• International Journal of Reliability and Applications
• /
• 제10권1호
• /
• pp.1-15
• /
• 2009

Even though the impact of manufacturing quality to reliability is not considered much as well as that of design area, a major cause of an early failure of the product is known as manufacturing problem. This research applies two different types of neural network algorithms, the Back propagation (BP) algorithm and Learning Vector Quantization (LVQ) algorithm, to identify and classify the nonrandom variation pattern on the control chart based on knowledge-based diagnosis of dimensional variation. The performance and efficiency of both algorithms are evaluated to choose the better pattern recognition system for auto body assembly process. To analyze hundred percent of the data obtained by Optical Coordinate Measurement Machine (OCMM), this research considers an application in which individual observations rather than subsample means are used. A case study for analysis of OCMM data in underbody assembly process is presented to demonstrate the proposed knowledge-based pattern recognition system.

• Journal of Electrical Engineering and Technology
• /
• 제12권5호
• /
• pp.1945-1954
• /
• 2017

In recent years, several LCL filter design methods for different converter topologies have been published, many of which use analytical expressions to calculate the ideal converter AC voltage harmonic spectrum. This paper presents the LCL filter design methodology but the focus is on presentation and validation of the non-iterative filter design method for a grid-connected three-phase two-level PWM-VSC. The developed method can be adapted for different converter topologies and PWM algorithms. Furthermore, as a starting point for the design procedure, only the range of PWM carrier frequencies is required instead of an exact value. System nonlinearities, usually omitted from analysis have a significant influence on VSC AC voltage harmonic spectrum. In order to achieve better accuracy of the proposed procedure, the system nonlinear model is incorporated into the method. Optimal filter parameters are determined using the novel cost function based on higher frequency losses of the filter. An example of LCL filter design for a 40 kVA grid-connected PWM-VSC has been presented. Obtained results have been used to construct the corresponding laboratory setup and measurements have been performed to verify the proposed method.

• Journal of Mechanical Science and Technology
• /
• 제16권5호
• /
• pp.619-632
• /
• 2002

In recent study on design of experiments, the complicate metamodeling has been studied because defining exact model using computer simulation is expensive and time consuming. Thus, some designers often use approximate models, which express the relation between some inputs and outputs. In this paper, we review and compare the complicate metamodels, which are expressed by the interaction of various data through trying many physical experiments and running a computer simulation. The prediction model in this paper employs interpolation schemes known as ordinary kriging developed in the fields of spatial statistics and kriging in Design and Analysis of Computer Experiments (DACE) model. We will focus on describing the definitions, the prediction functions and the algorithms of two kriging methods, and assess the error measures of those by using some validation methods.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
• /
• pp.438-441
• /
• 2004

In this study, we introduce a noble neurogenetic approach to the design of fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and Fuzzy-Set based Neural Networks (FSNN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, the tuning of the scaling factors of the fuzzy controller is carried out by using GAs, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based FSNN. The developed approach is applied to a nonlinear system such as an inverted pendulum where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.

• 한국전산구조공학회논문집
• /
• 제36권6호
• /
• pp.399-405
• /
• 2023

본 연구에서는 철근콘크리트 모멘트골조의 보-힌지 붕괴 기구를 유도하기 위한 유전자알고리즘 기반의 최적내진설계기법을 제시한다. 제안하는 기법은 두 가지의 목적함수을 사용한다. 첫 번째는 구조물의 비용을 최소화하는 것이고, 두 번째는 구조물의 에너지소산능력을 최대화하는 것이다. 제약조건은 기둥과 보의 강도조건, 기둥-보 휨강도비 최소 조건, 기둥의 소성힌지 발생 방지조건 등이 사용된다. 부재의 강도 평가를 위해 선형정적해석이 수행되고, 에너지소산능력과 소성힌지 발생여부를 평가하기 위해 비선형정적해석이 수행된다. 제안하는 기법은 4층 예제 구조물에 적용되었으며, 보-힌지 붕괴 기구를 유도하는 설계안이 얻어지는 것을 확인하였다. 획득된 설계안의 기둥-보 휨강도비를 분석한 결과, 그 값은 기존 내진 기준에서 제시하는 값보다 큰 것으로 나타났다. 보-힌지 붕괴 모드를 유도하기 위해서는 보다 더 강화된 전략이 필요하다.

• 대한안전경영과학회지
• /
• 제7권5호
• /
• pp.155-174
• /
• 2005

Parametric life-cycle cost(LCC) models have been integrated with traditional design tools, and used in prior work to demonstrate the rapid solution of holistic, analytical tradeoffs between detailed design variations. During early designs stages there may be competing concepts with dramatic differences. Additionally, detailed information is scarce, and decisions must be models. for a diverse range of concepts, and the lack of detailed information make the integration make the integration of traditional LCC models impractical. This paper explores an approximate method for providing preliminary life-cycle cost. Learning algorithms trained using the known characteristics of existing products be approximated quickly during conceptual design without the overhead of defining new models. Artificial neural networks are trained to generalize on product attributes and life cycle cost date from pre-existing LCC studies. The Product attribute data to quickly obtain and LCC for a new and then an application is provided. In additions, the statistical method, called regression analysis, is suggested to predict the LCC. Tests have shown it is possible to predict the life cycle cost, and the comparison results between a learning LCC model and a regression analysis is also shown

• Journal of Mechanical Science and Technology
• /
• 제17권5호
• /
• pp.668-678
• /
• 2003

For the purpose to facilitate development of high-speed spindle units (SUs) running on rolling bearings, we have developed a beam element model, algorithms, and software for computer analysis of thermal characteristics of SUs. The thermal model incorporates a model of heat generation in rolling bearings, a model of heat transfer from bearings, and models for estimation of temperature and temperature deformations of SU elements. We have carried out experimental test and made quantitative evaluation of the effect of operation conditions on friction and thermal characteristics of the SUs of grinding and turning machines of typical structures. It is found out that the operation conditions make stronger effect on SU temperatures when rpm increases. A comparison between the results of analysis and experiment proves their good mutual correspondence and allows us to recommend application of the models and software developed for design and research of high-speed SUs running on rolling bearings.

• 패션비즈니스
• /
• 제26권1호
• /
• pp.1-15
• /
• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• 한국정밀공학회지
• /
• 제13권9호
• /
• pp.114-129
• /
• 1996

This paper describes the whole development phase for the underwater vehicle actuating system with high hydroload torque disturbance. This includes requirement analysis, system modeling, control algorithm design, real time implementation, test and performance evaluations. As for driving control algorithms, fuzzy logic, variable structure and PD(Proportional-Differential) algorithm were designed and implemented on board controller using a single chip microprocessor. Intel 8797. And test and performance evaluation is carried out both single test and wystem integration test. We could confirm the basic performance of actuating system through the single test and gereral developing work of any actuating systems was finished with a single performance test of actuating system without system integration test. But, we suggested that system integration test be needed. System integration test is carried out using G/C HILS(Guidance and Control Hardware-In-the -Loop Simulation) which is constituted flight motion simulator, load simulator, real time host computer and the related subsystems such as inertial navigation system, power supply system and Guidance and Control Computer etc.. The most important practical contribution of this paper is that full system characteristics such as minimal control effort, enhancement of guidance and autopilot performance by the actuating system using G/C HILS technique are investigated. Through full running G/C HILS, in spite of the passing to single tests, some control algorithm resulted in failure as to stability of full system and system time frame.

• 한국멀티미디어학회논문지
• /
• 제19권4호
• /
• pp.747-755
• /
• 2016

Automated guided vehicles have been used for a long time to increase work efficiency in the logistics field, but it is difficult to apply to a variety of logistics sites due to either the restricted movement mechanism or expensive devices. In this paper, we present a flexible software architecture that is hardware-independent for a mobile power cart of the follow mode and implement it using a ROS software platform. Through the SCV analysis for the system functionalities, we design a package to track a user movement and a package to control a new hardware platform. It has an advantage to use a variety of movement algorithms and hardware platforms by applying the strategy pattern and the template method pattern for the design of a software architecture. Through the performance evaluation, we show that the proposed design is maintainable in terms of a software complexity and it detects a user's movement by obtaining a user skeleton information so that it can control a hardware platform to move at a certain distance.