• Journal of Computational Design and Engineering
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• v.1 no.2
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• pp.140-151
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• 2014

Storing, and the loading and unloading of materials at production sites in the manufacturing sector for mass production is a critical problem that affects various aspects: the layout of the factory, line-side space, logistics, workers' work paths and ease of work, automatic procurement of components, and transfer and supply. Traditionally, the nesting problem has been an issue to improve the efficiency of raw materials; further, research into mainly 2D optimization has progressed. Also, recently, research into the expanded usage of 3D models to implement packing optimization has been actively carried out. Nevertheless, packing algorithms using 3D models are not widely used in practice, due to the large decrease in efficiency, owing to the complexity and excessive computational time. In this paper, the problem of efficiently loading and unloading freeform 3D objects into a given container has been solved, by considering the 3D form, ease of loading and unloading, and packing density. For this reason, a Group Packing Approach for workers has been developed, by using analyzed truck packing work patterns and Group Technology, which is to enhance the efficiency of storage in the manufacturing sector. Also, an algorithm for 3D packing has been developed, and implemented in a commercial 3D CAD modeling system. The 3D packing method consists of a grouping algorithm, a sequencing algorithm, an orientating algorithm, and a loading algorithm. These algorithms concern the respective aspects: the packing order, orientation decisions of parts, collision checking among parts and processing, position decisions of parts, efficiency verification, and loading and unloading simulation. Storage optimization and examination of the ease of loading and unloading are possible, and various kinds of engineering analysis, such as work performance analysis, are facilitated through the intelligent 3D packing method developed in this paper, by using the results of the 3D model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12C
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• pp.1135-1142
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• 2006

This article presents a new asynchronous MC-CDMA system to implement multiple data rate communications. In a W-CDMA downlink, the OVSF code is used for spreading code for various multimedia traffic. Proposed system utilizes the OVSF code that generated by generation property for spreading. The proposed MC-CDMA system use different lengths of OVSF code as a spreading code according to their data rate. The groupwise processing is accomplished by code grouping in OVSF code generation tree. Between each group, the code grouping interference canceller is performed to cancel other group interference. At that time the proposed receiver does not require any information about interference users. For the analysis of average BER performance, we propose system model and computer simulation were used. We also compare the system performance with that of a single rate MC-CDMA system used orthogonal code as a spreading code.

• Nuclear Engineering and Technology
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• v.27 no.5
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• pp.743-752
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• 1995

This paper investigates the effects of fuel groupings in the coupled internals and core model on the internals and fuel responses due to pipe breaks. The 177 fuel assemblies for Korean standard nuclear power plant are grouped into several stick models and the responses of internals components are calculated. The analysis results show that the fuel model groupings in the coupled internals and core model have no significant effects on the internals and fuel responses for pipe break excitation. Also, in order to determine the feasibility of constructing a single equivalent stick representation of In or more adjacent fuel bundles, the reduced models, each of which employs a different stiffness lumping rule, are constructed. It is shown that the equivalent stiffness calculated to get the first natural frequency of the original model while preserving net gap between grouping centers gives the minimum modelling error.

• Journal of the Korean Statistical Society
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• v.14 no.2
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• pp.63-75
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• 1985

This paper considers a statistical calibration problem in which the standard as wel as the nonstandard measurement is subject to error. Since the classicla approach cannot handle this situation properly, a functional relationship model with additional feature of prediction is proposed. For the analysis of the problem four different approaches-two estimation techniques (ordinary and grouping least squares) combined with two prediction methods (classical and inverse prediction)-are considered. By Monte Carlo simulation the perromance of each approach is assessed in term of the probability of concentration. The simulation results indicate that the ordinary least squares with inverse prediction is generally preferred in interpolation while the grouping least squares with classical prediction turns out to be better in extrapolation.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.145-156
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• 1998

In a classical clustering problem, grouping is done on the basis of similarities or distances (dissimilarities) among the elements. Therefore, the objective is to minimize the variance within each group while maximizing the between-group variance among all groups. In this paper, however, a new class of clustering problem is introduced. We call this a laydown grouping problem (LGP). In LGP, the objective is to minimize both the within-group and between-group variances. Furthermore, the problem is expanded to a multi-dimensional case where the two-way minimization process must be considered for each dimension simultaneously for all measurement characteristics. At first, the problem is assessed by analyzing its variance structures and their complexities by conjecturing that LGP is NP-complete. Then, the simulated annealing (SA) algorithm is applied and the results are compared against that from others.

• Proceedings of the Korea Society of Costume Conference
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• 2003.10a
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• pp.68-68
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• 2003

Recently, street fashion has been regularly introduced in many fashion media because both consumers and marketers began to recognize the importance of street fashion as a meaningful and objective fashion information source. As the globalization proceeds in fashion field,' the street fashion informations in major cities which has led world fashion trends become more influential on domestic fashion, but little concern has been paid on it. This study classified women's street fashion in 4 major world fashion cities such as Paris, London, New York, Tokyo and identified style characteristics of each group. For data collection, 795 front-view photos were selected from the two fashion trade publication 'STREET' and 'VIEW' which has introduced street fashion photos in those cities from 1996. Classification process went on three stages: sorting, naming and grouping. 49 undergraduate students were divided into 12 teams and about 80 photos were given to each team to sort into several sub-groups by overall images or common style characteristics. Then each sub-group was named according to common images or characteristics. Final groups came out after grouping each sub-group with a similar or same title together. For each group, common style characteristics were analyzed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.341-343
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• 2012

This study introduces a method for computation of process and operation gap in the specific construction operation(i.e., RC frame construction applying a block-grouping scheme) using CYCLONE-based simulation modeling and analysis technique. Since uncertainty of construction environment exists, a thoughtful production planning is required to effectively deal with a risk resulting in schedule delay in advance. This study presents the concepts of a time delay occurred in a process level and operation level in a operation model, and a method of measuring gap-times in each level while the simulation progresses. It helps a site manager to decide how many segmentation in a construction block is suitable for eliminating unproductive time-delays under the constrained resources (e.g., laborer, equipment). A case study presents a network model representing a three segmented RC frame work, and result obtained from the simulation experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.780-783
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• 2002

This paper proposes an approximate LCA methodology fur the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes Into impact driver (ID) index. The relationship Is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then an artificial neural network model is developed to predict an approximate LCA of grouping products in conceptual design stage. The training is generalized by using identified product attributes for an ID In a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give an approximate LCA results for design concepts.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.172-179
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• 2001

A component based method out of load modeling is to aggregate component load model according to the composition rate of each component load at load bus based on the circuit theory. But the most of component loads respond complex nonlinear characteristics respect to voltage and frequency variation due to the control techniques and semiconductor elements applied to component load. It needs to verify this approach through actual experiment of the aggregation of component load even if it can be down. To identify this aggregation method well known, this paper is proposed the classifying method of component load characteristics for component loads to group by quantitative analysis. The component load characteristics were divided into several types by KSOM (kohonen self organizing map), which can classify multi-dimension vector, component load pattern, into two-dimension vector. Some ambiguous cases happened from KSOM were classified by the proposed closing degree.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.143-154
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• 2000

In port management, the scale of facilities and port layouts are major factors characterizing the port, which influence port economics and productivities continuously through the port operation. Grouping ports in certain region by their characteristics could be used as the principal informations to establish national policy for port development or investment and also to analyze the competitiveness between ports. Currently Korean ports are divided into two groups such as the local port and the designated port containing foreign trade port and coastal port under the Korean port law. These divisions seem to be used for port administration as the matter of convenience but some qualitative grouping is needed for research of port problems. In this paper, 20 major Korean ports were clustered by the similar characteristics using Fuzzy C-Means and found to be classified 8 qualitative groups.