• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.479-483
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• 2005

BBU is the weapon system for the extension of range through the reduction of base drag in 155mm. It has been mass-produced since 2000. The purpose of this research is productivity increase through the reduction of process lead time. Development process is as follows. First, formulation tests about propellent and liner, Second, spin test and final firing test about end products.

• Journal of the Korea Safety Management & Science
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• v.3 no.3
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• pp.55-64
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• 2001

The main objective of this research is to develop a model to select the optimal input service level for a distribution center-multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service levels for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.104-111
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• 2023

The semiconductor industry, which relies on global supply chains, has recently been facing longer lead time for material procurement due to supply chain uncertainties. Moreover, since increasing customer satisfaction and reducing inventory costs are in a trade-off relationship, it is challenging to determine the appropriate safety stock level under demand and lead time uncertainties. In this paper, we propose a framework for determining safety stock levels by utilizing the optimization method to determine the optimal safety stock level. Additionally, we employ a linear regression method to analyze customer satisfaction scores and inventory costs based on variations in lead time and demand. To verify the effectiveness of the proposed framework, we compared safety stock levels obtained by the regression equations with those of the conventional method. The numerical experiments demonstrated that the proposed method successfully reduces inventory costs while maintaining the same level of customer satisfaction when lead time increases.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.253-261
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• 1998

(s,S) inventrory system of a perishable item with positive lead times and finite backlogs under N-policy Under this policy as and when the inventory level drops to s-N during a lead time local purchase is made. Three models are con-sidered. The limiting distribution on the inventory level is obtained and an associated cost analysis is made. Results ae numerically illustrated.

• Journal of the Korean Society of Safety
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• v.14 no.4
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• pp.93-99
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• 1999

A try was carried out to reduce lead time of die manufacturing. That is to make manual machining and finishing work time shorter by improving CAD/CAM modeling methods, so called with "separate modeling" and "relief modeling". The manual machining and finishing manual work time were reduced adapting the novel CAD/CAM modeling methods. Ultimately we accomplished much reduction of the lead time of die manufacturing.f die manufacturing.

• Journal of Welding and Joining
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• v.18 no.1
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• pp.70-76
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• 2000

A rolled steel for structural parts and lead bronze alloy were bonded each other by a new semi-solid diffusion bonding process to investigate the effect of the process parameters, for example bonding temperature and bonding time, on the interface characteristics, and bonding behavior. It can be possible that manufacture of the bonded steel/lead bronze which has a cylindrical shape with inserted the lead bronze alloy into the steel ring by the diffusion bonding process under the semi-solid condition of the lead bronze alloy without any pressure and flux. It has been know that the control of the amount of the liquid phase in semi-solid lead bronze alloy was very important to obtain soundness interface, since the shear strength of the bonded steel/lead bronze at 850℃ for 60 minutes under the condition of about 40% of the liquid phase in the lead bronze alloy shows maximum value, 210 MPa. The shear strength increases with an increase in bonding time and show maximum value, and then decreases.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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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).

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.91-106
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• 1992

It an inventory control system, the demand over time are often assumed to be independently identically distributed (i. i. d.). However, the demands may well be correlated over time in many situations. The estimation of reorder points is not simple for correlated demands with variable lead time. In this paper, a general class of autoregressive and moving average processes is considered for modeling the demands of an inventory item. The first four moments of the lead-time demand (L) are derived and used to approximate the distribution of L. The reorder points at given service level are then estimated by the three approximation methods : normal approximation, Charlier series and Pearson system. Numerical investigation shows that the Pearson system and the Charlier series performs extremely well for various situations whereas the normal approximation show consistent underestimation and sensitive to the distribution of lead time. The same conclusion can be reached when the parameters are estimated from the sample based on the simulation study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.45-56
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• 1985

This thesis studies the order release scheduling by lead time offsetting technique in MRP system. MRP is the process of working backward from the scheduled completion dates of end products or major assemblies to determine the dates and quantities when the various component parts and materials are to be ordered. It aims getting the right quantity of component parts to the right places at the right time with a schedule that puts each parts or subassembly into stock shortly ahead of the need for that parts or subassembly. The planned order release point of a item can be easily decided when the scheduled completion date and planned lead time is certain and known before by lead time offsetting technique in MRP system.

• Ocean and Polar Research
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• v.40 no.3
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• pp.99-114
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• 2018

In the present study, we assess the GloSea5 (Global Seasonal Forecasting System version 5) near-surface ocean current forecasts using globally observed surface drifter dataset. Annual mean surface current fields at 0-day forecast lead time are quite consistent with drifter-derived velocity fields, and low values of root mean square (RMS) errors distributes in global oceans, except for regions of high variability, such as the Antarctic Circumpolar Current, Kuroshio, and Gulf Stream. Moreover a comparison with the global high-resolution forecasting system, HYCOM (Hybrid Coordinate Ocean Model), signifies that GloSea5 performs well in terms of short-range surface-current forecasts. Predictions from 0-day to 4-week lead time are also validated for the global ocean and regions covering the main ocean basins. In general, the Indian Ocean and tropical regions yield relatively high RMS errors against all forecast lead times, whilst the Pacific and Atlantic Oceans show low values. RMS errors against forecast lead time ranging from 0-day to 4-week reveal the largest increase rate between 0-day and 1-week lead time in all regions. Correlation against forecast lead time also reveals similar results. In addition, a strong westward bias of about $0.2m\;s^{-1}$ is found along the Equator in the western Pacific on the initial forecast day, and it extends toward the Equator of the eastern Pacific as the lead time increases.