• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.203-212
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• 2018

Quality requirements of manufactured products or parts are given in the form of specification limits on the quality characteristics of individual units. If a product is to meet the customer's fitness for use criteria, it should be produced by a process which is stable or repeatable. In other words, it must be capable of operating with little variability around the target value or nominal value of the product's quality characteristic. In order to maintain and improve product quality, we need to apply statistical process control techniques such as histogram, check sheet, Pareto chart, cause and effect diagram, or control charts. Among those techniques, the most important one is control charting. The cumulative sum (CUSUM) control charts have been used in statistical process control (SPC) in industries for monitoring process shifts and supporting online measurement. The objective of this research is to apply Taguchi's quality loss function concept to cost based CUSUM control chart design. In this study, a modified quality loss function was developed to reflect quality loss situation where general quadratic loss curve is not appropriate. This research also provided a methodology for the design of CUSUM charts using Taguchi quality loss function concept based on the minimum cost per hour criterion. The new model differs from previous models in that the model assumes that quality loss is incurred even in the incontrol period. This model was compared with other cost based CUSUM models by Wu and Goel, According to numerical sensitivity analysis, the proposed model results in longer average run length in in-control period compared to the other two models.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• International Journal of Highway Engineering
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• v.17 no.1
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• pp.129-142
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• 2015

PURPOSES : The purpose of this study is to suggest a basis for setting appropriate safety goals specifically related to the threshold zone luminance in a vehicular traffic tunnel. METHODS : In the test, drivers were divided into two groups. One group consisted of all drivers (average drivers) group with an age ratio of drivers holding domestic driver's license and driver group by age to produce threshold zone luminance in the tunnel. The threshold zone luminance produced as a result was used to analyze how it affects the safety level of each driver group and provide a basis for setting an appropriate safety criterion that can be used to determine threshold zone luminance. We used test equipment, test conditions, and ananalysis of threshold zone luminance identical to that reported by ChoandJung(2014) but the values of adaptation luminance in our analys is were expanded to range from100 to $10,000cd/m^2$. RESULTS : Adaptation luminance and threshold zone luminance are found to be related by a quadratic function. The threshold zone luminance needed by older drivers to ensure a certain safety level is significantly higher than that for drivers of other age brackets when adaptation luminance increases. 56% of older drivers are at an increased risk of an accident at the same luminance for which the safety level of average drivers is 75%. The safety level that can be achieved for older drivers increases to above 60% when threshold zone luminance level is set with the goal of attaining a safety level of more than 85% for average drivers. The safety level that can be attained for average drivers is above 90% when the threshold zone luminance is high enough to ensure over 75% in the safety level of older drivers. Results of this study are applicable to highways and others whose designed speed is 100 km/h. CONCLUSIONS : Threshold zone luminance determined on the basis of drivers having average visual ability is of limited value as a performance standard for ensuring the safety of older drivers. Hence, safety level for older drivers should be considered separately from safety levels for drivers with an average ability to avoid risk. Upward adjustment of older drivers' safety level in the process of determining appropriate threshold zone luminance in a vehicular traffic tunnel may bring both tangible and intangible benefit as a result of reducing accidents. However, there is an associated dollar cost arising from installing and operating lights. As a result, the economic impact of these trade-offs should also be considered.