• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.283-290
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• 2014

In the flat panel display industry, to meet production target quantities and the deadline of production, the scheduler and dispatching systems are major production management systems which control the order of facility production and the distribution of WIP (Work In Process). Especially the delivery time is a key factor of the dispatching system for the time when a lot can be supplied to the facility. In this paper, we use survival analysis methods to identify main factors of the delivery time and to build the delivery time forecasting model. To select important explanatory variables, the cox proportional hazard model is used to. To make a prediction model, the accelerated failure time (AFT) model was used. Performance comparisons were conducted with two other models, which are the technical statistics model based on transfer history and the linear regression model using same explanatory variables with AFT model. As a result, the mean square error (MSE) criteria, the AFT model decreased by 33.8% compared to the statistics prediction model, decreased by 5.3% compared to the linear regression model. This survival analysis approach is applicable to implementing the delivery time estimator in display manufacturing. And it can contribute to improve the productivity and reliability of production management system.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1588-1593
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• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.658-663
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• 2003

A process of 3-D stereo particle image velocimetry(PIV)was developed for the measurement of an illuminated sliced section field of 3-D complex flows. The present method includes modeling of camera by a calibrator based on the homogeneous coordinate system, transformation of the oblique-angled image to the right-angled image, identification of 2-D velocity vectors by 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criteria, and finally 3-D display as the post processing. An experimental system was also used for the application of the proposed method. Two high speed digital CCD cameras and an Argon-Ion Laser for the illumination were adopted to clarify the time-dependent characteristics of the leading edge extension(LEX) in a highly swept shape applied to a delta wing found in modern air-fighters.

• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.100-105
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• 2000

Quality sorting of cut flowers is very essential to increase the value of products. There are many factors that determine the quality of cut flowers such as length, thickness, and straightness of stem, and color and maturity of bud. Among these factors, the straightness of stem and the maturity of bud are generally considered to be more difficult to evaluate. A prototype grading and sorting machine for cut flowers was developed and tested for a rose variety. The machine consisted of a chain-drive feed mechanism, a pneumatic discharge system, and a grading system utilizing color image processing and neural network. Artificial neural network algorithm was utilized to grade cut roses based on the straightness of stem and maturity of bud. Test results showed 89% agreement with human expert for the straightness of stem and 90% agreement for the maturity of bud. Average processing time for evaluating straightness of the stem and maturity of the bud were 1.01 and 0.44 second, respectively. Application of neural network eliminated difficulties in determining criteria of each grade category while maintaining similar level of classification error.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.16 no.2
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• pp.91-100
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• 2006

The purpose of this study was to validate alternative method by using non-carcinogenic, and less toxic solvents than NIOSH analytical method 5524 for measuring the airborne MWFs in workplaces. In laboratory tests, the ETM solvents(mixture of same volume for ethyl ether, toluene, and ethanol) were selected. The alternative method of analyzing MWFs, referred to as the ETM solvent extraction method, showed 0.04 mg/sample as LOD, and 0.15 mg/sample as LOQ. The analytical precision (pooled CV, coefficient of variation) of the ETM solvent extraction method for analyzing the straight, soluble, semisynthetic, and synthetic metalworking fluid was 1.5%, 2.0%, 2.6%, 1.6%, respectively, which was similar to the precision (2.6%) of NIOSH analytical method (NIOSH 0500) for total dust. The analytical accuracy by recovery test, spiked mass calculated as extractable mass, was almost 100%. As the result of storage stability test, metalworking fluid samples should be stored in refrigerated condition, and be analyzed in two weeks after sampling. The 95% confidence limit of the estimated total standard error for the ETM solvent extraction method for analyzing the straight, soluble, semisynthetic, and synthetic metalworking fluid was ${\pm}12.6%$, ${\pm}12.5%$, ${\pm}14.0%$, and ${\pm}13.6%$, respectively, which satisfied the OSHA sampling and analytical criteria.

• Journal of the korean Society of Automotive Engineers
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• v.14 no.1
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• pp.25-37
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• 1992

Interior noise in a car is known to have an important influence on product acceptability. This noise is closely correlated with structural-acoustic vibration. When considering noise problem, the structural-acoustic relation of a vehicle cabin model needs to be identified. However, it is very difficult to get the modal parameters of this kind of cabin structure composed of thin plates: because it not only can be excited by the acoustic vibration of cavity, but also tends to have decoupling effects of one plate from another. In order to obtain modal parameters more precisely, various excitation techniques, i.e. impact, pure random, burst random, and swept sine testing are applied for the first step. In the case of the cabin model, impact and swept sine testing show good results. Next, the determination of the excitation point by trial- and-error and the accurate measurements of FRF's are performed with these methods. The modal parameter extraction is carried out for the final step. This paper proposes a new approach to find the modal parameters more reliably in the case of high decoupling effects. That is, the convergence of MIF and MCF in each panel, which provide some criteria for the validity of the obtained modal parameters, is observed. And from those results, the pretty accurate modal parameters can be determined. A comparative assessment between the modal testing and the FEM is also performed.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.64-69
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• 2012

Head injury is one of the most common cause of deaths in car-to-pedestrian collisions. To reduce the severity of such injuries, many international safety committees have performed headform impact test for pedestrian protection. In this paper, an adult headform impactor model is developed based on the finite element (FE) method and validated through the numerical simulation. The skin material of headform impactor is known as polyvinyl chloride skin (PVC) and its material was assumed as viscoelastic. The viscoelastic parameters of headform skin are identified by a series of trial and error methods. The new developed FE adult headform impactor is verified by the drop test and FE JARI adult headform impactor provided by Madymo program.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.195-200
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• 2002

ART (Adaptive Resonance Theory [1]) neural network and its variations perform non-hierarchical clustering by unsupervised learning. We propose a scheme "arboART" for hierarchical clustering by using several ART1.5-SSS networks. It classifies multidimensional vectors as a cluster tree, and finds features of clusters. The Basic idea of arboART is to use the prototype formed in an ART network as an input to other ART network that has looser distance criteria (Ishihara, et al., [2,3]). By sending prototype vectors made by ART to one after another, many small categories are combined into larger and more generalized categories. We can draw a dendrogram using classification records of sample and categories. We have confirmed its ability using standard test data commonly used in pattern recognition community. The clustering result is better than traditional computing methods, on separation of outliers, smaller error (diameter) of clusters and causes no chaining. This methodology is applied to Kansei evaluation experiment data analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.3
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• pp.238-247
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• 2007

Genetic Algorithms(GA) which searches optimum solution using natural selection and the law of heredity has been applied to learning algorithms in order to estimate performance deterioration of the aircraft gas turbine engine. The compressor, gas generator turbine and power turbine are considered for engine performance deterioration and estimation for performance deterioration of a single component at design point was conducted. As a result of that, defect diagnostics has been conducted. The input criteria for the genetic algorithm to guarantee the high stability and reliability was discussed as increasing learning data sets. As a result, the accuracy of defect estimation and diagnostics were verified with its RMS error within 3%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.1A
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• pp.10-17
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• 2000

In this paper, we evaluate the correlation properties and the optimization of PN sequence phase for multi-media DS/CDMA system with variable spreading gain (VSG) scheme. In multi-media multi-rate DS/CDMA systems, the optimization of PN sequence phase is not a tractable problem, since the sequences should be optimized against both sequences of the same length and other sequences with different length. Hence, we verify the correlation properties of PN sequence phase in multi-rate system environment and furthermore, we propose the new phase criterion, MIN-AIP (minimum-average interference parameter), to minimize the bit error rate (BER). As the results of performance evaluations, it is shown that the performance of MIN-AIP criteria gives the best results.