• The Korean Journal of Applied Statistics
• /
• v.17 no.3
• /
• pp.499-505
• /
• 2004

The Pareto diagram analysis of the experimental data by the two level orthogonal arrays has been used widely in practice since it is a graphical, quick and easy method to analyze experimental results, which does not use the analysis of variance to screen significant effects. For the analysis of the experimental data by $L_{18}(2 \times 3^7)$ orthogonal array, Park(1996) proposed Pareto ANOVA in which the size of effects is defined by the mean squares of effects and the Pareto principle is used. In this paper, a new approach of the Pareto diagram analysis of the experimental data by $L_{18}(2 \times 3^7)$ orthogonal array is proposed. The main idea is to partition the size of three level effects by that of linear and quadratic orthogonal contrasts of those effects.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.44 no.6
• /
• pp.49-60
• /
• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

• International Journal of Quality Innovation
• /
• v.2 no.2
• /
• pp.127-135
• /
• 2001

Personnel engaged in the medical field have implemented continual improvement by team activities in an effort to construct a system that reduces the risks involved in medical care. Knowledge in total quality management (TQM), especially statistical quality control (SQC) developed for industry, seems to be applicable to medical care. This paper describes the application of SQC to continual improvement in medical care.

• International Journal of Reliability and Applications
• /
• v.3 no.2
• /
• pp.61-80
• /
• 2002

Tree-harvesting worker data of 508 separate worker accidents are analyzed and an exploratory approach taken. The worker accident data cover a sample of five years. The scope of the study was the southeastern United States of America. As might be hypothesized, the chainsaw was the most hazardous type of tree-harvesting equipment. It accounted for 55％ of the tree-harvesting accidents. Most chainsaw accidents resulted in injuries to the lower extremities and were more frequent among younger employees. The probability of one or more chainsaw accidents occurring in any 30-day period was approximately 0.856. Chainsaw accidents were more likely to occur in late morning and early afternoon. We used statistical tools such as Pareto charts, c-charts and Ishikawa diagrams. Such tools are useful in diagnosing the root-cause of tree-harvesting worker accidents and help in developing preventive safety programs. Recommendations to help improve the quality of information of accident data collected by insurance companies and others are briefly given. The strategy and culture of continuous process improvements are stressed.

• Journal of Welding and Joining
• /
• v.20 no.2
• /
• pp.102-108
• /
• 2002

Resistance spot welding of aluminum alloys is based upon Joule heating of the components by passing a large current in a short duration. Since aluminum alloys have the potential to replace steels fur automobile body assemblies, it is important to study the process robustness of aluminum spot welding process. In order to evaluate the effects of process parameters on the weld quality, major process variables and abnormal process conditions were selected and analyzed. A newly developed two-stage, sliding-level experiment was adopted fur effective parameter design and analysis. Suitable ranges of welding current and button diameters were obtained through the experiment. The effects of the factors and their levels on the variation of acceptable welding current were considered in terms of main effects. From the results, it is concluded that any abnormal process condition decreases the suitable current range in the weld lobe curve. Pareto analysis of variance was also introduced to estimate the significant factors on the signal-to-noise (S/N) ratio. Among the six factors studied, fit-up condition is found to be the most significant factor influencing the SM ratio. Using a Pareto diagram, the optimal condition is determined and the SM ratio is significantly improved using the optimal condition.

• Journal of Wetlands Research
• /
• v.17 no.3
• /
• pp.251-263
• /
• 2015

This study suggested a novel approach of estimating the optimal probability density function (OPDF) of the annual maximum rainfall time series (AMRT) combining the L-moment ratio diagram and the geographical information system. This study also reported several interesting geographical characteristics of the AMRT in Korea. To achieve this purpose, this study determined the OPDF of the AMRT with the duration of 1-, 3-, 6-, 12-, and 24-hours using the method of L-moment ratio diagram for each of the 67 rain gages in Korea. Then, a map with the Thiessen polygons of the 67 rain gages colored differently according the different type of the OPDF, was produced to analyze the spatial trend of the OPDF. In addition, this study produced the color maps which show the fitness of a given probability density function to represent the AMRT. The study found that (1) both L-skewness and L-kurtosis of the AMRT have clear geographical trends, which means that the extreme rainfall events are highly influenced by geography; (2) the impact of the altitude on these two rainfall statistics is greater for the mountaneous region than for the non-mountaneous region. In the mountaneous region, the areas with higher altitude are more likely to experience the less-frequent and strong rainfall events than the areas with lower altitude; (3) The most representative OPDFs of Korea except for the Southern edge are Generalized Extreme Value distribution and the Generalized Logistic distribution. The AMRT of southern edge of Korea was best represented by the Generalized Pareto distribution.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2002.10a
• /
• pp.225-228
• /
• 2002

This research seeks to derive the design rainfalls through the L-moment with the test of homogeneity, independence and outlier of data on annual maximum daily rainfall in 38 Korean rainfall stations. To select the fit appropriate distribution of annual maximum daily rainfall data according to rainfall stations, applied were Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) probability distributions were applied. and their aptness was judged Dusing an L-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test, the aptitude was judged of applied distributions such as GEV, GLO and GPA. The GEV and GLO distributions were selected as the appropriate distributions. Their parameters were estimated Targetingfrom the observed and simulated annual maximum daily rainfalls and using Monte Carlo techniques, the parameters of GEV and GLO selected as suitable distributions were estimated and. dDesign rainfallss were then derived, using the L-moment. Appropriate design rainfalls were suggested by doing a comparative analysis of design rainfall from the GEV and GLO distributions according to rainfall stations.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2004.05b
• /
• pp.1103-1106
• /
• 2004

The objective of this study is to induce the design drought rainfall by the methodology of L-moment including testing homogeneity, independence and outlier of the data of annual minimum monthly rainfall in 57 rainfall stations in Korea in terms of consecutive duration for 1, 2, 4, 6, 9 and 12 months. To select appropriate distribution of the data for annual minimum monthy rainfall by rainfall station, the distribution of generalized extreme value (GEV), generalized logistic (GLO) as well as that of generalized pareto (GPA) are applied and the appropriateness of the applied GEV, GLO, and GPA distribution is judged by L-moment ratio diagram and Kolmogorov-Smirnov (K-S) test. As for the annual minimum monthly rainfall measured by rainfall station and that stimulated by Monte Carlo techniques, the parameters of the appropriately selected GEV and GPA distributions are calculated by the methodology of L-moment and the design drought rainfall is induced. Through the comparative analysis of design drought rainfall induced by GEV and GPA distribution by rainfall station, the optimal design drought rainfall by rainfall station is provided.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2002.10a
• /
• pp.229-232
• /
• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.46 no.3
• /
• pp.31-42
• /
• 2004

This research seeks to derive the design rainfalls through the L-moment with the test of homogeneity, independence and outlier of data on annual maximum daily rainfall at 38 rainfall stations in Korea. To select the appropriate distribution of annual maximum daily rainfall data by the rainfall stations, Generalized Extreme Value (GEV), Generalized Logistic (GLO), Generalized Pareto (GPA), Generalized Normal (GNO) and Pearson Type 3 (PT3) probability distributions were applied and their aptness were judged using an L-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test. Parameters of appropriate distributions were estimated from the observed and simulated annual maximum daily rainfall using Monte Carlo techniques. Design rainfalls were finally derived by GEV distribution, which was proved to be more appropriate than the other distributions.