• Journal of Korea Planning Association
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• v.54 no.5
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• pp.129-138
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• 2019

This study aims to empirically examine the relationship between building energy consumption and building and local factors in Seoul. Building energy issue is an important topic for low carbon and eco-friendly city development. Building physical, socio-economic and environmental factors effect to increasing or decreasing energy consumption. However, there are different characteristic in each area, and this kind of variable has a hierarchical structure. The multi-level model was used to consider the hierarchical structure of the variables. In this study, a multi-level model was applied to confirm the difference between areas. Spatial area is Seoul, Korea and the temporal scope is August, summer season. As the result, in Model 1 (Null Model), ICC is 0.817. This shows that the energy consumption differs by 8.174% due to factors at the Dong level. Model 2 (Random Intercept Model) suggests that building's physical factors and Average age, Household size and Land price in Dong level have significant effects on Building energy consumption. In Model 3 (Random Coefficient Model), random effect variables have intercepts and slopes to vary across groups. This study provides a perspective for policy makers that the building energy reduction policies to be applied for buildings should be differently applied on area. Furthermore, not only physical factors but also socio-economic and environmental factors are important when making energy reduction policy.

• Korean Journal of Computational Design and Engineering
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• v.14 no.1
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• pp.60-68
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• 2009

Because of the reduced product life-cycle, industries are making an effort to bring down the process planning time. In the traditional approach, we have to analyze established process planning, then design the time chart based on process information and drawing the formal time chart such as SOP(sequence of operation). Thereafter, it will be converted to PLC code that is a time consuming and redundant job. Similarly, Industrial automated process uses PLC Code to control the factory; however, control information and control code(PLC code) are difficult to understand. Hence, industries prefer writing new control code instead of using the existing one. It shows the lack of information reusability in the existing process planning. As a result, to reduce this redundancy and lack of reusability, we propose SOS-Net modeling method. Unlike past stabilized process planning that is rigid to any change; our proposed SOS-Net modeling method is more adaptable to the new changes. The SOS-Net model is easy to understand and easy to convert into PLC Code accordingly. Therefore, we can easily modify the control information and reuse it for new process planning. The proposed model plays an intermediary role between process planning and PLC code generation. It can reduce the process planning and implementation time as well as cost.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.595-598
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• 2002

Laser scanners are getting used more and more in reverse engineering and inspection. For CNC-driven laser scanners, it is important to automate the scanning operations to improve the accuracy of capture point data and to reduce scanning time in industry. However, there are few research works on laser scan planning system. In addition, it is difficult to directly analyze multi-patched freeform models. In this paper, we propose an STL (Stereolithography) mesh based laser scan planning system for complex freeform surfaces. The scan planning system consists of three steps and it is assumed that the CAD model of the part exists. Firstly, the surface model is approximated into STL meshes. From the mesh model, normal vector of each node point is estimated. Second, scan directions and regions are determined through the region growing method. Also, scan paths are generated by calculating the minimum-bounding rectangle of points that can be scanned in each scan direction. Finally, the generated scan directions and paths are validated by checking optical constraints and the collision between the laser probe and the part to be scanned.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.33-40
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• 2000

In this paper, an integrated method for the path planning and motion control of wheeled mobile robots using a hybrid system model and control is presented. The hybrid model including the continuous dynamics and discrete dynamics with the continuous and discrete state vector is derived for a two wheel driven mobile robot. The architecture of the hybrid control system for real time path planning and following is designed which has the 3-layered hierarchical structure : the discrete event system using the digital automata as the higher process, the continuous state system for the wheel velocity controls as the lower process, and the interface system as the interaction process between the continuous system as the low level and the discrete event system as the high level. The reference motion commands for autonomous navigation are generated by the abstracted motion in the discrete event system. The motion control tasks including the feasible path planning and autonomous motion control with various initial conditions are investigated as the applications by the simulation studies.

• Journal of Navigation and Port Research
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• v.45 no.5
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• pp.231-237
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• 2021

Enhancing the performance of maritime wireless communication has been highlighted by the issue of cell planning in the sea area because of lack of an appropriate Propagation Loss Model (PLM). To resolve the cell planning issue in vast sea areas, it was essential to develop the (PLM) matching the intended sea area. However, there were considerable gaps between the prediction of legacy PLMs and field measurement in propagation loss and there was a need to develop the adjusted PLM (A-PLM). Therefore, cell planning was performed on this adjusted model, including modification of the base station's location, altitude, and antenna azimuth to meet the quality objectives. Furthermore, in order to verify the availability of the cell planning, Communication Service Quality Monitoring System (CS-QMS) was developed in the LTE-Maritime project to collect LTE signal quality information from the onboard equipment at regular intervals and to ensure that the service quality was high enough to satisfy the goals in each designated grid. As a result of verification, the success rate of RSRP was 95.7% for the intensive management zone (IMZ) and 96.4% for the interested zone (IZ), respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.77-90
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• 2009

Total profit level Increases if a company increase the cost for achieving R&D related goals of equipment productivity enhancement, production cost saving, or for achieving equipment scale target, sales volume goal. But how much money should be invested to achieve a certain level of profit? We formulated the model to set the optimal goal levels to minimize the investment cost under the constraint that certain level of total profit should be guaranteed. This model derived from a case of P steel company. We found that this should be considered in relation with the production sales planning (known as optimal product mix problem) to guarantee the profit. We suggested a nonlinear programming model, 3 valiant form of the p+roduct mix problem. We can find the optimal Investment level for the R&D related goals or sales volume goal, equipment scale target for the P steel company using the model.

• Journal of the Korea Safety Management & Science
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• v.11 no.4
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• pp.193-199
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• 2009

Recently, an industrial production-distribution planning problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area is reverse logistics network. This study have developed a simulation model for the reverse logistics network. The simulation model analysis reverse logistics network issues such as inventory policy, manufacturing policy, transportation mode, warehouse assignment, supplier assignment. Computational experiments using commercial simulation tool ARENA show that the real problems. The model can be used to decide an appropriate production-distribution planning problem in the research area.

• IE interfaces
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• v.13 no.3
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• pp.512-520
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• 2000

An integrated process planning and scheduling model considering outsourcing in manufacturing supply chain is proposed in this paper. The process planning and scheduling considering outsourcing are actually interrelated and should be solved simultaneously. The proposed model considers the alternative process plans for job types, precedence constraints of job operations, due date of production, transportation time and production information for outsourcing. The integrated states include:(1) Operations sequencing, (2) Machine selection, (3) Scheduling with outsourcing under the due date. To solve the model, a heuristic approach based on genetic algorithm(GA) is developed. The proposed approach minimizes the makespan considering outsourcing and shows the best operation-sequences and schedule of all jobs.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.113-125
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• 2008

This paper presents a model for designing cellular manufacturing systems (CMS) by integrating system cost, machine reliability, and preventive maintenance (PM) planning. In a CMS, a part is processed using alternative process routes, each consisting of a sequence of visits to machines. Thus, a level of 'system reliability' is associated with the machines along the process route assigned to a part type. Assuming machine reliabilities to follow the Weibull distribution, the model assigns the machines to cells, and selects, for each part type, a process route which maximizes the overall system reliability and minimizes the total costs of manufacturing operations, machine underutilization, and inter-cell material handling. The model also incorporates a reliability based PM plan and an algorithm to implement the plan. The algorithm determines effective PM intervals for the CMS machines based on a group maintenance policy and thus minimizes the maintenance costs subject to acceptable machine reliability thresholds. The model is a large mixed integer linear program, and is solved using LINGO. The results point out that integrating PM in the CMS design improves the overall system reliability markedly, and reduces the total costs significantly.