• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.29-37
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• 2017

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises' sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.2
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• pp.92-98
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• 2002

It is necessary to measure the solar cell parameter fur understanding characteristic of solar cell and applying to many other fields. Since photovoltaic system consists of solar cell module, which are connected each other in series and parallel, it is not proper to apply a solar cell parameter to photovoltaic system. Therefore, to estimate the solar tell module and to solve the problem of the established algorithm is on demand. In this paper the authors have improved the accuracy of solar cell module Parameter estimation by compensating series and Parallel resistance, and developed a new parameter estimation algorithm, which can be applied to photovoltaic system without high cost measuring equipment. And the validity of proposed algorithm is verified by the simulation and experimentation.

• Asia Marketing Journal
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• v.22 no.2
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• pp.1-18
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• 2020

We estimate a choice-based aggregate demand model accounting for consumers' consideration sets, and study its implications on market structure. In contrast to past research, we model and estimate consumer demand using aggregate-level consumer browsing data in addition to aggregate-level choice data. The use of consumer browsing data allows us to study consumer demand in a realistic setting in which consumers choose from a subset of products. We calibrate the proposed model on both data sets, avoid biases in parameter estimates, and compute the price elasticity measures. As an empirical application, we estimate consumer demand in the camcorder category and study its implications on market structure. The proposed model predicts a limited consumer price response and offers a more discriminating competitive landscape from the one assuming universal consideration set.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1291-1314
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• 2016

The paper presents the development of experimental fragility functions for exterior RC beam-column connections based on results obtained from extensive testing carried out in the present study. Three typical types of seismically deficient beam-column connections, which are commonly prevalent in Indian sub-continent, were considered. These specimens were tested under cyclic displacement histories with different characteristics to induce different damage states. Rehabilitation specific fragility functions for damaged specimens were developed considering drift angle as a demand parameter. Four probability distributions were fit to the data and suitability of each distribution was evaluated using standard statistical method. Specimens with different damage states were rehabilitated appropriately and rehabilitated specimens were tested under similar displacement histories. Fragility functions for rehabilitated specimens have also been developed following similar procedure. Comparison of fragility functions for both original and rehabilitated specimens for each rehabilitation method showed close agreement, which establishes the effectiveness of the adopted rehabilitation strategies and hence would provide confidence in field application.

• Earthquakes and Structures
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• v.21 no.6
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• pp.627-639
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• 2021

Fragility curves are being more significant as a useful tool for evaluating the relationship between the earthquake intensity measure and the effects of the engineering demand parameter on the buildings. In this paper, the effect of different site conditions on the vulnerability of the structures was examined through the fragility curves taking into account different strength capacities of the precast columns. Thus, typical existing single-story precast RC industrial buildings which were built in Turkey after the year 2000 were examined. The fragility curves for the three typical existing industrial structures were derived from an analytical approach by performing non-linear dynamic analyses considering three different soil conditions. The Park and Ang damage index was used in order to determine the damage level of the members. The spectral acceleration (Sa) was used as the ground motion parameter in the fragility curves. The results indicate that the fragility curves were derived for the structures vary depending on the site conditions. The damage probability of exceedance values increased from stiff site to soft site for any Sa value. This difference increases in long period in examined buildings. In addition, earthquake demand values were calculated by considering the buildings and site conditions, and the effect of the site class on the building damage was evaluated by considering the Mean Damage Ratio parameter (MDR). Achieving fragility curves and MDR curves as a function of spectral acceleration enables a quick and practical risk assessment in existing buildings.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.50-58
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• 2018

Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston's method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecasting because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston's method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands' interval separately, as in Croston's method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.

• Earthquakes and Structures
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• v.26 no.2
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• pp.117-130
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• 2024

Probabilistic model of seismic demand is the main tool used for seismic demand estimation, which is a fundamental component of the new performance-based design method. This model seeks to mathematically relate the seismic demand parameter and the ground motion intensity measure. This study is intended to use Bayesian analysis to evaluate the accuracy of the seismic demand estimation of Steel moment resisting frames (SMRFs) through a completely Bayesian method in statistical calculations. In this study, two types of intensity measures (earthquake intensity-related indices such as magnitude and distance and intensity indices related to ground motion and spectral response including peak ground acceleration (PGA) and spectral acceleration (SA)) have been used to form the models. In addition, an extensive database consisting of sixty accelerograms was used for time-series analysis, and the target structures included five SMRFs of three, six, nine, twelve and fifteen stories. The results of this study showed that for low-rise frames, first mode spectral acceleration index is sufficient to accurately estimate demand. However, for high-rise frames, two parameters should be used to increase the accuracy. In addition, adding the product of the square of earthquake magnitude multiplied by distance to the model can significantly increase the accuracy of seismic demand estimation.

• Journal of Korean Society of Transportation
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• v.14 no.3
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• pp.7-26
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• 1996

The estimation of real-time Origin-Destination(O-D) parameters, which gives travel demand between combinations of origin and destination points on a urban freeway network, from on-line surveillance traffic data is essential in developing an efficient ATMS strategy. On this need a real-time O-D parameter estimation model is formulated as a parameter adaptive filtering model based on the extended Kalman Filter. A Monte Carlo test have shown that the estimation of time-varying O-D parameter is possible using only traffic counts. Tests with field data produced the interesting finding that off-ramp volume predictions generated using a constant freeway O-D matrix was replaced by real-time estimates generated using the parameter adaptive filter.

• Journal of Institute of Convergence Technology
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• v.1 no.1
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• pp.41-47
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• 2011

With the world-wide demand on the emission minimization, the needs on the diesel aftertreatment devices with high efficiency are also increasing. In order to effectively develop or design a high-performance diesel particulate filter, a clear understanding on the deposition and regeneration mechanism is required. In the present study, a theory on the lumped parameter model for wall-flow type diesel particulate filters is described focusing on the deposition efficiency, pressure drop inside the filter. The fourth order explicit Runge-Kutta method is utilized for the mass flow rate computation. Engine operation modes with controlled and uncontrolled regeneration options are selected. The computational lumped parameter model is validated by comparing the computed results with the measured data.

• Journal of Distribution Science
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• v.10 no.11
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• pp.31-37
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• 2012

Purpose - This study was conducted under the assumption that brand A, a store of company Z of Pangyo, with a new store at Pangyo station is targeting the Bundang-gu area of the newly developed city of Seongnam. Research design, data, methodology - As a result of demand forecasting using geometric series models, an extrapolation of past trends provided the coefficient estimates, without utilizing regression analysis on a constant increase in children's wear, for which the population size and estimated parameter were required. Results - Demand forecasting on the basis of past trends indicates the likelihood that sales of discount stores in the Bundang area, where brand A currently has a presence, would fetch a higher estimated value than that of the average discount store in the country during 2015. If past trends persist, future sales of operational stores are likely to increase. Conclusions - In evaluating location using the simple weighting model, Seohyun Lotte Mart obtained a high rating amongst new stores in Pangyo, on the basis of accessibility, demand class, and existing stores. Therefore, when opening a new counter at a relevant store, a positive effect can be predicted.