• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.151-157
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• 1993

In this paper, we investigate the effects of yield randomness for lot-sizing in a multi-stage production system. The practical importance of incorporating yield randomness into production models has been emphasized by many researchers. Yield randomness, especially in semiconductor manufacturing, poses a mojor challenge for production planning and control. The task becomes even more difficult if the demand for final product is uncertain. An attempt to meet the demand with a higher level of confidence forces one to release more input in the fabrication line. This leads to excessive work-in-process (WIP) inventories which cause jobs to spend unpredictably longer time waiting for the machines. The result is that it is more difficult to meet demand with exceptionally long cycle time and puts further pressure to increase the safety stocks. Due to this spiral effect, it is common to find that the capital tied in inventory is the msot significant factor undermining profitability. We propose a policy to determine the quantity to be processed at each stage of a multi-stage production system in which the yield at each stage may be random and may need rework.

• Korean Management Science Review
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• v.31 no.3
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• pp.61-76
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• 2014

There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

• Journal of information and communication convergence engineering
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• v.18 no.1
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• pp.61-68
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• 2020

In the era of the fourth industrial revolution, many production plants are gradually evolving into smart factories that apply information and communication technology to manufacturing, distribution, production, and quality management. The conversion from conventional factories to smart factories has resulted in the automation of production sites using the internet and the internet of things (IoT) technology. Thus, labor-intensive production can easily collect necessary information. However, implementing a smart factory required a significant amount of time, effort, and money. In particular, labor-intensive production industries are not automated, and productivity is determined by human skill. A representative industry of such industries is sewing the industry. In the sewing industry, wherein productivity is determined by the operator's skills. This study suggests that production performance, inventory management and product delivery of the sewing industries can be managed efficiently with existing production method by using smart buttons incorporating IoT functions, without using automated machinery.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.92-95
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• 2001

제조업체에서의 재고관리 시스템은 그 적용 목적과 상황에 따라 다양한 형태가 있다. 그러나, 완제품 생산에 필요한 원자재 및 부품의 안정된 공급을 위하여 수요 예측과 경제성, 신뢰성, 운용성이 우수한 시스템 기술이 요구되고 있다. 본 논문에서는 효율적인 재고관리를 위하여 신경망을 이용한 지능적인 예측 재고관리 시스템을 설계하고, 신경망의 학습알고리즘을 적용하여 제품생산에 요구되는 자재들의 재고를 예측하고 효율적으로 관리할 수 있는 방법을 제안한다.

• Proceedings of KOSOMES biannual meeting
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• 2004.11a
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• pp.143-149
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• 2004

Recently, RFID technology play a key role to implement ubiquitous sensor network(USN). In this paper, we introduce trends of RFID technology, standardization, and then its applications. The purpose of this work is to suggest prosperous applications of RFID, which is applicable on marine information system, such as ship inventory management, management of container and its contents, sensing of environments within cargo hold, management of fishery boats. In case that RFID technology is utilized on marine information systems, it makes safety at sea and marine environments protection.

• Journal of Fashion Business
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• v.11 no.4
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• pp.221-231
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• 2007

SCM system is required inter-industrial cooperation as well as inter-organizational cooperation. It means not only standardization of inter-organization but also standardization of inter-industry. SCM makes possible one circulation from fiber to retail industry in the respects of information and product flows. QR is the SCM of textile apparel industry, which satisfy customer need with least cost and maximum profit. Customer-oriented supply chain system focused on information sharing, cost reduction, inventory control, lead time reduction, quick response on customer demand. How we can measure the performance of successful SCM is issued on the approach of Balanced Scorecard which evaluates 4 perspectives such as customer perspective, internal business perspective, financial perspective, and innovation and learning perspective. This can project the blueprint of textile fashion business to right direction with vision.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.404-411
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• 2016

In footwear manufacturing systems, the upper parts of the shoes are manually sewed on a sub-line while bottom parts are produced by machines such as injection and molding machines on a sub-line before these two parts are combined into complete shoes on a final assembly line. The manual operations for the upper parts lead to a large variability in processing times, resulting in higher work-in-process inventory. In most footwear industries, production lines have been controlled by MRP-based push systems. Some industries attempt to introduce Kanban-based pull systems. This paper identifies the characteristics of the footwear manufacturing processes, and discusses the problems of the current control systems. As an operational alternative, a CONWIP-based control strategy is presented. Simulation experiments are performed to examine the performance of the control strategies.

• Management Science and Financial Engineering
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• v.3 no.1
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• pp.57-74
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• 1997

An EOQ-like inventory model for a manufacturing process is studied. The system is assumed to deteriorate during the production process. The results are either the production of a number of defective items, or the breakdown of the production machine. The optimal production lot size is derived. The model is extended to the case in which the probabilities of making defective items and machine breakdowns are a function of both the quantity (amount) and quality (performance) of the consumed setup cost (including the preventive maintenance cost). We further assume that the setup performance can be improved by investing in the performance improvement program. Hence, the same or a better setup outcome can be achieved with a lower setup cost. We then investigate the optimal setup cost and investment policy simultaneously, thereby achieving a better process quality and setup cost reduction concurrently.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.157-175
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• 2011

The purpose of this paper is to find out the effects of the gambler's fallacy bias on the supply chain. For this study, the simulation was based on a casual structure of the Beer Distribution Game from Sterman(2000)'s Business Dynamics and designed into 2 different models : the first model carries the exact same structure as the reference mentioned above and for the second model, the comparison model is used reflecting gambler's fallacy bias. Each model has 2 different demand patterns. The 4 cases of models was tested with 1,000 different random number seeds. The results for the simulation are following : In the aspect of the inventory and out of stock, the basic model resulted better than the comparison. However, in the bullwhip effect, the comparison model has less than the basic in terms of the level demand pattern. But there was no significant difference in the cycle demand.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.116-123
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• 2023

In supply chain, most partners except the top level suppliers have inbound and outbound logistics. For example, toll manufacturing companies get unprocessed materials from a requesting company and send the processed materials back to the company after toll processing. Accordingly, those companies have inbound and outbound transportation costs in their total logistics costs. For many cases, the company may make the schedule of distributions by considering only the due delivery dates. However, the inbound and outbound transportation costs could significantly affect the total logistics costs. Thus, this paper considers the inbound and outbound transportation costs to find the optimal distribution plans. In addition, we have considered the inventory holding costs as well with transportation costs. From the experimental results, we have provided the optimal strategies for the distributions of replenishment as well as deliveries.