• Geomechanics and Engineering
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• v.18 no.3
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• pp.225-234
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• 2019

A numerical stepwise approach for cavity expansion problem in strain-softening rock or soil mass is investigated, which is compatible with Mohr-Coulomb and generalized Hoek-Brown failure criteria. Based on finite difference method, plastic region is divided into a finite number of concentric rings whose thicknesses are determined internally to satisfy the equilibrium and compatibility equations, the material parameters of the rock or soil mass are assumed to be the same in each ring. For the strain-softening behavior, the strength parameters are assumed to be a linear function of deviatoric plastic strain (${\gamma}p^*$) for each ring. Increments of stress and strain for each ring are calculated with the finite difference method. Assumptions of large-strain for soil mass and small-strain for rock mass are adopted, respectively. A new numerical stepwise approach for limited pressure and plastic radius are obtained. Comparisons are conducted to validate the correctness of the proposed approach with Vesic's solution (1972). The results show that the perfectly elasto-plastic model may underestimate the displacement and stresses in cavity expansion than strain-softening coefficient considered. The results of limit expansion pressure based on the generalised H-B failure criterion are less than those obtained based on the M-C failure criterion.

• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.83-93
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• 2009

This study proposes a stepwise approach to product safety management(PSM), of which roadmap consists of five phases. ISO 9001 QM model is assumed as the first-phase model and each higher-phase model is built by adding a corresponding module to the lower one. In the phase order, those modules are CCMS, a failure to warn, manufacturing defect and design defect. The progress in PSM of a domestic food company is discussed.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.6
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• pp.628-641
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• 2014

Stepwise efficiency improvement in data envelopment analysis (DEA)-based benchmarking is a realistic and effective method by which inefficient decision making units (DMUs) can choose benchmarks in a stepwise manner and, thereby, effect gradual performance improvement. Most of the previous research relevant to stepwise efficiency improvement has focused primarily on how to stratify DMUs into multiple layers and how to select immediate benchmark targets in leading levels for lagging-level DMUs. It can be said that the sequence of benchmark targets was constructed in a myopic way, which can limit its effectiveness. To address this issue, this paper proposes an optimization approach to the construction of a sequence of benchmarks in DEA-based benchmarking, wherein two optimization criteria are employed : similarity of input-output use patterns, and proximity of input-output use levels between DMUs. To illustrate the proposed method, we applied it to the benchmarking of 23 national universities in South Korea.

• 한국연소학회:학술대회논문집
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• 2015.12a
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• pp.77-78
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• 2015

Laminar burning velocities have been predicted by constant volume combustion chamber, counter flow burner and others. In this study, the measured flame propagation velocities in an assembled annular stepwise diverging tube were plotted with respect to equivalence ratio, length scale, and velocity scale. Three dimensional approach to understand the flame propagation velocity including laminar burning velocity is investigated, and the surface provides the correlation among quenching distance, propagation velocity, and equivalence ratio.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.17-26
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• 2018

Purpose - The purpose of this study is to provide a formalized process of decision making for companies or organizations that need to make various decisions in the age of uncertainty. Therefore, this study aimed to proposes a strategic decision-making approach citing the relatively easily accessible using IPA(important-performance analysis) and SWOT/AHP analysis. Research design, data, and methodology - To be specific, the first step is to derive necessary attributes and conduct IPA. The second step is to subdivide the IPA results into internal strength and weakness factors and the external opportunity and threat factors, hierarchize those factors, and weight them accordingly. The third step is to build a causality model to propose a method of supporting a rational decision making. Results - The foregoing approach seems to facilitate the diversification of decision-making strategies by helping businesses or organizations to measure and analyze the attributes needed for certain decisions. Additionally, the perceived importance and satisfaction (or achievement) usage of those derived attributes can be used as the reference data for SWOT/AHP analysis. Conclusions - The proposed stepwise approach is applicable to businesses or organizations in need of making stepwise decisions in line with their retained competencies in comparison to conventional or intuitive decision-making practices.

• Korean Journal of Computational Design and Engineering
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• v.6 no.3
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• pp.157-168
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• 2001

The description of enterprise activities is the basis fur process improvement and information system building. To describe such activities, it is necessary to model the enterprise activities from the abstraction level to the implementation level in a stepwise and integrated form. For this reason, several modeling approaches have been proposed. However, most of them lacked the stepwise or integration aspects although some of them covered overall levels. This study proposes the hierarchical modeling approach for integrating the enterprise activity model from the abstraction level to the implementation level systematically. It is composed of five modeling levels such as function level, process level, task level, document workflow level, and event flow level. This study discusses the definition and characteristics of each level and compare our modeling frame with other modeling methodologies in case study.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.33-46
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• 2019

Purpose: This study proposed a DEA (Data Envelopment Analysis)-based stepwise benchmarking target selection for inefficient DMU (Decision Making Unit) to improve its efficiency gradually to reach most efficient frontier considering resource (DEA inputs and outputs) improvement preferences. Methods: The proposed method proceeded in two steps. First step evaluates efficiency of DMUs by using DEA, and an evaluated DMU selects benchmarking targets of HCU (Hypothesis Composit Unit) or RU (Real Unit) considering resource improvement preferences. Second step selects stepwise benchmarking targets of the inefficient DMU. To achieve this, this study developed a new DEA model, which can select a benchmarking target of an inefficient DMU in considering inputs or outputs improvement preference, and suggested an algorithm, which can select stepwise benchmarking targets of the inefficient DMU. Results: The proposed method was applied to 34 international ports for validation. In efficiency evaluation, five ports was evaluated as most efficient port, and the remaining 29 ports was evaluated as relative inefficient port. When port 34 was supposed as evaluated DMU, its can select its four stepwise benchmarking targets in assigning the preference weight to inputs (berth length, total area of pier, CFS, number of loading machine) as (0.82, 1.00, 0.41, 0.00). Conclusion: For the validation of the proposed method, it applied to the 34 major ports around the world and selected stepwise benchmarking targets for an inefficient port to improve its efficiency gradually. We can say that the proposed method enables for inefficient DMU to establish more effective and practical benchmarking strategy than the conventional DEA because it considers the resource (inputs or outputs) improvement preference in selecting benchmarking targets gradually.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2017.05a
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• pp.131-132
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• 2017

• International Commerce and Information Review
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• v.8 no.1
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• pp.69-86
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• 2006

The trade volume between South and North Korea has reached 1 billion dollars in year 2005. This means the economic motives may prevail over the political concerns between two regimes from now on. At the same time, the direct telecommunication lines installed to promote the IT collaboration. Based on these monumental issues, the research focuses on the workable mechanism of the South-North Korean e-Market Place(e-MP) collaboration project. The research analyzes on the capabilities as well as willingness of the South and North Korea for the e-MP, and concludes with four stepwise approach to promote the South and North Korean e-MP. The first step initiates the web marketing integration, and then the second step provides the legal environments. The third step promotes the on-/off- trade-automation via infrastructure collaboration, and the final step expands and deepens the flexibility as well as openness of the e-MP.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.64-79
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• 2017

Identifying disease genes from human genome is a critical task in biomedical research. Important biological features to distinguish the disease genes from the non-disease genes have been mainly selected based on traditional feature selection approaches. However, the traditional feature selection approaches unnecessarily consider many unimportant biological features. As a result, although some of the existing classification techniques have been applied to disease gene identification, the prediction performance was not satisfactory. A small set of the most important biological features can enhance the accuracy of disease gene identification, as well as provide potentially useful knowledge for biologists or clinicians, who can further investigate the selected biological features as well as the potential disease genes. In this paper, we propose a new stepwise random forests (SRF) approach for biological feature selection and disease gene identification. The SRF approach consists of two stages. In the first stage, only important biological features are iteratively selected in a forward selection manner based on one-dimensional random forest regression, where the updated residual vector is considered as the current response vector. We can then determine a small set of important biological features. In the second stage, random forests classification with regard to the selected biological features is applied to identify disease genes. Our extensive experiments show that the proposed SRF approach outperforms the existing feature selection and classification techniques in terms of biological feature selection and disease gene identification.