• Communications of the Korean Mathematical Society
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• v.26 no.3
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• pp.515-530
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• 2011

This paper deals with the existence result of solutions of a second order functional differential inclusion, governed by a class of nonconvex sweeping process, with a nonconvex perturbation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.1
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• pp.8-16
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• 1986

For digital process control, a low order discrete time modeling method is suggested and a direct digital control algorithm has been developed. The modeling method maintains process order of 3, while the sampling rate is doubled for fast response. With easy calculation it is possible to compute the model parameters and the controller gains. Controller tuning is possible on the spot. Simulation results show that this method has better performance than the deadbeat control agorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.106-116
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• 2016

MTO (Make to Order) is a manufacturing process in which manufacturing starts only after a customer's order is received. Manufacturing after receiving customer's orders means to start a pull-type supply chain operation because manufacturing is performed when demand is confirmed, i.e. being pulled by demand (The opposite business model is to manufacture products for stock MTS (Make to Stock), which is push-type production). There are also BTO (Build to Order) and ATO (Assemble To Order) in which assembly starts according to demand. Lean manufacturing by MTO is very efficient system. Nevertheless, the process industry, generally, which has a high fixed cost burden due to large-scale investment is suitable for mass production of small pieces or 'mass customization' defined recently. The process industry produces large quantities at one time because of the lack of manufacturing flexibility due to long time for model change or job change, and high loss during line-down (shutdown). As a result, it has a lot of inventory and costs are increased. In order to reduce the cost due to the characteristics of the process industry, which has a high fixed cost per hour, it operates a stock production system in which it is made and sold regardless of the order of the customer. Therefore, in a business environment where the external environment changes greatly, the inventory is not sold and it becomes obsolete. As a result, the company's costs increase, profits fall, and it make more difficult to survive in the competition. Based on the customer's order, we have built a new method for order system to meet the characteristics of the process industry by producing it as a high-profitable model. The design elements are designed by deriving the functions to satisfy the Y by collecting the internal and external VOC (voice of customer), and the design elements are verified through the conversion function. And the Y is satisfied through the pilot test verified and supplemented. By operating this make to order system, we have reduced bad inventories, lowered costs, and improved lead time in terms of delivery competitiveness. Make to order system in the process industry is effective for the display glass industry, for example, B and C groups which are non-flagship models, have confirmed that the line is down when there is no order, and A group which is flagship model, have confirmed stock production when there is no order.

• Journal of the military operations research society of Korea
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• v.8 no.1
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• pp.99-107
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• 1982

This paper is concerned with the optimality of exponential smoothing applied to the general IMA process with different moving average and differencing orders. Numerical experiments were performed for IMA(m,n) process with various combinations of m and n, and the corresponding forecast errors were compared. Results show that the higher differencing order is more critical to the optimality of exponential smoothing, i.e., the IMA process with the higher moving average order, forecasted by exponential smoothing, has comparatively smaller forecast error. If the difference between the differencing order and the moving average order becomes larger, the accuracy of forecast by exponential smoothing declines gradually.

• Proceedings of the KIPE Conference
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• 1998.11a
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• pp.73-77
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• 1998

The conventional sliding mode controller (SMCr) approach is often impractical or difficult when applied to high order process because the number of tuning parameters in the SMCr increases with the order of the plant. Camacho(1996) proposed the design of a fixed structure sliding mode controller based on a first order plus dead time approximation to the higher-order process. But, there are such problems as overshoot, settling time and command following. They are mainly due to the approximation errors of the time delay term by Taylor series. In this paper, in order to improve Camcho's method, a new Taylor approximation technique considering a weight is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.451-454
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• 1998

This paper proposes a new method of Model Predictive Control (MPC) of nonlinear process by us-ing the measured Volterra kernels as the nonlinear model. A nonlinear dynamical process is usually de-scribed as Volterra kernel representation, In the authors' method, a pseudo-random M-sequence is ar plied to the nonlinear process, and its output is measured. Taking the crosscorrelation between the input and output, we obtain the Volterra kernels up to 3rd order which represent the nonlinear characteristics of the process. By using the measured Volterra kernels, we can construct the nonlinear model for MPC. In applying Model Predictive Control to a nonlinear process, the most important thing is, in general, what kind of nonlinear model should be used. The authors used the measured Volterra kernels of up to 3rd order as the process model. The authors have carried out computer simulations and compared the simulation results for the linear model, the nonlinear model up to 2nd Volterra kernel, and the nonlinear model up to 3rd order Vol-terra kernel. The results of computer simulation show that the use of Valterra kernels of up to 3rd order is most effective for Model Predictive Control of nonlinear dynamical processes.

• The Journal of Society for e-Business Studies
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• v.3 no.2
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• pp.179-202
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• 1998

This study reviews the concept of Integrated Logistic Support(ILS), ILS standards, ILS elements, and the processes of developing ILS elements and Logistics Support Analysis(LSA). It also examines the potentials of applying ILS development process to building CALS systems in commercial sectors in order to accomplish business process innovation and achieve life-cycle cost savings in product and equipment management. In order to utilize the ILS approach for commercial industries, we need customizing the process of Logistics Support Analysis defined in MIL-STD-1388-lA. The success of ILS implementation depends on the determination of the range of ILS elements in relation with the application environment, and the appropriate development of those elements. During the development process, in order to analyze and design logistics flow processes and supporting activities, we suggest the object-oriented logistics process modeling approach with basic concepts and constructs embedded in objects. Several diagrams including Class Diagram, Class-Instance Diagram, and Integrated Instance Diagram, are provided. Simple Steps to follow are suggested for the analysis and design of inter-organizational logistics flow and support processes. The outcomes of the study are expected to contribute to stimulating the utilization of ILS concepts and development process during building commercial CALS systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1062-1070
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• 2018

This paper presents a simple identification method for discrete-time low-order model of unknown delay process from pulse response. The key idea is to find the parameters of the model such that the first N moments of the unknown process and the model are equal. We first show that the k-th moment of a process can be determined by the moments of the input and output. The parameters and delay are estimated separately. It is shown that for a given delay, the parameters of the low-order model can be determined by solving linear equations in a matrix form. Delay of the model is estimated such that the integral of the absolute errors (IAE) of the candidate models with possible delays minimizes. The illustrative example shows that the proposed method can directly identify low-order models without order reduction process from a single pulse response.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.109-122
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• 2003

This paper presents a robust process capability index(PCI) based on the expected loss derived from the empirical distribution function(EDF). We propose the EDF expected loss in order to develop a PCI that does not depends on the underlying process distribution. The EDF expected loss depends only on the sample data, so the PCI based on it is robust and it does nor require complex calculations. The inverted normal loss function(INLF) is employed in order to overcome the drawback of the quadratic loss which may Increase unboundedly outside the specification limits. A comprehensive simulation study was performed under various process distributions, in order to compare the accuracy and the precision of the proposed PCI with those of the PCI based on the expected loss derived from the normal distribution. The proposed PCI turned out to be more accurate than the normal PCI in most cases, especially when the process distribution has high kurtosis or skewness. It is expected that the proposed PCI can be utilized In real processes where the true distribution family may not be known.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.7
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• pp.158-166
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• 1996

In this study, a flexible disk grinding process is applied in order to produce high precision product. A new model was developed considering feed motion along horizontal and vertical direction. Different types of feed speed variation was tested with respect to distinct process stages in order to achieve flat surface. It was observed that highest order polynomial form for both horizontal and vertical feed speed variation among the proposed categories produced surface close to flat one. Disk deflection trend during the process was visualized confirming the proposed scheme. Cutting force and VRR(volume removal rate) was observed as an aid to process planning.