• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.93-100
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• 2004

For accurate construction contract time estimation, few parameters are more significant than crew production rates and factors affecting the rates. However, statistical analysis techniques for finding such factors are not always simple mainly because there are many factors and the interaction between factors is not well quantitatively understood. This paper presents methodology of identifying factors driving crew production rates. The methodology is further demonstrated with representative data collected by the author from 13 on-going highway constructions. Three factors were identified as statistically significant drivers of Cap crew production rate: 'Cap Size (m3/ea)'; 'Cap Length (m)'; and 'Cap Shape (Rectangle vs. Inverted 'T')'. It was also found that the production rates are best explained by a multiple regression model with two of the drivers; 'Cap Size' and 'Cap Shape'.

• Communications for Statistical Applications and Methods
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• v.23 no.5
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• pp.399-409
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• 2016

Many of studies have suggested the modifications on Weibull distribution to model the non-monotone hazards. In this paper, we combine two cumulative hazard functions and propose a new modified Weibull distribution function. The newly suggested distribution will be named as a new flexible Weibull distribution. Corresponding hazard function of the proposed distribution shows flexible (monotone or non-monotone) shapes. We study the characteristics of the proposed distribution that includes ageing behavior, moment, and order statistic. We also discuss an estimation method for its parameters. The performance of the proposed distribution is compared with existing modified Weibull distributions using various types of hazard functions. We also use real data example to illustrate the efficiency of the proposed distribution.

• Journal of the Korean Statistical Society
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• v.13 no.1
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• pp.48-56
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• 1984

This paper considers one-sample and two-sample test for the logistic function by means of Kolmororov-Smirnov type statistics. The standard tables used for the Kolmogorov-Smirnov test are valid only when the function is completely specified; but they are not valid if the parameters of function are estimated from the sample. This note presents modified tables for the Kolmogorov-Sminov type staistic. These tables can be used to test the hypothesis that a sample comes from a logistic function when shape parameter $(\alpha)$ and location parameter $(\beta)$ must be estimated from the sample by the method of maximum likelihood. Monte Carlo method is employed to calculate the criticla values of the test. The tables of the critical values are provided.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.83-91
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• 2018

This paper suggests a weibull time delay model to evaluate failure risks in FMEA(failure modes and effects analysis). Assuming three types of loss functions for delayed time in failure cause detection, the risk of each failure cause is evaluated as its occurring frequency and expected loss. Since the closed form solution of the risk metric cannot be obtained, a statistical computer software R program is used for numerical calculation. When the occurrence and detection times have a common shape parameter, though, some simple results of mathematical derivation are also available. As an enormous quantity of field data becomes available under recent progress of data acquisition system, the proposed risk metric will provide a more practical and reasonable tool for evaluating the risks of failure causes in FMEA.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.34-40
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• 2002

Machining accuracy is affected by quasi-static errors of machining center. Since machine errors have a direct influence upon both the surface finish and geometric shape of the finished workpiece, it is very important to measure the machine errors and to compensate these errors. The laser measurement method for identifying geometric errors of machine tool has the disadvantages such as high cost, long calibration time and usage of volumetric error synthesis model. Accordingly, this paper deals with analysis of the geometric errors of a machine tool using ball bar test without using complicated error synthesis model. Statistical analysis method was adopted in this paper for deriving geometric errors using hemispherical helix ball bar test. As a result of experiment, geometric errors of the vertical machining center are compensated by 88%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.9
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• pp.1305-1310
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• 2010

In a practical design process, the method of extracting the design space information of the complex system for verifying, improving, and optimizing the design process by taking into account the design variables and their shape tolerance is very important. Finite element analysis has been successfully implemented and integrated with design of experiment such as D-Optimal array; thus, a response surface model and optimization tools have been obtained, and design variables can be optimized by using the model and these tools. Then, to guarantee the robustness of the design variables, a robust design should be additionally performed by taking into account the statistical variation of the shape tolerance of the optimized design variables. In this study, a new approach based on the use of the response surface model is proposed; in this approach, the standard normal distribution of the shape tolerance is considered. By adopting this approach, it is possible to simultaneously optimize variables and perform a robust design. This approach can serve as a means of efficiently modeling the trade-off among many conflicting goals in the applications of finite element analysis. A case study on the robust optimal design of disc brakes under thermal loadings was carried out to solve multiple objective functions and determine the constraints of the design variables, such as a thermal deformation and weight.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.5
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• pp.117-124
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• 2011

Tire's performance plays important roles in improving vehicle's performances. Tire makers carry out a lot of research to improve tire's performance. They are making effort to meet multi purposes using various optimization methods. Recently, the tire makers perform the shape optimization using approximation models, which are surrogate models obtained by statistical method. Generally, the reason why we increase sampling points during optimization process, is to get more reliable approximation models, but the more we adopt sampling points, the more we need time to test. So it is important to select approximation model and proper number of sampling points to balance between reliability and time consuming. In this research, we studied to compare two kind cases for a approximation construction. First, we compare RSM and Kriging which are Curve Fitting Method and Interpolation Method, respectively. Second, we construct approximation models using three different number of sampling points. And then, we recommend proper approximation model and orthogonal array adopt tire's design optimization.

• Fashion & Textile Research Journal
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• v.12 no.6
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• pp.812-820
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• 2010

The objectives of this study were to classify the head shapes of Korean men and to suggest computer tomography as a new body measurement method. The 23 head measurement items of 760 men, aged more than 18 in Sizekorea 2004 database were used to analyze, measured by using statistical methods. Factor analysis, cluster analysis and duncan test were performed using these data. Through factor analysis, 5 factors were extracted upon factor scores and those factors comprised 70.91% for the total variances. The head and face shapes were categorized as 5 types-triangle, round, oval, long, rectangle. We decided for the type 1(triangle) to standard head shape since this type was the most observed. 21 participants were measured using computed tomography(CT). The measured data of skin and skeleton and the standard head shapes were illustrated.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.372-378
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• 2005

Finite element analysis of concrete slab system in apartment building was executed using the tables of orthogonal arrays, and optimal design process was proposed. At first, experimental results show that sound peak components to influence the overall level and the rating of floor impact sound insulation were coincident with natural frequencies of the reinforced concrete slab. Finite element model of concrete slab was compared with experimental results, and well corresponded with an error of less than 10%. The tables of orthogonal arrays were used for finite element analysis with 8 factors. 3 related to material properties and 5 related to slab shape parameters and its results were analyzed by statistical method, ANOVA. The most effective factor among them was slab thickness, and main effect factor from slab shape parameters was different from each natural frequency. The interaction was found in the higher mode over $3^{rd}$ natural frequency. From main effect plot and interaction plot, the optimal design factor to increase the natural frequency was determined.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.441-447
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• 2022

In this paper, we propose a pill identification model using engraved text feature and image feature such as shape and color, and compare it with an identification model that does not use engraved text feature to verify the possibility of improving identification performance by improving recognition rate of the engraved text. The data consisted of 100 classes and used 10 images per class. The engraved text feature was acquired through Keras OCR based on deep learning and 1D CNN, and the image feature was acquired through 2D CNN. According to the identification results, the accuracy of the text recognition model was 90%. The accuracy of the comparative model and the proposed model was 91.9% and 97.6%. The accuracy, precision, recall, and F1-score of the proposed model were better than those of the comparative model in terms of statistical significance. As a result, we confirmed that the expansion of the range of feature improved the performance of the identification model.