• 한국경영과학회지
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• 제18권3호
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• pp.151-157
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• 1993

In this paper, we investigate the effects of yield randomness for lot-sizing in a multi-stage production system. The practical importance of incorporating yield randomness into production models has been emphasized by many researchers. Yield randomness, especially in semiconductor manufacturing, poses a mojor challenge for production planning and control. The task becomes even more difficult if the demand for final product is uncertain. An attempt to meet the demand with a higher level of confidence forces one to release more input in the fabrication line. This leads to excessive work-in-process (WIP) inventories which cause jobs to spend unpredictably longer time waiting for the machines. The result is that it is more difficult to meet demand with exceptionally long cycle time and puts further pressure to increase the safety stocks. Due to this spiral effect, it is common to find that the capital tied in inventory is the msot significant factor undermining profitability. We propose a policy to determine the quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need rework.

• 한국수산과학회지
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• 제45권5호
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• pp.493-498
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• 2012

We derived biological reference points for Pacific cod Gadus macrocephalus in southeastern Korean waters by applying a yield-per-recruit analysis based on a daily simulation that adopted size-dependent fecundity, growth, and natural mortality functions. This showed that the yield per recruit of Pacific cod can be maximized at an instantaneous rate of fishing mortality (F)=0.37 $yr^{-1}$ under the current regulations, where the minimum catch size ($L_c$)=30 cm in total length (TL). The maximum economic yield was estimated to be attained at $L_c$=35-45 cm TL, if F>1 $yr^{-1}$ but at $L_c$=35-40 cm TL, if F<1 $yr^{-1}$. Despite great uncertainty in the stock assessment, to develop fisheries management plans for the sustainable exploitation of Pacific cod in southeastern Korean waters, it is necessary to estimate F using capture-recapture or other expedient methods.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2009년도 제38회 동계학술대회 초록집
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• pp.413-413
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• 2010

In semiconductor manufacturing field, all equipments have various sensors to diagnosis the situations of processes. For increasing the accuracy of diagnosis, hundreds of sensors are emplyed. As sensors provide millions of data, the process diagnosis from them are unrealistic. Besides, in some cases, the results from some data which have same conditions are different. We want to find some information, such as data and knowledge, from the data. Nowadays, fault detection and classification (FDC) has been concerned to increasing the yield. Certain faults and no-faults can be classified by various FDC tools. The uncertainty in semiconductor manufacturing, no-faulty in faulty and faulty in no-faulty, has been caused the productivity to decreased. From the uncertainty, the rough set theory is a viable approach for extraction of meaningful knowledge and making predictions. Reduction of data sets, finding hidden data patterns, and generation of decision rules contrasts other approaches such as regression analysis and neural networks. In this research, a RGB sensor was used for diagnosis plasma instead of optical emission spectroscopy (OES). RGB data has just three variables (red, green and blue), while OES data has thousands of variables. RGB data, however, is difficult to analyze by human's eyes. Same outputs in a variable show different outcomes. In other words, RGB data includes the uncertainty. In this research, by rough set theory, decision rules were generated. In decision rules, we could find the hidden data patterns from the uncertainty. RGB sensor can diagnosis the change of plasma condition as over 90% accuracy by the rough set theory. Although we only present a preliminary research result, in this paper, we will continuously develop uncertainty problem solving data mining algorithm for the application of semiconductor process diagnosis.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2005년도 춘계 학술발표회 논문집
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• pp.521-528
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• 2005

The evaluation process of rock mass properties intrinsically contains some uncertainty due to the inhomogeneity of rock mass and the measurement error. Although various empirical methods for the determination of rock mass properties were suggested, there is no way of integrating various information on rock mass properties except averaging. For these reasons, this research introduces evidence theory which can model epistemic uncertainty and yield reasonable rock mass properties through combining various information such as empirical equations, in-situ test results, and so on. Through the application of evidence theory to the real site investigation and in situ experiment results, an interval of deformation modulus, cohesion and friction angle of rock mass were obtained. The ratios between lower and upper bound of those properties ranges from 1.6 to 3.6. Numerical analyses of circular hole using the properties for TYPE-2 rock mass were carried out. The magnitude or size of plastic region and radial displacement in case of lower bound properties is about 4 times larger than that of upper bound properties.

• Asian Journal of Business Environment
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• 제11권4호
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• pp.17-29
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• 2021

Purpose: The aim of this study is to explore the dynamic linkage between conditional stock market volatility and macroeconomic uncertainty of Bangladesh. Research design, data, and methodology: This study uses monthly data covering the time period from January 2005 to December 2018. A comprehensive set of macroeconomic variables, namely industrial production index (IP), consumer price index (CPI), broad money supply (M2), 91-day treasury bill rate (TB), treasury bond yield (GB), exchange rate (EX), inflow of foreign remittance (RT) and stock market index of DSEX are used for analysis. Symmetric and asymmetric univariate GARCH family of models and multivariate VAR model, along with block exogeneity and impulse response functions, are implemented on conditional volatility series to discover the possible interactions and causal relations between macroeconomic forces and stock return. Results: The analysis of the study exhibits time-varying volatility and volatility persistence in all the variables of interest. Moreover, the asymmetric effect is found significant in the stock return and most of the growth series of macroeconomic fundamentals. Results from the multivariate VAR model indicate that only short-term interest rate significantly influence the stock market volatility, while conditional stock return volatility is significant in explaining the volatility of industrial production, inflation, and treasury bill rate. Conclusion: The findings suggest an increasing interdependence between the money market and equity market as well as the macroeconomic fundamentals of Bangladesh.

• Nuclear Engineering and Technology
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• 제54권8호
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• pp.3073-3084
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• 2022

The propagation of radiation source uncertainties in spent nuclear fuel (SNF) cask shielding calculations is presented in this paper. The uncertainty propagation employs the depletion and source term outputs of the deterministic code STREAM as input to the transport simulation of the Monte Carlo (MC) codes MCS and MCNP6. The uncertainties of dose rate coming from two sources: nuclear data and modeling parameters, are quantified. The nuclear data uncertainties are obtained from the stochastic sampling of the cross-section covariance and perturbed fission product yields. Uncertainties induced by perturbed modeling parameters consider the design parameters and operating conditions. Uncertainties coming from the two sources result in perturbed depleted nuclide inventories and radiation source terms which are then propagated to the dose rate on the cask surface. The uncertainty analysis results show that the neutron and secondary photon dose have uncertainties which are dominated by the cross section and modeling parameters, while the fission yields have relatively insignificant effect. Besides, the primary photon dose is mostly influenced by the fission yield and modeling parameters, while the cross-section data have a relatively negligible effect. Moreover, the neutron, secondary photon, and primary photon dose can have uncertainties up to about 13%, 14%, and 6%, respectively.

• Transactions on Control, Automation and Systems Engineering
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• 제3권3호
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• pp.159-163
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• 2001

An input constrained receding horizon predictive control algorithm for uncertain systems with nonzero set points is proposed. for constant nonzero set points, models with uncertainty can be converted into an augmented incremental system through the use of integrators and the problem is transformed into a zero-state regulation problem for the incremental system. But the original constraints on inputs are converted into constraints on the sum of control inputs at each time instants, which have not been dealt in earlier constrained robust receding horizon control problems. Recursive state bounding technique and worst case minimizing strategy developed in earlier works are applied to the augmented incremental system to yield an offset error free controller. The resulting algorithm is formulated so that it can be solved using LP.

• Current Research on Agriculture and Life Sciences
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• 제31권4호
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• pp.233-239
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• 2013

Understanding the temporal variability of agricultural parameters derived from historical climate data is important for planning in agriculture. Therefore, this study assessed the magnitude and recent trends of the transpiration ratio defined as the crop water use per harvested yield for the period from 1980 to 2010. The crop water use was estimated using the Food and Agriculture Organization's Crop Wat model for eight administrative provinces in Korea. The temporal trends and spatial uncertainty were explored using the Mann-Kendall and Theil Sen's methods. The regional average rice yield was $6.31t\;ha^{-1}$(range 5.9 to $6.9t\;ha^{-1}$). The results showed that the rice yield in Korea increased by $26kg\;ha^{-1}yr^{-1}$. Overall, the regional average transpiration ratio was $1,298m^3t^{-1}$ (range 1,162 to $1,470m^3t^{-1}$). From 1980 to 2010, the transpiration ratio decreased by $8.2m^3t^{-1}$ (range 2.7 to $14.4m^3t^{-1}$), largely as a result of the increasing yield. The statistical approach to historical data used in this study also provides a basis for simulating the future transpiration ratio.

• 마이크로전자및패키징학회지
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• 제26권1호
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• pp.29-33
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• 2019

전자패키지 크기의 소형화와 전자기기의 성능 향상이 함께 이루어지면서 높은 입출력 밀도 구현이 중요한 요소로서 평가받고 있다. 이를 구현하기 위해 팬아웃 웨이퍼 레벨 패키지(FO-WLP)가 큰 주목을 받고 있다. 하지만 FO-WLP는 휨(Warpage) 현상에 취약하다는 약점이 있다. 휨 현상은 생산 수율 감소와 더불어 패키지 신뢰성 하락에 큰 원인이므로 이를 최소화하는 것이 필수적이다. 유한요소해석을 이용한 재질의 물성 등 FO-WLP의 휨 현상과 연관된 요소에 대한 많은 연구가 진행되어 왔지만, 대부분의 연구는 이러한 요소들의 불확실성을 고려하지 않았다. 재질의 물성, 칩의 위치 등 패키지의 휨 현상과 연관된 요소들은 제조 측면에서 보았을 때 불확실성을 가지고 있기 때문에, 실제 결과와 더 가깝게 모사하기 위해서는 이러한 요소들의 불확실성이 고려되어야 한다. 이번 연구에서는 FO-WLP 과정 중 칩의 탄성 계수가 정규 분포를 따르는 불확실성을 가졌을 때 휨 현상에 미치는 영향을 유한요소해석을 통해 알아보았다. 그 결과 칩의 탄성 계수의 불확실성이 최대 von Mises 응력에 영향을 미치는 것을 확인하였다. Von Mises 응력은 전체 패키지 신뢰성과 관련된 인자이기 때문에 칩의 물성에 대한 불확실성 제어가 필요하다.

• 산업경영시스템학회지
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• 제15권26호
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• pp.59-66
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• 1992

This Paper, first, tries to optimize the output specifications with uncertain characteristics. And then aims to solve the problem not only by making use of transformed multiple regression equation which can yield objective function of output characteristics but also by formulating developed multiple fuzzy goal programming using fuzzy set theory which can treat uncertainty easily, and the efficiency of these techniques, will be also demonstrated through a case study.