometries and properties of the shops, roads, and addresses are manipulated in the shipyard map management menu. The block transportation requests and the properties of transporters are managed in the block transportation request and transporter management menus, respectively. The optimum transportation is planned automatically for minimizing the unload times of the transporters, and the optimum transportation plans are confirmed and printed to the transporter drivers. The effectiveness of the system was verified through the application to a large-sized shipyard.

• Korean Management Science Review
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• v.31 no.3
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• pp.61-76
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• 2014

There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

• Journal of Applied Reliability
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• v.17 no.3
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• pp.246-255
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• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.135-140
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• 2012

Fuel Cell Hybrid Vehicles (FCHVs) have already become the subject of major interest among automotive industry as well as power management strategies of FCHVs, as the fuel economy of FCHVs depends on them. There are several types of power management strategies of FCHVs that have been developed to improve the fuel economy of FCHVs. Among them, optimal control theory is applied to this study. A problem is defined and its objective is to minimize the energy consumption of an FCHV and to find the optimal trajectories of powertrain parameters during driving. Necessary conditions for the optimal control are introduced and the simulation results of constant costate are compared to that of variable costate in order to prove that the variable costate can be replaced with the constant costate.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.69-86
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• 2020

Purpose: This study aims to determine the optimal conditions for the spot welding process that mechanically connects the case of a cylindrical secondary battery and the negative tab. Methods: We use 33 factorial design to derive the optimal conditions for the spot welding process. The pulling strength, the cross-sectional area of nugget, and the shock test life are selected as response variables, which can represent the resistance welding quality. The input variables are selected as the welding time, welding voltage, and pressure, which are the controllable factors in the spot welding process. Results: The main effects of welding time and welding voltage and the interaction effect of welding time and welding voltage are significant. Conclusion: The optimal conditions for the spot welding process to mechanically join the negative electrode tab of the cylindrical secondary battery and the battery case are developed. The result shows that the pulling strength is increased by 44% compared to before improvement under optimal conditions.