• Tribology and Lubricants
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• 제39권3호
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• pp.94-101
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• 2023

Automotive wheel bearings are a critical component of vehicles that support their weight and facilitate rotation. Life and stiffness are significant performance characteristics of wheel bearings. Designing wheel bearings involves finding optimal design variables that satisfy both performances. CO₂ emission reduction and fuel efficiency regulations attribute to the recent increase in design requirements for lightweight and compact automotive parts while maintaining performance. However, achieving a design that maintains performance while reducing weight poses challenges, as performance and weight are generally inversely proportional. In this study, we perform design optimization of automotive wheel bearings considering life and stiffness. We develop a program that calculates the basic rated life and modified rated life based on international standards for evaluating the life of wheel bearings. We develop a regression equation using regression analysis to address the time-consuming stiffness analysis during repetitive analysis. We perform ANOVA and main effect analyses to understand the statistical characteristics of the developed regression equation. Furthermore, we verify its reliability by comparing the predicted and test results. We perform design optimization using the developed life prediction program, stiffness regression equation and weight regression equation. We select bearing specifications and geometry as design variables, weight as the cost function, and life and stiffness as constraints. Through design optimization, we investigate the influence of design variables on the cost function and constraints by comparing the initial and optimal design values.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.544-555
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• 1998

Although the bimodal mixed weibull distribution is used to developing burn-in model widely, the failure times for a component or a system is often truncated at some time, T, due to the obsolescence in the electronics industry. In this paper, we will determine minimum total cost and burn-in time by using the bimodal mixed weibull distribution and the truncated bimodal mixed weibull distribution under the free warranty policy. The results of this study are summarized as follows. First, when products or system is not repairable, the width of the change of burn-in time can be larger by ${\beta}_1,\;{\beta}_2$ Second, if burn-in time become longer, it will be impossible to consider the bum-in in a long time, and in this case, the burn-in time should be shorten by the acceleration burn-in. Third, in case that opportunity loss cost or repair cost is exceed the warranty cost, or the total cost of considering burn-in is larger than that of not considering burn-in, it is not existed burn-in time which makes total cost to minimize. Forth, the shorter life-cycle of product, the more burn-in times will be decreased and the cost in considering burn-in will be increased

• 벤처창업연구
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• 제7권4호
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• pp.143-148
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• 2012

기업들이 제품을 개발하는데 가치공학을 적용하여 실시할 때 느끼는 공통적인 어려움은 기능을 어떻게 정확하게 정의하느냐가 관건인 것으로 나타났다. 기능이라는 추상적인 개념을 어떻게 수치화하느냐에 따라 가치공학의 효과가 차이가 나기 때문이다. 더 나아가 가치공학의 성과를 향상시키기 위해서는 가치의 향상이 요구되어지는데 가치공학을 실시하고 있는 대부분의 기업들은 원가절감에 목적을 두고 이 방법을 추진하고 있다. 제품 개발의 연구결과 기능은 충족하면서 본체, 노트북, 부루투스 프로브가 제품에 대부분을 차지하는 것을 확인할 수 있으며, 원가절감을 위해서는 안정된 품질이 요구되는 것과 맞추어 구매에서의 원가 절감노력이 필요하다고 사료되며 구매업체의 다변화를 통한 가격다운 절감노력이 필요한 것으로 분석, 연구되었다.

• 한국산학기술학회논문지
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• 제20권10호
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• pp.149-158
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• 2019

본 논문에서는 다수의 구성품으로 구성된 시스템에 대해 Hidden Failure를 고려하여 최적의 계획 정비 스케줄링 문제에 대해 연구하였다. 계획 정비 스케줄링의 목적은 장기 운용 유지비용 최소화이다. 시스템 측면에서는 다수의 구성품을 그룹화하여 검사함으로써 시스템이 정지함으로 인해 발생할 수 있는 비용을 최소화 할 수 있다. 또한 각 구성품 별로 적절한 검사 주기를 선정하여 고장을 조기에 확인함으로써 고장 발생으로 인한 비용을 최소화 할 수 있다. 본 논문에서는 계산의 복잡성을 줄이기 위해 기존 연구에서 사용한 "Base interval approach"를 적용하였으며 추가적으로 다수 구성품의 동시 검사를 통한 검사비용 절감 효과를 고려하였다. 검사비용은 소요되는 시설, 장비 및 인력 비용으로 구성된다고 가정하였으며 유사한 구성품을 동시에 검사함으로써 검사비용이 절감되는 경우에 대한 분석을 실시하였다. 본 논문에서는 검사비용 절감 효과를 비교하기 위해 기존 연구에서 활용한 사례를 대상으로 분석을 실시하였고 이에 따른 비용 절감 효과를 시뮬레이션을 통해 비교하여 제시한다.

• 정보관리연구
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• 제36권1호
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• pp.155-171
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• 2005

온라인 기술이전시장은 단순한 기술 수요자와 공급자가 만나는 자리일 뿐만 아니라 기술이전 관련 정보를 제공함으로써 기술이전에 있어서 그 시간적, 물리적 비용을 줄이는 데 그 존재의 이유가 있다. 기술이전시 정보제공에는 시의성이 중요한 요인으로 작용하므로 이를 효율적으로 관리하기 위한 콘텐츠 통합관리 시스템이 요구된다. 종래의 온라인 기술이전정보 제공 사이트는 단순한 기술정보의 제공과 수시로 발생하는 기술판 매자나 수요자의 갱신상황을 반영하지 못하고 있다. 이에 본 연구에서는 기술수요자나 기술공급자에게 보다 시의적절한 정보를 제공할 수 있는 방안을 제시하기 위하여 온라인 기술이전정보 통합 시스템에 대한 구현의 예를 제시하고자 한다.

• 전력전자학회논문지
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• 제25권5호
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• pp.376-384
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• 2020

An energy storage system is composed of lithium-ion batteries in modern applications. Batteries are regarded as storage devices for renewable and residual energy. The failure of batteries can cause the performance reduction and explosion of battery systems. High maintenance cost is essential when dealing with the problem of battery safety. Therefore an accurate health diagnosis is required to ensure the high reliability of battery systems. A battery pack is a combination of single cells in series and parallel connections. A battery pack has to consider various factors to assess battery health. Battery health involves conventional factors and additional factors, such as cell-to-cell imbalance. For large applications, state-of-health (SOH) can be inaccurate because of the lack of factors that indicate the state of the battery pack. In this study, six characterization factors are proposed for improving the SOH estimation of battery packs. The six proposed characterization factors can be regarded as health indicators (HIs). The six HIs are applied to the principal component analysis (PCA) algorithm. To reflect information regarding capacity, voltage, and temperature, the PCA algorithm extracts new degradation factors by using the six HIs. The new degradation factors are applied to a multiple regression model. Results show the advancement and improvement of SOH estimation.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.248-256
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• 2021

Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.

• ETRI Journal
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• 제32권5호
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• 한국멀티미디어학회논문지
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• 제6권6호
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• pp.1000-1007
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• 2003

이 논문은 입술의 모양을 효과적으로 추출하는 방법을 제안하였다. 입술은 Point Distribution Model에 근거하여 점들의 집합으로 표현하였다. Isodata군집 알고리듬을 이용하여 전체 학습 영상을 입술 형태별로 군집화 하고 주성분 분석법을 사용하여 각 군집에 대한 입술의 형태 모델을 구하였다 추출 결과가 입력 영상의 실제 입술 위치를 올바르게 찾았는지 판정하기 위하여 입술 경계선 주변의 화소값들을 이용한 입술의 경계선 모델을 구하고 이를 반영하는 평가함수를 구성하였다. 형태 차이를 반영하여 얻은 입술 형태 모델을 사용하여 입술을 추출하기 때문에 전체 학습 영상의 평균 모양과 많은 차이를 보이는 입술을 정확하게 추출할 수 있었다. 여러 영상을 대상으로 실험하여 약 92%의 성공률을 얻었다.

• 제어로봇시스템학회논문지
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• 제6권1호
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.