• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2451-2460
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• 2000

In order to minimize straightness error of deflected shaft, a geometric adaptive straightness controller system is studied. A multi-step straightening and a three-point bending process have been developed for the geometric adaptive straightness controller. Load-deflection relationship, on-line identification of variations of material properties, on-line springback prediction, and real-time hydraulic control methodology are studied for the three-point bending process. By deflection pattern analysis and fuzzy self-learning method in the multi-step straightening process, a straightening point and direction, desired permanent deflection and supporting condition are determined. An automatic straightening machine has been fabricated for rack bars by using the developed ideas. Validity of the proposed system is verified through experiments.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.6
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• pp.589-593
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• 2013

An efficient measurement methodology is proposed to construct the scattering parameters of a multi-port device using a four-port vector network analyzer (VNA) without the external un-terminated ports. By using the four-port VNA, the reflected waves from the un-terminated ports could be minimized. The proposed method significantly enhances the accuracy of the S-parameters with less number of measurements compared to the results of classical renormalization technique which uses two-port VNA. The proposed method is validated from the measured data with the coupled 8-port micro-strip lines.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.124-131
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• 2000

A shop floor can be considered as and importand level to develop a Computer Integrated Manufacturing system (CIMs). The shop foor is a dynamic environment where unexpected events contrinuously occur, and impose changes to planned activities. The shop floor should adopt an appropriate control system that is responsible for scheduling coordination and moving the manufacturing material and information flow. In this paper, the architecture of the hybrid control model identifies three levels; i.e., the shop floor controller (SFC), the cell controller(CC) and the equipment controller (EC). The methodology for developing these controller is employ an object-oriented approach for static models and IDEF0 for function models for dispatching a job. SFC and CC are coordinated by employing a multi-factors bidding and an adapted Analytic Hierarchy Process(AHP) prove applicability of the suggested method. Test experiment has been conducted by with the shopfloor, consisting of six manufacturing cells.

• Advances in Computational Design
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• v.2 no.3
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• pp.241-256
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• 2017

This paper introduces the process for Multi-objective Optimization Framework (MOF) which mediates multiple conflicting design targets. Even though the extensive researches have shown the benefits of optimization in engineering and design disciplines, most optimizations have been limited to the performance-related targets or the single-objective optimization which seek optimum solution within one design parameter. In design practice, however, designers should consider the multiple parameters whose resultant purposes are conflicting. The MOF is a BIM-integrated and simulation-based parametric workflow capable of optimizing the configuration of building components by using performance and non-performance driven measure to satisfy requirements including build programs, climate-based daylighting, occupant's experience, construction cost and etc. The MOF will generate, evaluate all different possible configurations within the predefined each parameter, present the most optimized set of solution, and then feed BIM environment to minimize data loss across software platform. This paper illustrates how Multi-objective optimization methodology can be utilized in design practice by integrating advanced simulation, optimization algorithm and BIM.

• Journal of Distribution Science
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• v.13 no.10
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• pp.15-21
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• 2015

Purpose - This study examines a bundling effect on production and distribution in a patent-protected industry. Despite the heavy use of bundling strategies in the information and technology industry, literature has paid scant attention to bundling of intellectual property rights. This study examines a theoretical exploration of the bundling effect on licensing behavior. Research design, data, and methodology - To address this behavior, we build a simplified model consisting of three stages: 1) bundling decision, 2) licensing agreement, and 3) competition. The subgame perfect Nash equilibrium is applied to the model. Results - A single-patent holder with superior technology grants its own license to the multiple-patent firm, thereby leaving the market. Anticipating the single right holder's licensing strategy, the multiple-patent firm offers a bundle, making the single-right holder's bargaining position weaker. Conclusions - Bundling is an effective business strategy, resulting in multiple products for a firm as it faces other firms with single-product lines in each market. Taking advantage of the multi-patent or multi-product lines, the firm utilizes the bundling strategy obtaining better technology from the standalone single-patent firms.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.225-228
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• 2007

This paper presents a geostatistical methodology to model local uncertainty in spatial estimation of sediment grain size with high-resolution remote sensing imagery. Within a multi-Gaussian framework, the IKONOS imagery is used as local means both to estimate the grain size values and to model local uncertainty at unsample locations. A conditional cumulative distribution function (ccdf) at any locations is defined by mean and variance values which can be estimated by multi-Gaussian kriging with local means. Two ccdf statistics including condition variance and interquartile range are used here as measures of local uncertainty and are compared through a cross validation analysis. In addition to local uncertainty measures, the probabilities of not exceeding or exceeding any grain size value at any locations are retrieved and mapped from the local ccdf models. A case study of Baramarae beach, Korea is carried out to illustrate the potential of geostatistical uncertainty modeling.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.5 s.182
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• pp.93-102
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• 2006

This paper proposes a controller design analysis for three-axis CNC systems considering both contouring and tracking performance. The proposed analysis inclusively combines axial controllers for each individual feed drive system together with cross-coupling controller at the beginning design stage as an integrated manner. These two controllers used to be separately designed and analyzed since they have different control objectives. The proposed scheme includes a stability analysis for the overall control system and a performance analysis in terms of contouring and tracking accuracy. Computer simulation is performed and the results show the validity of the proposed methodology. Further, the results can be used as a basic guideline in systematic and comprehensive controller design for multi-axis CNC systems.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.195-196
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• 2010

This study aims to methodology a system which is able to monitoring and analysis of long span bridge in real time using multi GPS. Through setting up many GPS at the important points of long span bridge and measuring displacement in real time, over all 3D configuration of bridge could be analyzed. Behavior analyzing system developed in this study is able to digitize and visualize the overall and points displacement of bridge and deal with events actively. Also it is able to calculate statistical data related to analyze behavior through the constricting database of measuring data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.463-468
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• 2002

Recently, a multi-facility, multi-product and multi-period industrial problem has been widely investigated in Supply Chain Management(SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. We have developed an optimization model to tackle the above problems under the restricted conditions such as transportation time and a zero inventory. The model can be used to deride an appropriate factory and assign an optimal output the factory yields. This paper deals with the main idea of the proposed methodology in depth.

• Korean Management Science Review
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• v.24 no.2
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• pp.73-80
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• 2007

Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.