• 정보처리학회논문지D
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• 제10D권1호
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• pp.161-166
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• 2003

제품을 생산하고 공급하는데 소요되는 주문리드타임과 달리 주문이 처리되는데 소요되는데 지연되는 것을 정보리드타임이라고 하는데, 이는 공급체인에서 개별기업들이 수요예측의 변동폭을 높이게 되며 이것이 바로 비용 상승요인으로 작용하게 된다. 본 논문에서는 직렬형 가치사슬에서 정보리드타임이 공급체인 시스템에 주는 영향을 알아본다. 특별히, MIT 시뮬레이션 모형을 동해서 실험을 수행하며, 아래와 같은 두 가지의 이슈를 다룬다. 첫째는 비용-이익 관점에서 물류 리드타임보다 정보리드타임의 개선이 효과적인가\ulcorner 둘째는 정보리드타임이 고객에게 보다 인접한 기업(downstream)이 고객하고 떨어져 있는 기업(upstream)보다 비용을 크게 상승시키고 있는지에 대한 물음이다. 사례 분석에서는 공급체인상의 개변기업들이 갖는 정보리드타임의 중요성을 지적하고, 개별기업간의 정보리드타임의 차이 분석을 통해서 고객의 수요와 요구를 직접 받는 기업에서 정보리드타임의 중요성이 큼을 인증하고 있다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.342-345
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• 2003

Due to the rapid development of manufacturing and information technology, traditional supply chain scheme has been changed dramatically Most companies have been forced to relocate or redesign their logistics network in different countries. A supply chain partnership is a relationship formed between two independent members in supply chain through information sharing to achieve specific objectives and benefits in terms of reductions in total costs and inventories. This study illustrates the benefits of supply chain partnerships based on information sharing and lead-time patterns. We consider three level of information sharing: (1) immediate order information; (2) demand information; (3) inventory information. Given a fixed total lead-time, how lead-time distribution will affect the bullwhip effect and inventory cost under information sharing strategies. The results can help improving supply chain performance and selecting suitable direction for the re-configuration of supply chain network.

• 한국정보시스템학회지:정보시스템연구
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• 제10권2호
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• pp.129-150
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• 2001

In this study, we model a decentralized supply chain system which is managed by four types of centers, sequentially located: Retailer, Wholesaler, Distributor, and Factory Each center contributes to enhancing the performance of the supply chain system individually with its own local inventory information. Through experiments which are performed with a programmed simulation (like the MIT beer game), we investigate how the information lead time improvement in each center affects the whole system. And we show that the impact of the lead time improvement in the downstream, like retailers, affects more to the system than the one in the upstream, like factories, in a cost-effective way. Moreover, by using information lead time for each center, we analyze how much the extent of the improvement affects the whole system, especially for the total cost and the order level.

• 대한안전경영과학회지
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• 제20권3호
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• pp.11-19
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• 2018

This study suggests a model of production information system that can reduce manufacturing lead time and uniformize quality by using DNC S/W as a part of constructing production information management system in the industrial field of the existing marine engine block manufacturing companies. Under the effect of development of this system, the NC machine interface device can be installed in the control computer to obtain the quality information of the workpiece in real time so that the time to inspect the process quality and verify the product defect information can be reduced by more than 70%. In addition, the reliability of quality information has been improved and the external credibility has been improved. It took 30 minutes for operator to obtain, analyze and manage the quality information when the existing USB memory is used, but the communication between the NC controller computer and the NC controller in real time was completed to analyze the workpiece within 10 seconds.

• International Journal of Naval Architecture and Ocean Engineering
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• 제12권1호
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• pp.428-439
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• 2020

The continuous development of information and communication technologies has resulted in an exponential increase in data. Consequently, technologies related to data analysis are growing in importance. The shipbuilding industry has high production uncertainty and variability, which has created an urgent need for data analysis techniques, such as machine learning. In particular, the industry cannot effectively respond to changes in the production-related standard time information systems, such as the basic cycle time and lead time. Improvement measures are necessary to enable the industry to respond swiftly to changes in the production environment. In this study, the lead times for fabrication, assembly of ship block, spool fabrication and painting were predicted using machine learning technology to propose a new management method for the process lead time using a master data system for the time element in the production data. Data preprocessing was performed in various ways using R and Python, which are open source programming languages, and process variables were selected considering their relationships with the lead time through correlation analysis and analysis of variables. Various machine learning, deep learning, and ensemble learning algorithms were applied to create the lead time prediction models. In addition, the applicability of the proposed machine learning methodology to standard work hour prediction was verified by evaluating the prediction models using the evaluation criteria, such as the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Logarithmic Error (RMSLE).

• 산업경영시스템학회지
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• 제19권37호
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• pp.31-40
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• 1996

The amount of safety stock is decided from various information such as the forecasted demand, the lead time, the size of the order quantity and the desired service level. There are two cases to consider the problem of setting safety stock when both the demand in a period and the lead time are characterized as random variables: the first case is the parameters of the demand and lead time distributions are known, the second case is they are unknown and must be estimated. The objective of this study is to present the procedure for setting safety stocks in the case the parameters of the demand and lead time distributions are unknown and must be estimated. In this study, a simple exponential smoothing model is used. to generate the estimates of demand in each period and a discrete distribution of the lead time is developed from historical data, and the optimal service level is used which determined to consider both of a backorder and lost sale.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.508-521
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• 2020

We compared a novel encoding Lempel-Ziv complexity (ELZC) with three common complexity algorithms i.e., approximate entropy (ApEn), sample entropy (SampEn), and classic Lempel-Ziv complexity (CLZC) so as to determine a satisfied complexity and its corresponding quality indices for assessing quality of multi-lead electrocardiogram (ECG). First, we calculated the aforementioned algorithms on six artificial time series in order to compare their performance in terms of discerning randomness and the inherent irregularity within time series. Then, for analyzing sensitivity of the algorithms to content level of different noises within the ECG, we investigated their change trend in five artificial synthetic noisy ECGs containing different noises at several signal noise ratios. Finally, three quality indices based on the ELZC of the multi-lead ECG were proposed to assess the quality of 862 real 12-lead ECGs from the MIT databases. The results showed the ELZC could discern randomness and the inherent irregularity within six artificial time series, and also reflect content level of different noises within five artificial synthetic ECGs. The results indicated the AUCs of three quality indices of the ELZC had statistical significance (>0.500). The ELZC and its corresponding three indices were more suitable for multi-lead ECG quality assessment than the other three algorithms.

• 한국응용과학기술학회지
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• 제27권2호
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• pp.196-201
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• 2010

The influence of red lead($Pb_3O_4$) to curing and formation reaction properties when it was added in positive material of lead acid battery for vehicle use has been investigated. At the results, it was confirmed that the addition of red lead led 4BS crystal size to be smaller and increased the rates of 4BS formation and Pb consumption. Consequently the curing time was shortened to half compared with that of red lead-free one. In addition to this, the lead acid battery prepared by adding red lead showed 14% higher efficiency at the life cycle test than that without red lead.

• 대한설비관리학회지
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• 제23권4호
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• pp.29-38
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• 2018

Through process quality information, the time required for process quality analysis has been drastically shortened, the process defect rate has been reduced, and the manufacturing lead time has been shortened and the on-time delivery rate has been improved. Therefore, The purpose of this study is to develop a quality information analysis system model that effectively shortens the time required for process quality analysis in automobile safety belt parts manufacturing process. As a result of experiments on communication operation between manufacturing execution system (MES) quality server, injection machine control computer, injection machine programmable logic controller (PLC) and terminal, in analyzing quality information, the conventional handwriting input method took an average of 20 minutes, but the new multi-network method took about 2 minutes on average. In addition, the process defect rate was reduced by 13% and the manufacturing lead time was shortened from 28 hours to 20 hours. The delivery compliance rate improved from 96 to 99%.

• 한국수자원학회논문집
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• 제51권12호
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• pp.1207-1216
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• 2018

본 연구는 물리적 수리 수문모형의 적용이 제한적인 감조하천에서의 수위예측을 목적으로 하고 있으며, 이를 위해 한강 잠수교를 대상으로 딥러닝 오픈소스 소프트웨어 라이브러리인 TensorFlow를 활용하여 LSTM 모형을 구성하고 2011년부터 2017년까지의 10분 단위의 잠수교 수위, 팔당댐 방류량과 한강하구 강화대교지점의 예측조위 자료를 이용하여 모형학습(2011~2016) 및 수위예측(2017)을 수행하였다. 모형 매개변수는 민감도 분석을 통해 은닉층의 개수는 6개, 학습속도는 0.01, 학습횟수는 3000번로 결정하였으며, 모형 학습 시 학습정보의 시간적 양을 결정하는 중요한 매개변수인 시퀀스길이는 1시간, 3시간, 6시간으로 변화시키며 모의하였다. 최종적으로 선행시간에 따른 모의 예측능력을 평가하기 위해 LSTM 모형의 예측 선행시간을 6개(1 ~ 24시간)로 구분하여 실측수위와 예측수위와의 비교 분석을 수행한 결과, LSTM 모형의 최적의 성능을 내는 결과는 시퀀스길이를 1시간으로 하였을 때로 분석되었으며, 특히 선행시간 1시간에 대한 예측정확도는 RMSE는 0.065 m, NSE는 0.99로 실측수위에 매우 근접한 예측 결과를 나타내었다. 또한 시퀀스길이에 상관없이 선행시간이 길어질수록 모형의 예측 정확도는 2017년 전기간에 걸쳐 평균적으로 RMSE 0.08 m에서 0.28 m로 오차가 증가하였으며, NSE는 0.99에서 0.74로 감소하였다.