• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.57-65
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• 2008

Available-to-promise (ATP) exhibiting availability of manufacturing resources can be used to support customer order promising. Recently, one advanced function called Capable-to-promise (CTP) is provided by several modern APS (advanced planning system) that checks available capacity for placing new production orders or increasing already scheduled production orders. At the customer enquiry stage while considering the order delivery date and quantity to quote, both ATP and CTP are allocated to support order promising. In particular, current trends of mass customization and multi-side production chain derive several new constraints that should be considered when ATP/CTP allocation planning for order promising - such as customer's preference plants or material vendors, material compatibility, etc. Moreover, ATP/CTP allocation planning would be executed over a rolling time horizon. To utilize capacity and material manufacturing resource flexibly and fulfill more customer orders, ATP/CTP rolling planning should possess resource reallocation mechanism under the constraints of order quantities and delivery dates for all previous order promising. Therefore, to enhance order promising with reliability and flexibility to reallocate manufacturing resource, the ATP/CTP reallocation planning mechanism is needed in order to reallocate material and capacity resource for fulfilling all previous promised and new customer orders beneficially with considering new derived material and capacity constraints.

• Carbon letters
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• v.9 no.3
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• pp.181-187
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• 2008

Batch sorption experiments were carried out for the removal of metylene blue from its aqueous solution using $H_3PO_4$ activated Acacia arabica carbon (AAC). The prepared activated carbon was characterized and was found as an effective adsorbent material. The operating variables studied were initial metylene blue concentration, AAC concentration and solution pH. AAC activated carbon posses a maximum sorption capacity for the range of initial dye concentrations studied (60~100 mg $L^{-1}$). The sorption kinetics were analyzed using reversible first order kinetics, second order, reversible first order, pseudo-first order, and pseudo-second order model. The sorption data tend to fit very well in pseudo-second order model for the entire sorption time. The average pseudo-second order rate constant, $K_{II}$ and regression coefficient value were determined to be 0.0174 mg $g^{-1}$ $min^{-1}$ and 0.9977. The biosorption process also fit well to reversible I order kinetics with a regression coefficient of 0.9878.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.83-89
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• 2004

In this paper MIP(mean inventory period) Model and OMMIP decision flow have been developed. MIP model can calculate mean inventory period which is subject to the order quantity alternative plan. OMMIP decision flow leads how can decide the most minimized order quantity in mean inventory period among various order quantity alternatives. This paper also suggests how to select the order quantity with minimum inventory period as optimal order quantity by means of comparison each mean inventory period with other mean inventory period, after simulating EOQ and order quantity of OMMIP calculated in MIP model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.50-53
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• 1999

It has been pointed out in the literature that the Routh approximation method for order reduction has limitations in treating transfer functions with the denominator-numerator order difference not equal to one. The purpose of this paper is to present a new algorithm based on the Routh approximation method that can be applied to general rational transfer functions, yield ing reduced models with arbitrary order.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.64-70
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• 2013

Estimation approaches for casual relation model with high-order factors have strict restrictions or limits. In the case of ML (Maximum Likelihood), a strong assumption which data must show a normal distribution is required and factors of exponentiation is impossible due to the uncertainty of factors. To overcome this limitation many PLS (Partial Least Squares) approaches are introduced to estimate the structural equation model including high-order factors. However, it is possible to yield biased estimates if there are some differences in the number of measurement variables connected to each latent variable. In addition, any approach does not exist to deal with general cases not having any measurement variable of high-order factors. This study compare several approaches including the repeated measures approach which are used to estimate the casual relation model including high-order factors by using PLS (Partial Least Squares), and suggest the best estimation approach. In other words, the study proposes the best approach through the research on the existing studies related to the casual relation model including high-order factors by using PLS and approach comparison using a virtual model.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1863-1871
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• 2016

This paper presents an application of fractional order controller for the control of multi input multi output twin rotor aerodynamic system. Dynamics of the considered system are highly nonlinear and there exists a significant cross-coupling between the horizontal and vertical axes (pitch & yaw). In this paper, a fractional order model of twin rotor aerodynamic system is identified using input output data from nonlinear system. Based upon identified fractional order model, a fractional order PID controller is designed to control the angular position of level bar of twin rotor aerodynamic system. The parameters of controller are tuned using Nelder-Mead optimization and compared with particle swarm optimization techniques. Simulation results on the nonlinear model show a significant improvement in the performance of fractional order PID controller as compared to a classical PID controller.

• Structural Engineering and Mechanics
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• v.45 no.5
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• pp.595-611
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• 2013

This paper aims to compare three collocation point methods associated with the odd order stochastic response surface method (SRSM) in a systematical and quantitative way. The SRSM with the Hermite polynomial chaos is briefly introduced first. Then, three collocation point methods, namely the point method, the root method and the without origin method underlying the odd order SRSMs are highlighted. Three examples are presented to demonstrate the accuracy and efficiency of the three methods. The results indicate that the condition that the Hermite polynomial information matrix evaluated at the collocation points has a full rank should be satisfied to yield reliability results with a sufficient accuracy. The point method and the without origin method are much more efficient than the root method, especially for the reliability problems involving a large number of random variables or requiring complex finite element analysis. The without origin method can also produce sufficiently accurate reliability results in comparison with the point and root methods. Therefore, the origin often used as a collocation point is not absolutely necessary. The odd order SRSMs with the point method and the without origin method are recommended for the reliability analysis due to their computational accuracy and efficiency. The order of SRSM has a significant influence on the results associated with the three collocation point methods. For normal random variables, the SRSM with an order equaling or exceeding the order of a performance function can produce reliability results with a sufficient accuracy. The order of SRSM should significantly exceed the order of the performance function involving strongly non-normal random variables.

• ETRI Journal
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• v.37 no.4
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• pp.727-735
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• 2015

This paper deals with the problem of blind source separation (BSS), where observed signals are a mixture of delayed sources. In reference to a previous work, when the delay time is small such that the first-order Taylor approximation holds, delayed observations are transformed into an instantaneous mixture of original sources and their derivatives, for which an extended second-order blind identification (SOBI) approach is used to recover sources. Inspired by the results of this previous work, we propose to generalize its first-order Taylor approximation to suit higher-order approximations in the case of a large delay time based on a similar version of its extended SOBI. Compared to SOBI and its extended version for a first-order Taylor approximation, our method is more efficient in terms of separation quality when the delay time is large. Simulation results verify the performance of our approach under different time delays and signal-to-noise ratio conditions, respectively.

• IE interfaces
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• v.15 no.4
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• pp.382-390
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• 2002

This paper deals with planning of order-picking warehouse considering the batch order picking for transportation equipments to pick consumers' orders at a time among order-picking methods and a systematic approach method in order to analyze the order-picking warehouse which can perform optimal operation. To estimate an operating time of transportation equipments to carry out order-picking, this paper suggests three operations : first, to design the refrigerated warehouse using warehouse design parameters, second, to calculate the travel time of transporters considering four types of times with the probabilistic picking frequency, and third, to analyze an order-picking warehouse to construct a simulation model with the AutoMod as a simulation tool. We apply this model to a refrigerated warehouse company in Busan.