• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.18-27
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• 2019

The process control methods based on the statistical analysis apply the analysis method or mathematical model under the assumption that the process characteristic is normally distributed. However, the distribution of data collected by the automatic measurement system in real time is often not followed by normal distribution. As the statistical analysis tools, the process capability index (PCI) has been used a lot as a measure of process capability analysis in the production site. However, PCI has been usually used without checking the normality test for the process data. Even though the normality assumption is violated, if the analysis method under the assumption of the normal distribution is performed, this will be an incorrect result and take a wrong action. When the normality assumption is violated, we can transform the non-normal data into the normal data by using an appropriate normal transformation method. There are various methods of the normal transformation. In this paper, we consider the Box-Cox transformation among them. Hence, the purpose of the study is to expand the analysis method for the multivariate process capability index using Box-Cox transformation. This study proposes the multivariate process capability index to be able to use according to both methodologies whether data is normally distributed or not. Through the computational examples, we compare and discuss the multivariate process capability index between before and after Box-Cox transformation when the process data is not normally distributed.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.5
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• pp.51-55
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• 2002

This paper presents a systematic methodology and formulation for determining optimal strategies of multi-body dynamic systems, which is based on multi-body dynamics, design sensitivity, and optimization techniques, and is applicable to a wide variety of mechanical systems. The particular application discussed in this paper considers a vehicle model with four-wheel steeling capability, and the presented methodology determines an optimal steering angle ratio strategy for the vehicle. It is shown that such a strategy can improve the ride stability of the vehicle, during a variety of maneuvers, when compared against similar strategies obtained from linear and simplified vehicle models.

• Journal of Mechanical Science and Technology
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• v.15 no.7
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• pp.847-858
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• 2001

This paper considers the control model identification and H(sub)$\infty$ controller design for a tandem cold mill (TCM). In order to improve the performance of the existing automatic gauge control (AGC) system based on the Taylor linearized model of the TCM, a new mathematical model that can complement the Taylor linearized model is constructed by using the N4SID algorithm based on subspace method and the least squares algorithm based on ARX model. It is shown that the identified model had dynamic characteristics of the TCM than the existing Taylor linearized model. The H(sub)$\infty$ controller is designed to have robust stability to the system parameters variation, disturbance attenuation and robust tracking capability to the set-up value of strip thickness. The H(sub)$\infty$ servo problem is formulated and it is solved by using LMI (linear matrix inequality) techniques. Simulation results demonstrate the usefulness and applicability of the proposed H(sub)$\infty$ controller.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.54-63
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• 2016

As technology has developed and cost for data processing has reduced, big data market has grown bigger. Developed countries such as the United States have constantly invested in big data industry and achieved some remarkable results like improving advertisement effects and getting patents for customer service. Every company aims to achieve long-term survival and profit maximization, but it needs to establish a good strategy, considering current industrial conditions so that it can accomplish its goal in big data industry. However, since domestic big data industry is at its initial stage, local companies lack systematic method to establish competitive strategy. Therefore, this research aims to help local companies diagnose their big data capabilities through a reference model and big data capability assessment system. Big data reference model consists of five maturity levels such as Ad hoc, Repeatable, Defined, Managed and Optimizing and five key dimensions such as Organization, Resources, Infrastructure, People, and Analytics. Big data assessment system is planned based on the reference model's key factors. In the Organization area, there are 4 key diagnosis factors, big data leadership, big data strategy, analytical culture and data governance. In Resource area, there are 3 factors, data management, data integrity and data security/privacy. In Infrastructure area, there are 2 factors, big data platform and data management technology. In People area, there are 3 factors, training, big data skills and business-IT alignment. In Analytics area, there are 2 factors, data analysis and data visualization. These reference model and assessment system would be a useful guideline for local companies.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.542-552
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• 2018

Operators face challenges to plan alternative countermeasures when no procedure exists to address the current plant state. A model-based approach is desired to aid operators in acquiring plant resources and deriving response plans. Multilevel flow modeling (MFM) is a functional modeling methodology that can represent intentional knowledge about systems, which is essential in response planning. This article investigates the capabilities of MFM to plan alternatives. It is concluded that MFM has a knowledge capability to represent alternative means that are designed for given ends and a reasoning capability to identify alternative functions that can causally influence the goal achievement. The second capability can be applied to find originally unassociated means to achieve a goal. This is vital in a situation where all designed means have failed. A technique of procedure synthesis can be used to express identified alternatives as a series of operations. A case of station blackout occurring at the boiling water reactor is described. An MFM model of a boiling water reactor is built according to the analysis of goals and functions. The accident situations are defined by the model, and several alternative countermeasures in terms of operating procedures are generated to achieve the goal of core cooling.

• KIEE International Transactions on Power Engineering
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• v.4A no.4
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• pp.192-200
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• 2004

This paper evaluates FACTS control on the available transfer capability (ATC) enhancement. Technical merits of FACTS technology on boosting ATC are analyzed. More effective control means for line flow and bus voltage require the application of FACTS. In this paper, the power flow calculation method for the power systems with FACTS is based on the current injection model (CIM) and the Newton-Raphson method. An integrated scheme for ATC calculation, which considers the dynamic characteristic of the power system, is suggested. The study is applied to the IEEE 57-bus power system to demonstrate the effectiveness of FACTS control on ATC enhancement.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.327-340
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• 2021

Purpose: The purpose of this study is to propose a system predicting whether an electricity distribution system is abnormal by analyzing the temperature of the deteriorated system. Traditional electricity distribution system abnormality diagnosis was mainly limited to post-inspection. This research presents a remote monitoring system for detecting thermal images of the deteriorated electricity distribution system efficiently hereby providing safe and efficient abnormal diagnosis to electricians. Methods: In this study, an object detection algorithm (YOLOv5) is performed using 16,866 thermal images of electricity distribution systems provided by KEPCO(Korea Electric Power Corporation). Abnormality/Normality of the extracted system images from the algorithm are classified via the limit temperature. Each classification model, Random Forest, Support Vector Machine, XGBOOST is performed to explore 463,053 temperature datasets. The process capability index is employed to indicate the quality of the electricity distribution system. Results: This research performs case study with transformers representing the electricity distribution systems. The case study shows the following states: accuracy 100%, precision 100%, recall 100%, F1-score 100%. Also the case study shows the process capability index of the transformers with the following states: steady state 99.47%, caution state 0.16%, and risk state 0.37%. Conclusion: The sum of caution and risk state is 0.53%, which is higher than the actual failure rate. Also most transformer abnormalities can be detected through this monitoring system.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.784-794
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• 2020

In order to effectively evaluate the urban water security, the study investigates a novel system to assess factors that impact urban water security and builds an urban water poverty evaluation index system. Based on the contribution rates of Resource, Access, Capacity, Use, and Environment, the study adopts the Water Poverty Index (WPI) model to evaluate the water poverty levels of 14 cities in Gansu during 2011-2018 and uses the least variance method to evaluate water poverty space drive types. The case study results show that the water poverty space drive types of 14 cites fall into four categories. The first category is the dual factor dominant type driven by environment and resources, which includes Lanzhou, Qingyang, Jiuquan, and Jiayuguan. The second category is the three-factor dominant type driven by Access, Use, and Capability, which includes Longnan, Linxia, and Gannan. The third category is the four-factor dominant type driven by Resource, Access, Capability, and Environment, which includes Jinchang, Pingliang, Wuwei, Baiyin, and Zhangye. The fourth category is the five-factor dominant type, which includes Tianshui and Dingxi. The driven types impacting the urban water security factors reflected by the WPI and its model are clear and accurate. The divisions of the urban water security level supply a reliable theoretical and numerical basis for an urban water security early warning mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.435-435
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• 2000

Light Rail Transit (LRT) system is a complex and large system in which there are many subsystems, interfaces, functions and demanding performance requirements. Because many contractors participate in the development, it is necessary to apply methods of sharing common objectives and communicating effectively among all of the stakeholders. This paper shows not only the methodology and the results of computer-aided systems engineering including requirement management, functional analysis and architecting LRT system, but also propose a tool to help manage a project by linking WBS (Work Breakdown Structure), work organization and PBS (Product Breakdown Structure). The application of computer-aided tool RDD-100 provides the capability to model product design knowledge and decisions about important issues such as architecting the top-level system. The product design knowledge will be essential in integrating the following life-cycle phase activities over the life of the LRT system. Additionally, when a new generation train system is required, the reuse of the database can increase the system design productivity and effectiveness significantly.