• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.285-288
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• 1996

This paper deals with an (s, S) spare-part inventory model with general leadtime. In the model, if the inventory level falls to a reorder point s, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (s, S) minimizing the cost rate.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.77-83
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• 1996

The design of multi -echelon distribution system is need for appropriate inventory control strategy considering for systematic tradeoff between trunk cost in central warehouse and inventory cost in regional warehouse. This study presents a method of the efficient inventory control of multi-echelon distribution system through partial leadtime management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.117-124
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• 2008

Ultra-high voltage transformer industry has characteristic of small quantity batch production system by other order processing unlike general mass production systems. In this industry, observance of time deadline is very important in market competitive power security and company continued existence. The transformer winding is a process that rolls a coil is coated with an electric insulation material in order to generate the required voltage using the voltage fluctuation. The winding process is very important production process in the extra-high voltage transformer manufacturing industry because winding process is core process that occupy weight about half of whole process and is process that decide current ratio of transformer. This paper proposes a statistical calculation and control method of planned leadtime on the basis of real data and informations for the A company in transformer winding process. Moreover, we develop unit process scheduling system.

• Journal of the Korea Safety Management & Science
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• v.20 no.3
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• pp.37-46
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• 2018

According to enhancement of roles and functions of enterprises' distribution centers, recent trend of distribution centers are specialization and diversification which have generated lots of new distribution center building or expansion of the existing ones and led attention on stock transfer importance in case of distribution center relocation. This thesis is a study for how to reduce stock transfer leadtime in order to minimize business risk and how to increase inventory accuracy when stock ownership is transferred in case of distribution center relocation, and to provide inventory accuracy management methods and inventory in/out management types, detailed definition to evaluate level for inventory accuracy management and pros/cons by inventory in/out management type assuming 'the higher inventory accuracy before stock transfer, the shorter stock transfer leadtime when distribution center is relocated'. This thesis provides detailed procedure to secure an absolute stock transfer leadtime and process to confirm hugh inventory accuracy by stakeholders which should be sloved by Task Force Team for stock transfer in case of distribution center relocation.

• Journal of Korean Society for Quality Management
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• v.24 no.1
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• pp.44-49
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• 1996

This paper deals with a (Q, r) spare-part inventory model with gamma leadtime. In the model, if the inventory level falls to a reorder point r, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (Q, r) minimizing the cost rate. A numerical example is presented to explain the model.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.4
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• pp.285-293
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• 2004

In this study, a machine grouping problem for the formation of manufacturing cells is considered. We constructed the problem as minimizing manufacturing leadtime consisting of parts' processing, moving, and waiting time. Specifically, the main objective of the defined problem is established as minimizing inter-cell traffic in order to minimize the part's moving time. In addition, to reduce the waiting time of parts, the load balance among cells is implicitly included as constraints. Since this problem is well known as NP-complete and cannot be solved in polynomial time, a genetic algorithm is implemented to obtain solutions. Also, a local optimization algorithm is applied in order to improve the solution by the genetic algorithm. Several experiments show that the suggested algorithms guarantee near optimal solutions in a few seconds.

• IE interfaces
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• v.6 no.2
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• pp.103-115
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• 1993

In dies manufacturing industry, quality, cost, and production leadtime are very important. In this study, we describe the current status and characteristics of dies industry in Korea. AS a case study, we introduce a CIM system implemented in a leading dies manufacturer and describe its components and functions. Subsequently, we analyze the effectiveness of the CIM system by using the real data between 1987 and 1992 from the company. It is indicated that the most significant impact of CIM is the reduced cost, followed by increased sales, reduced leadtime, and improved quality of dies. All these four variables show positive correlations with one another. However, the data indicate that the number of employees are not directly related with other variables : probably because additional personnel are required for operating new technology such as CAD/CAM and information network.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.37-49
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• 2017

In order to maximize the efficiency and the quality of care in a hospital, hospitals in general operate by appointments. Patient no-shows or missed appointments waste the time of staffs who prepare for appointments, deprive patients of needed care, and increase burden on clinic capacity. The purpose of this study is to examine the importance and significance of factors that affect patient no-shows. The actual data of 50,000 outpatient appointments is compiled and analyzed from a VAMC in the United States with aims to identify the factors that contribute to outpatient no-shows and to draw meaningful implications. Random forest along with logistic regression analysis identify the factors affecting no-shows; appointment leadtime, show-up rate, travel distance, no-show rate in previous period, patient age, severity, complexity of disease, chronic pain, depression, drug dependence. The appointment leadtime, show-up rate, travel distance and previous no-show rate can be improved by enhancing SMS pre-notification and by improving afterwards telephone counseling. For other factors, it needs to study on the service differentiation with the characteristics of each patient group.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.273-284
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• 2007

This paper studies a periodic review inventory model with an e-MarketPlace transaction in reconfigurable manufacturing system(RMS). A decision maker can expand/reduce production capacity/quantities and/or replenish/dispose inventories from/to e-MarketPlace urgently to satisfy the stochastic demands. If inventories are replenished or disposed through e-MarketPlace, this leadtime is shorter than the production leadtime, but unit purchasing or selling cost is more expensive than that of expanding capacity or reducing production quantities respectively. Henceforth, trade-off on these alternatives is considered. In addition to this, in order to consider the economy of scale, our model includes the fixed cost for purchasing from e-MarketPlace and capacity expansion. We use dynamic programming and K convexity methods to characterize the nature of the optimal policy. Finally, We present the optimal inventory control policy which is composed by the combinations of a base stock and (s,S) type policy.

• Water Engineering Research
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• v.3 no.2
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• pp.113-122
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.