• Geomechanics and Engineering
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• v.7 no.5
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• pp.539-552
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• 2014

A simplified probability-based design charts for stone column-improved ground have been presented based on the unit cell approach. The undrained cohesion ($c_u$) and coefficient of radial consolidation ($c_r$) of the soft soil are taken as the most predominant random variables. The design charts are developed to estimate the diameter of the stone column or the spacing between the stone columns by employing a factored design value of $c_r$ and $c_u$ so as to satisfy a specific probability level of the target degree of consolidation and/or a target safe load that needs to be achieved in a specified timeframe. The design charts can be used by the practicing engineers to design the stone column-improved ground by considering consolidation and /or bearing capacity of the improved ground.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1289-1303
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• 2010

The need for statistical process control to check the performance of a process is becoming more important in chemical and pharmaceutical industries. This study illustrates the method to determine whether a process is in control and how to produce and interpret control charts. In the experiment, a stream of green dyed water and a stream of pure water were continuously mixed in the process. The concentration of the dye solution was measured before and after the mixer via a spectrophotometer. The in-line mixer provided benefits to the dye and water mixture but not for the stock dye solution. The control charts were analyzed, and the pre-mixer process was in control for both the stock and mixed solutions. The R and X-bar charts showed virtually all of the points within control limits, and there were no patterns in the X-bar charts to suggest nonrandom data. However, the post-mixer process was shown to be out of control. While the R charts showed variability within the control limits, the X-bar charts were out of control and showed a steady increase in values, suggesting that the data was nonrandom. This steady increase in dye concentration was due to discontinuous, non-steady state flow. To improve the experiment in the future, a mixer could be inserted into the stock dye tank. The mixer would ensure that the dye concentration of the stock solution is more uniform prior to entering the pre-mixer ow cell. Overall, this would create a better standard to judge the water and dye mixture data against as well.

• Journal of the Korea Safety Management & Science
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• v.12 no.4
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• pp.255-263
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• 2010

The research developes short-run standardized control charts(SSCC) and short-run acceptance control charts(SACC) under the various demand patterns. The demand patterns considered in this paper are three types such as high-variety and repetitive low-volume pattern, extremely-high-variety and nonrepetitive low-volume pattern, and high-variety and extremely-low-volume pattern. The short-run standardized control charts developed by extending the long-run ${\bar{x}}$-R, ${\bar{x}}$-s and I-MR charts have strengths for practioners to understand and use easily. Moreover, the short-range acceptance control charts developed in the study can be efficiently used through combining the functions of the inspection and control chart. The weighting schemes such as Shewhart, moving average (MA) and exponentially weighted moving average (EWMA) can be considered by the reliability of data sets. The two types according to the use of control chart are presented in the short-range standardized charts and acceptance control charts. Finally, process capability index(PCI) and process performance index(PPI) classified by the demand patterns are presented.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.773-782
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• 2007

The statistical process control charts are very extensively used for monitoring of process mean, deviation, defect rate or reject rate. In this paper we consider a control chart to monitor the process reject rate in the high yield process, which is based on the observed cumulative probability of the number of items inspected until r defective items are observed. We first propose selection of the optimal value of r in the CPC-r charts, and also consider the usefulness of the chart in high yield process such as semiconductor or TFT-LCD manufacturing process.

• Journal of Industrial Technology
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• v.2
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• pp.27-31
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• 1982

An approximation to the ARL for cusum control charts is derived using a Brownian motion approximation to the cumulative sum. The accuracy of this approximation is numerically evaluated and the results are compared with those obtained by other method.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.200-207
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• 2014

Average number of samples to signal (ANSS) and average time to signal (ATS) are the most widely used criterion for comparing the efficiencies of the quality control charts. In this study the method of evaluating ANSS and ATS values of the multivariate exponentially weighted moving average (EWMA) control charts with Markov chain approach was presented when the production process is in control state or out of control state. Through numerical results, it is found that when the number of transient state r is less than 50, the calculated ANSS and ATS values are unstable; and ATS(r) tends to be stabilized when r is greater than 100; in addition, when the properties of multivariate EWMA control chart is evaluated using Markov chain method, the number of transient state r requires bigger values when the smoothing constatnt ${\lambda}$ becomes smaller.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.451-466
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• 2020

CCC-r chart is effective for high-quality processes with a very low fraction nonconforming. The values of process parameters should be estimated from the Phase I sample since they are often not known. However, if the Phase I sample size is not sufficiently large, an estimation error may occur when the parameter is estimated and the practitioner may not achieve the desired in-control performance. Therefore, we adjust the control limits of CCC-r charts using the bootstrap algorithm to improve the in-control performance of charts with smaller sample sizes. The simulation results show that the adjustment with the bootstrap algorithm improves the in-control performance of CCC-r charts by controlling the probability that the in-control average number of observations to signal (ANOS) has a value greater than the desired one.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.7 no.4
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• pp.681-693
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• 1995

A new set of capillary tube selection charts for R-22 is proposed. The set of charts takes into account of the roughness effect on the mass flow rate. For this purpose, a set of numerical model is developed and a series of experiments is conducted to verify the numerical model. A numerical model is used to calculated the mass flow rate for several sets of tube diameter, length, inlet pressures and degree of subcooling. The outlet of the tube is controlled to be at critical condition. The experimental flow rate is compared with calculated values. The calculated values are consistently less than the experimental ones except for the flow rate range below 40kg/hr. The deviation is within 10---. Based on the nunmerical model and results of experiments, the set of capillary tube selection charts for R-22 is constructed. The set of charts consists of standard capillary tube chart(L=2030mm, d=1.63mm, ${\varepsilon}=2.5{\mu}m$), non -standard flow factor(${\phi}_1$) chart, and non-standard roughness factor(${\phi}_2$) chart. The mass flow rate, flow factor, and the roughness factor are defined respectively as; $\dot{m}={\phi}_1{\phi}_2\dot{m}_{standard}\\{\phi}_1=\frac{\dot{m}(L,\;d,\;\varepsilon_{standard})}{\dot{m}_{standard}(L_{standard},\;d_{standard},\;{\varepsilon}_{standard})}\\{\phi}_2=\frac{\dot{m}(L_{standard},\;d_{standard},\;{\varepsilon})}{\dot{m}_{standard}(L_{standard},\;d_{standard},\;{\varepsilon}_{standard})}$.

• International Journal of Air-Conditioning and Refrigeration
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• v.12 no.4
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• pp.192-197
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• 2004

A capillary tube, which is a common expansion device in small sized refrig-eration and air-conditioning systems, should be redesigned properly to establish an optimum operation cycle of a refrigerating system with alternative refrigerants. Based on experimental data for R-22, R-290, and R-407C, an empirical correlation is developed to predict mass flow rate through capillary tubes. Dimensionless parameters are derived from the Buckingham Pi theorem, considering the effects of operating conditions and capillary tube geometry on mass flow rate. Approximately $97\%$ of the present data are correlated within a relative deviation of $\pm\;10\%.$ The present correlation also predicts the data obtained from open literature within $\pm\;15\%.$ In addition, rating charts of refrigerant flow rate for R-12, R-22, R-134a, R-152a, R-407C, R-410A, R-290, and R-600a are developed.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.529-536
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• 2016

The purpose of this research is to evaluate the quality of Differential Police Response strategy. Although it has been approximately three years since these new police response systems were introduced, there is no research to evaluate them empirically. Using two types of statistical quality control techniques, Xbar-R control charts for variables data and P charts for attributes data, this study analyzes approximately 3,000 calls reported throughout the year 2012 to the 112 Integrated Dispatch Center in Ik-san police station. The Xbar-R control charts revealed that the police did not consistently respond to an emergency call for service (i.e., code one case) within 3 minutes. The P control chart also identified that there was a significant variation in the portion/number of defective calls where police failed to respond to non-emergency calls for service within 5 minutes. The results from this study suggest the police may need to review the target response time for code 1 and code 2 respectively.