• International Journal of Quality Innovation
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• v.7 no.2
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• pp.141-156
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• 2006

This study describes a novel algorithm for optimizing the quality yield of silicon wafer slicing. 12 inch wafer slicing is the most difficult in terms of semiconductor manufacturing yield. As silicon wafer slicing directly impacts production costs, semiconductor manufacturers are especially concerned with increasing and maintaining the yield, as well as identifying why yields decline. The criteria for establishing the proposed algorithm are derived from a literature review and interviews with a group of experts in semiconductor manufacturing. The modified Delphi method is then adopted to analyze those results. The proposed algorithm also incorporates the analytic hierarchy process (AHP) to determine the weights of evaluation. Additionally, the proposed algorithm can select the evaluation outcomes to identify the worst machine of precision. Finally, results of the exponential weighted moving average (EWMA) control chart demonstrate the feasibility of the proposed AHP-based algorithm in effectively selecting the evaluation outcomes and evaluating the precision of the worst performing machines. So, through collect data (the quality and quantity) to judge the result by AHP, it is the key to help the engineer can find out the manufacturing process yield quickly effectively.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.117-117
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• 2000

This paper presents experimental results for peformance management of a Profibus-FMS network. The performance management alms to maintain a uniform level of network performance at all stations under changing network traffic. The performance management algorithm monitors the performance of individual network stations and commands the stations to change their timer values in order to have comparable performance at all stations. In order to determine the amount of timer change, the algorithm employs a set of fuzzy rules. This algorithm has been evaluated on a Profibus network

• Journal of the Korea Society for Simulation
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• v.17 no.1
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• pp.43-52
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• 2008

The High Level Architecture(HLA) is the IEEE 1516 standard for interoperation between heterogeneous simulators which are developed with different languages and platforms. Run-Time Infrastructure(RTI) is a software which implements the HLA Interface Specification. With the development of time management service of RTI, it is necessary to consider an efficient design approach and an algorithm of Greatest Available Logical Time(GALT) computation. However, many time management services of existing RTIs have difficulty in modification and extension. Although some RTIs avoid this difficulty through modular design, they comply with not IEEE 1516 HLA/RTI but HLA 1.3. In addition, a lot of RTIs made use of well-known Mattern's algorithm for GALT computation. However, Mattern's algorithm has a few limitations for applying to IEEE 1516 HLA/RTI. This paper proposes a modular design and an implementation of time management service for IEEE 1516 HLA/RTI. We divided th time management service module into two sub-modules: a TIME module and a GALT module and used Mattern's algorithm improved for IEEE 1516 HLARTI. The paper also contains several experimental results in order to evaluate our time management service module.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.437-447
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• 2003

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF(Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED(Random Early Detection) algorithm. However, RED algorithm simple but does not protect traffic from high-bandwidth flows, which include not only flows that fail to use end-to-end congestion control such as UDP flow, but also short round-trip time TCP flows. In this paper, in order to solve this problem, we propose a simple fairness queue management scheme, called AFQM(Approximate Fair Queue Management) algorithm, that discriminate against the flows which submit more packets/sec than is allowed by their fair share. By doing this, the scheme aims to approximate the fair queueing policy Since it is a small overhead and easy to implement, AFQM algorithm controls unresponsive or misbehaving flows with a minimum overhead.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.37-64
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• 2022

As the social acceptance of artificial intelligence increases, the number of cases of applying machine learning methods to companies is also increasing. Technical factors such as accuracy and interpretability have been the main criteria for selecting machine learning methods. However, the success of implementing machine learning also affects management factors such as IT departments, operation departments, leadership, and organizational culture. Unfortunately, there are few integrated studies that understand the success factors of machine learning selection in which technical and management factors are considered together. Therefore, the purpose of this paper is to propose and empirically analyze a technology-management integrated model that combines task-tech fit, IS Success Model theory, and John Rice's algorithm selection process model to understand machine learning selection within the company. As a result of a survey of 240 companies that implemented machine learning, it was found that the higher the algorithm quality and data quality, the higher the algorithm-problem fit was perceived. It was also verified that algorithm-problem fit had a significant impact on the organization's innovation and productivity. In addition, it was confirmed that outsourcing and management support had a positive impact on the quality of the machine learning system and organizational cultural factors such as data-driven management and motivation. Data-driven management and motivation were highly perceived in companies' performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.343-352
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• 1993

In this study, a modified algorithm for the exchange heuristic is developed and applied to a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The exchange heuristkc is a multiple pass algorithm which makes improvements upon a given initial feasible schedule. Four different modified algorithms are proposed. The original algorithm and the new algorithms were compared through an experimental investigation. All the proposed algorithms reduce the maximum completion time much more effectively than the original algorithm. Especially, one of four proposed algorithms obviously outperforms the other three algorithms. The algorithm of the best performance produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time. However, in most situations, a reduction in schedule length means a significant reduction in the total cost.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.2
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• pp.109-121
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• 2007

This paper focuses on algorithms based on the evolution, which is applied to various optimization problems. Especially, among these algorithms based on the evolution, we investigate the simple genetic algorithm based on Darwin's evolution, the Lamarckian algorithm based on Lamark's evolution and the Baldwin algorithm based on the Baldwin effect and also Investigate the difference among them in the biological and engineering aspects. Finally, through this comparison, we suggest a new algorithm to find more various solutions changing the genotype or phenotype search space and show the performance of the proposed method. Conclusively, the proposed method showed superior performance to the previous method which was applied to the constrained minimum spanning tree problem and known as the best algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.330-340
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• 2007

IEEE 802.11 wireless LANs employ the backoff algorithm to avoid contentions among STAs when two or more STAs attempt to transmit their data frames simultaneously. The MAC efficiency can be improved if the CW values are adaptively changed according to the channel state of IEEE 802.11 wireless LANs. In this paper, we propose a dynamic contention window control algorithm using the genetic algorithm to improve the MAC throughput of IEEE 802.11 wireless LANs.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.81-89
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• 2000

The real-time multicast problem is to construct a multicast tree starting from a source node and including multiple destination nodes and that has minimum network cost with delay constraints. It is known that to find a tree of the minimum network cost is the Steiner Tree problem which is NP-complete. In this paper, we propose a genetic algorithm to solve the multicast tree with minimum network cost and the delay constraints. The computational results obtained by comparing an existing algorithm. Kompella algorithm, and the proposed algorithm show that our algorithm tends to find lower network cost on the average than Kompella algorithm does.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.4
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• pp.61-70
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• 2005

In this Paper, we develop an improved branch and bound algorithm for the (un)weighted unconstrained two-dimensional cutting problem. In the proposed algorithm, we improve the branching strategies of the existing exact algorithm and reduce the size of problem by removing the dominated pieces from the problem. We apply the newly Proposed definition of dominated cutting pattern and it can reduce the number of nodes that must be searched during the algorithm procedure. The efficiency of the proposed algorithm is presented through comparison with the exact algorithm known as the most efficient.