• 한국경영과학회지
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• 제29권3호
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• 한국경영과학회지
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• 제35권4호
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• pp.33-53
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• 2010

When purchase prices of a raw material fluctuate over time, the total purchasing cost is mainly affected by reordering time. Existing researches focus on deciding the right time when the demand for each period is replenished at the lowest cost. However, the decision is based on expected future prices which usually turn out to include some error. This discrepancy between expected prices and actual prices deteriorates the performance of inventory models dealing with fluctuating purchase prices. In this paper, we propose a new inventory model which incorporates not only cost but also risk into making up a replenishment schedule to meet each period's demand. For each replenishment schedule, the risk is defined to be the variance of its total cost. By introducing the risk into the objective function, the variability of the total cost can be mitigated, and eventually more stable replenishment schedule will be obtained. According to experimental results from crude oil inventory management, the proposed model showed better performance over other models in respect of variability and cost.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.365-368
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• 2006

The implementation of a screening procedure for removing non-conforming products has become a common practice especially in high-tech manufacturing industries. Screening procedures involve a measurement on the quality characteristic of interest since decisions regarding the conformance to specifications are usually made on the basis of the realization of measurement. A significant variability in measurement procedures may result in the misclassification of an outgoing product (that is, falsely accepting defectives or falsely rejecting conforming items), which may lead to wrong interpretation on product quality, It may thus be necessary to consider the impacts of misclassification errors due to measurement variability when designing screening procedures. Along this line, this article investigates the design of screening procedures based on the assessment of misclassification errors. The main objective is to determine the screening limits on measured values so that two types of misclassification errors may properly be compromised.

• 대한안전경영과학회지
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• 제13권4호
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• pp.225-235
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• 2011

Autoregressed Controller, which have trend algorithm, seeks to minimize variability by transferring the output variable to the related process input variable, while multivariate process control techniques seek to reduce variability by detecting and eliminating assignable causes of variation. In the case of process control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We also investigate algorithm with relevant Shewhart chart, Theoretical control charts, precontrol and process capability. To help the people who want to make the theoretical system, we compare the main techniques in "a study on the relation between multivariate process control techniques and trend algorithms".

• Journal of Cardiovascular Imaging
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• 제31권3호
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• pp.135-141
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• 2023

BACKGROUND: Global longitudinal strain (GLS) is an accurate and reproducible parameter of left ventricular (LV) systolic function which has shown meaningful prognostic value. Fast, user-friendly, and accurate tools are required for its widespread implementation. We aim to compare a novel web-based tool with two established algorithms for strain analysis and test its reproducibility. METHODS: Thirty echocardiographic datasets with focused LV acquisitions were analyzed using three different semi-automated endocardial GLS algorithms by two readers. Analyses were repeated by one reader for the purpose of intra-observer variability. CAAS Qardia (Pie Medical Imaging) was compared with 2DCPA and AutoLV (TomTec). RESULTS: Mean GLS values were -15.0 ± 3.5% from Qardia, -15.3 ± 4.0% from 2DCPA, and -15.2 ± 3.8% from AutoLV. Mean GLS between Qardia and 2DCPA were not statistically different (p = 0.359), with a bias of -0.3%, limits of agreement (LOA) of 3.7%, and an intraclass correlation coefficient (ICC) of 0.88. Mean GLS between Qardia and AutoLV were not statistically different (p = 0.637), with a bias of -0.2%, LOA of 3.4%, and an ICC of 0.89. The coefficient of variation (CV) for intra-observer variability was 4.4% for Qardia, 8.4% 2DCPA, and 7.7% AutoLV. The CV for inter-observer variability was 4.5%, 8.1%, and 8.0%, respectively. CONCLUSIONS: In echocardiographic datasets of good image quality analyzed at an independent core laboratory using a standardized annotation method, a novel web-based tool for GLS analysis showed consistent results when compared with two algorithms of an established platform. Moreover, inter- and intra-observer reproducibility results were excellent.

• International Journal of Reliability and Applications
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• 제10권2호
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• pp.89-99
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• 2009

Oriented Strand Board (OSB) is an important engineered wood product used in housing construction which has a lower environmental impact or "carbon footprint." In this paper, reliability and statistical tools are applied to gain insights on the strand thickness of OSB panels. An OSB panel consists of several hundred wood strands that are resinated and pressed. The variability of OSB strand thickness for six manufacturers in the Eastern United States is examined as a whole, as well as individually. Little research exists on OSB strand thickness across mills even though strand thickness variability has been documented in laboratory experiments to greatly influence the dimensional stability of OSB panels. Our aims are to quantify and characterize strand thickness, plus apply reliability techniques, such as Kaplan-Meier curves, to characterize the probability of strand thickness. We further explore graphically and statistically the thickness of the strands.

• The Journal of Asian Finance, Economics and Business
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• 제6권4호
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• pp.139-145
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• 2019

This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

• 한국경영과학회지
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• 제27권4호
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• pp.185-205
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• 2002

In this study, we consider infinite supply of raw materials and backlogged demands as given two boundary conditions. And we need not make any specific assumptions about the inter-arrival of external demand and service time distributions. Under these situations, the ultimate objective of this study is to prove the variability propagation principle in a pull serial line and is to measure it in terms of the first two moments of the inter-departure process subject to number of cards in each cell. Two preparations are required to achieve this objective : The one is to derive a true lower bound of variance of the inter-departure process. The other is to establish a constrained discrete minimax problem for the no backorder (backlogging) probabilities in each cell. We may get some fundamental results necessary to a completion for the proof through the necessary and sufficient conditions for existence of optimal solution of a constrained discrete minimax problem and the implicit function theorem. finally, we propose a numeric model to measure the variability propagation principle. Numeric examples show the validity and applicability of our study.

• Journal of Biosystems Engineering
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• 제33권5호
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• pp.362-369
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• 2008

There is developing interest in precision agriculture in Korea, despite the fact that typical Korean fields are less than 1 ha in size. Describing within-field variability in typical Korean production settings is a fundamental first step toward determining the size of management zones and the inter-relationships between limiting factors, for establishment of site-specific management strategies. Measurements of rice (Oriza Sativa L) yield, chlorophyll content, and soil properties were obtained in a small (100-m by 30-m) Korean rice paddy field. Yield data were manually collected on 10-m by 5-m grids (180 samples with 3 samples in each of 60 grid cells) and chlorophyll content was measured using a Minolta SPAD 502 in 2-m by 2-m grids. Soil samples were collected at 275 points to compare results from sampling at different scales. Ten soil properties important for rice production in Korea were determined through laboratory analyses. Variogram analysis and point kriging with and without median polishing were conducted to determine the variability of the measured parameters. Influence of variogram model selection and other parameters on the interpretation of the data was investigated. For many of the data, maximum values were greater than double the minimum values, indicating considerable spatial variability in the small paddy field, and large-scale spatial trends were present. When variograms were fit to the original data, the limits of spatial dependency for rice yield and SP AD reading were 11.5 m and 6.5 m, respectively, and after detrending the limits were reduced to 7.4 m and 3.9 m. The range of spatial dependency for soil properties was variable, with several having ranges as short as 2 m and others having ranges greater than 30 m. Kriged maps of the variables clearly showed the presence of both large-scale (trend) variability and small-scale variability in this small field where it would be reasonable to expect uniformity. These findings indicate the potential for applying the principles and technology of precision agriculture for Korean paddy fields. Additional research is needed to confirm the results with data from other fields and crops.d similar tendency with the result for the frequency less than 20 Hz, but the width of change was reduced highly.

• 한국물환경학회지
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• 제34권1호
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• pp.33-45
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• 2018

In this study, we discussed the application of Watershed model and Load Duration Curves (LDC) in Total Water Load Management System. The Flow Duration Curves (FDC) and the LDC were generated using the results of the daily HSPF model and analyzed on monthly or yearly flow duration variability, and non-point pollutant discharge loads by entire flow conditions. As a result of the calibration and verification of the HSPF model, both the flow and the water quality were appropriately simulated. The simulated values were used to generate the Flow Duration Curve and the Load Duration Curve, and then the excess rate by entire flow conditions was analyzed. The point and non-point pollutant discharge loads for entire flow conditions were calculated. It is possible to evaluate the variability of water quality in specific flow duration through the curves reflecting the flow duration variability and to confirm the characteristics of the pollutant source. For a more scientific Total Water Load Management System, it is necessary to switch from a current system to a system that can take into account the entire flow conditions. For this, the application of the watershed model and load duration curve is considered to be the best alternative.