• 경영과학
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• 제13권1호
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• pp.47-55
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• 1996

Rapid globalization of production and marketing functions makes choice of international transportation mode of great importance. In this paper, transportation mode is characterized by two factors, mean and variability of transportation lead time. We developed a simple mathematical model to estimate the relative impact of mean lead time, lead time variance and demand variance on the required average inventory level under specified service rates.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.101-101
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• 2020

Traditional stochastic simulation of hydroclimatological variables often underestimates the variability and correlation structure of larger timescale due to the difficulty in preserving long-term memory. However, the Long Short-Term Memory (LSTM) model illustrates a remarkable long-term memory from the recursive hidden and cell states. The current study, therefore, employed the LSTM model in stochastic generation of hydrologic and climate variables to examine how much the LSTM model can preserve the long-term memory and overcome the drawbacks of conventional time series models such as autoregressive (AR). A trigonometric function and the Rössler system as well as real case studies for hydrological and climatological variables were tested. Results presented that the LSTM model reproduced the variability and correlation structure of the larger timescale as well as the key statistics of the original time domain better than the AR and other traditional models. The hidden and cell states of the LSTM containing the long-memory and oscillation structure following the observations allows better performance compared to the other tested conventional models. This good representation of the long-term variability can be important in water manager since future water resources planning and management is highly related with this long-term variability.

• 품질경영학회지
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• 제32권2호
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• pp.201-211
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• 2004

Process adjustment is a complimentary tool to process monitoring in process control. Process adjustment directs on maintaining a process output close to a target value by manipulating another controllable variable, by which significant process improvement can be achieved. Therefore, this approach can be applied to the 'Improve' stage of Six Sigma strategy. Though the optimal control rule minimizes process variability in general, it may not properly function when special causes occur in underlying process, resulting in off-target bias and increased variability in the adjusted output process, possibly for long periods. In this paper, we consider a responsive feedback control system and the minimum mean square error control rule. The bias in the adjusted output process is investigated in a general framework, especially focussing on stationary underlying process and the special cause of level shift type. Illustrative examples are employed to illustrate the issues discussed.

• 품질경영학회지
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• 제36권3호
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• pp.102-111
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• 2008

본 연구에서는 공급리드타임이 한정된 용량을 가진 생산시스템에 의해서 내부적으로 결정되어지는 다품종 재고시스템에서의 제품의 수요변동이 미치는 영향을 조사하였다. 공급리드타임이 시스템의 외부에서 결정되어 주어지는 경우와는 달리 리드타임 수요의 변동이 제품 수요의 변동이 증가할 때 실제 감소하는 결과를 보였다. 또한, 수요의 변동이 증가할 때 전체 재고 중 안전재고의 비율이 감소되는 것도 보였다. 더 나아가서 수요 변동의 크기가 어느 정도 이상으로 커지면 안전재고가 완전히 제거되는 사실도 입증하였다. 이 같은 결과는 제품수요의 변동이 매우 클 때 리드타임 수요의 변동을 줄이기 위한 전략은 별로 효용이 없음을 보여준다.

• 대한안전경영과학회지
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• 제8권6호
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• pp.119-137
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• 2006

This paper seeks to Combination for Efficient Application of SPC/EPC minimize variability by transferring the output variable to a related process controllable variable, while SPC seeks to reduce variability by detecting and eliminating assignable causes of variation. In the case of product control, a very reasonable objective is to try to minimize the variance of the output deviations from the target or set point. We consider an alternative EPC model with autoregressed disturbance. We compare three control systems; EPC, Cp, SPC combined system with EWMA, CUSUM and Shewhart. This paper shows through simulation that the performance of the integrated model of EPC and SPC, Cp is more preferable than that of EPC.

• 품질경영학회지
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• 제26권4호
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• pp.88-100
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• 1998

Robust design in industry is an a, pp.oach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise raio(SN) to achieve the a, pp.opriate set of operating conditions where variablity around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure in the two different experimental design(product array, combined array) a, pp.oaches.

• 한국경영과학회지
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• 제12권1호
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• pp.111-111
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• 1987

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• 경영과학
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• 제12권1호
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• pp.111-124
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• 1995

With the increasing interest of reducing process variation, statistical process control has served the pivotal tool in most industrial quality programs. In this study, system analyses have been performed associated with a cost incorporated version of a process control, a quadratic loss-based X over bar control chart model. Specifically, two issues, the capital/research investments for improvement of a system and the precision of a parameter estimation, have been addressed and discussed. Through the analysis of experimental results, we show that process variability is seen to be one of the most important sources of loss and quality improvement efforts should be directed to reduce this variability. We further derive the results that, even if the optimal designs may be sensitive, the model appears to be robust with regard to misspecification of parameters. The approach and discussion taken in this study provide a meaningful guide for proper process control. We conclude this study with providing general comments.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1079-1084
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• 2006

Since the focus of QFD is placed on the early stage of product development, the uncertainty in the input information of QFD is inevitable. If the uncertainty is neglected, the QFD analysis results can be misleading. This paper proposes an extended version of the QFD methodology, called Robust QFD, which is capable of considering the uncertainty of the input information and the resulting variability of the output. The proposed framework aims to model, analyze, and dampen the effects of the uncertainty and variability in a systematic manner. The proposed framework is demonstrated through a case study on the ADSL-based high-speed internet service.

• Agricultural and Biosystems Engineering
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• 제6권2호
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• pp.39-46
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• 2005

Because soil compaction is a concern in crop production and environmental pollution, quantification and management of spatial and vertical variability in soil compaction for soil strength) would be a useful aspect of site -specific field management. In this paper, a soil strength profile sensor (SSPS) that could take measurements continuously while traveling across the field was developed and the performance was evaluated through laboratory and field tests. The SSPS obtained data simultaneously at 5 evenly spaced depths up to 50 em using an array of load cells, each of which was interfaced with a soil-cutting tip. Means of soil strength measurements collected in adjacent, parallel transects were not significantly different, confirming the repeatability of soil strength sensing with the SSPS. Maps created with sensor data showed spatial and vertical variability in soil strength. Depth to the restrictive layer was different for different field locations, and only 5 to 16% of the tested field areas were highly compacted.