• Journal of Technology Innovation
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• v.12 no.1
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• pp.115-134
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• 2004

In this paper, we tried to find the bottleneck factors of firms' innovative activities using the KIS (Korea Innovation Survey) 2002 data. Employing the method of factor analysis, we identified five bottleneck factors of innovative activities: organizational bottleneck factor, innovative bottleneck factor, economic bottleneck factor, supply-chain bottleneck factor, and market-environment bottleneck factor. Using regression analysis which includes the five bottleneck factors, industry characteristics variables (market concentration, technological opportunity, appropriability), and other control variables, we found (1) that all the five bottleneck factors are negatively related with innovative activities, (2) that technological opportunity and appropriability conditions are positively related with innovative activities, (3) that there is an inverted-U relationship between market concentration and innovative activities, and (4) that firm size has no significant influence on firms' innovative activities.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.923-928
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• 2003

This paper proposes a bottleneck link bandwidth measurement algorithm for reducing packet transmission delay within the grid network. There are two methods for measuring bottleneck link bandwidth：Packet Pair algorithm and Paced Probes algorithm. They measure bottleneck link bandwidth using the difference in arrival times of two paced probe packets of the same size traveling from the same source to destination. In addition, they reduce the influences of cross traffic by pacer packet. But there are some problems on these algorithms：it's not possible to know where bottleneck link occurred because they only focus on measuring the smallest link bandwidth along the path without considering bandwidth of every link on the path. So hop-by-hop based bottleneck link bandwidth measurement algorithm can be used for reducing packet transmission delay on grid network. Timestamp option was used on the paced probe packet for the link level measurement of bottleneck bandwidth. And the reducing of packet transmission delay was simulated by the solving a bottleneck link. The algorithm suggested in this paper can contribute to data transmission ensuring FTP and realtime QoS by detecting bandwidth and the location where bottleneck link occurred.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.2
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• pp.246-253
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• 2007

All of the machines in a production line can be classified into bottleneck and non-bottleneck machines. A bottleneck is a resource whose capacity limits the throughput of the whole production facility. This paper addresses a batch sizing problem at the bottleneck machine. Traditionally, most batch sizing decisions have been made based on the EOQ (economic order quantity) model where setup and inventory costs are considered while throughput rate is assumed to be given. However, since batch size affects the capacity of the bottleneck machine, the throughput rate may not be constant. As the batch size increases, the frequency of the setup decreases. The saved setup time can be transferred to processing time, which results in higher throughput. But, the larger batch size may also result in longer lead time and larger WIP inventory level. This paper presents an alternative method to determine batch size at the bottleneck machine in a manufacturing line. A linear search algorithm is introduced to find optimal throughput rate and batch size at the same time. Numerical examples are provided to see how the proposed method works and to investigate the effects of some parameters.

• Korean Journal of Computational Design and Engineering
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• v.19 no.3
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• pp.214-223
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• 2014

This paper presents a bottleneck detection framework using simulation approach in a wafer FAB (Fabrication). In a semiconductor manufacturing industry, wafer FAB facility contains various equipment and dozens kinds of wafer products. The wafer FAB has many characteristics, such as re-entrant processing flow, batch tools. The performance of a complex manufacturing system (i.e. semiconductor wafer FAB) is mainly decided by a bottleneck. This paper defines the problem of a bottleneck process and propose a simulation based framework for bottleneck detection. The bottleneck is not the viewpoint of a machine, but the viewpoint of a step with the highest WIP in its upstream buffer and severe fluctuation. In this paper, focus on the classification of bottleneck steps and then verify the steps are not in a starvation state in last, regardless of dispatching rules. By the proposed framework of this paper, the performance of a wafer FAB is improved in on-time delivery and the mean of minimum of cycle time.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.681-684
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• 2000

본 논문은 Client & Server 모델을 기반으로 선로 이용률과 응답시간을 분석, 조합하여 웹 상에서 해당 목적지 경로 사이에 있을 수 있는 bottleneck 구간을 탐지하기 위한 시스템을 설계하였다. 이를 위해 traceroute를 이용하여 사용자와 해당 목적지 경로 사이의 인터페이스들을 추적하였다. 추적된 인터페이스들의 IP로 TCP/IP 표준 네트워크 망 관리 프로토콜인 SNMP Polling을 하여 인터페이스로부터 각종 MIB 정보들을 가져와 각 인터페이스간의 선로 이용률을 분석해냈으며, 또한 정확한 bottleneck 구간을 알아내고자 각 라우터로 ping을 실행시켜 응답시간을 계산하였다. 이렇게 얻은 선로 이용률과 응답시간으로 보다 정확한 트래픽 정보와 bottleneck 구간을 분석해낼 수 있었다. 이러한 분석 시스템으로 인해 사용자들은 전문적인 지식 없이 단지 자신의 컴퓨터의 웹브라우저를 통한 서버 분석 시스템 접속만으로도 해당 구간의 어떤 부분이 bottleneck 구간인지를 탐지, 분석할 수 있을 것이다.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.621-628
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• 2009

Wireless sensor networks (WSNs) have been considered as a promising method for reliably monitoring both civil and military environments under hazardous or dangerous conditions. Due to the special property and difference from the traditional wireless network, the lifetime of the whole network is the most important aspect. The bottleneck nodes widely exist in WSNs and lead to decrease the lifetime of the whole network. In order to find out the bottleneck nodes, the traditional centralized bottleneck detection method MINCUT has been proposed as a solution for WSNs. However they are impractical for the networks that have a huge number of nodes. This paper first proposes a distributed algorithm called DBND (Distributed Bottleneck Node detection) that can reduce the time for location information collection, lower the algorithm complexity and find out the bottleneck nodes quickly. We also give two simple suggestions of how to solve the bottleneck problem. The simulation results and analysis show that our algorithm achieves much better performance and our solutions can relax the bottleneck problem, resulting in the prolonging of the network lifetime.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.4
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• pp.170-181
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• 2009

When a slow-moving vehicle occupies one of the lanes of a multi-lane highway, it often causes queuing behind, unlike one is caused by an actual stoppage on that lane. This happens when the traffic flow rate upstream from the slow vehicle exceeds a certain critical value. This phenomena is called as the Moving Bottleneck, defined by Gazis and Herman (1992), Newell (1998) [3], and Munoz and Daganzo (2002), who conducted the flow estimates of upstream and downstream and considered slow-moving vehicle speed and the flow ratio exceeding slow vehicle and the microscopic traffic flow characteristics of moving bottleneck. But, a study of delay on moving bottleneck was not conducted until now. So this study provides a average delay time model related to upstream flow and the speed of slow vehicle. We have chosen the two-lane highway and homogeneous traffic flow. A slow-moving vehicle occupies one of the two lanes. Average delay time value is a result of AIMSUN[9], the microscopic traffic flow simulator. We developed a multiple regression model based on that value. Average delay time has a high value when the speed of slow vehicle is decreased and traffic flow is increased. Conclusively, the model is formulated by the negative exponential function.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.102-109
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• 2018

This paper seeks to present a multi-control method that can contribute to effective control of the production line with multiple bottleneck processes. The multi-control method is the production system that complements shortcomings of CONWIP and DBR, and it is designed to determine the raw material input according to the WIP level of two bottleneck processes and WIP level of total process. The effectiveness of the production system developed by applying the multi-control method was verified by the following three procedures. Raw material input conditions of the multi-control method are as follows. First, raw materials are go into the production line when the number of the total process WIP is lower than established number of WIP in total process and first process is idle. Second, raw materials are introduced when the number of WIP of two bottleneck processes is lower than the established number of WIP of each bottleneck process. Third, raw materials are introduced when the first process and in front of bottleneck process are idle even if the number of WIP in the total process is less than established number of WIP of the total process. The production line with two bottleneck processes was selected as the condition for production environment, and the production process modeling of CONWIP, DBR and multi-control production method was defined according to the production condition. And the optimum limited WIP level suitable for each system was obtained by applying a genetic algorithm to determine the total limited number of WIP of CONWIP, the limited number of WIP of DBR bottleneck process, the number of WIP in the total process of multi-control method and the limited number of WIP of bottleneck process. The limited number of WIP of CONWIP, DBR and multi-control method obtained by the genetic algorithm were applied to ARENA modeling, which is simulation software, and a simulation was conducted to derive result values on the basis of three criteria such as production volume, lead time and number of goods in-progress.

• Journal of the Korea Society for Simulation
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• v.22 no.3
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• pp.35-41
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• 2013

This paper applies an active period based bottleneck detection method to flow shop manufacturing system with limited buffer size. Manufacturing systems are constrained by one or more bottlenecks which degrades the system throughput. Conventional bottleneck detection methods include the waiting time or queue length of production stations and their utilization. Due to the random events such as production time of items, machine failure and repair times, the systems may change over time, and subsequently bottlenecks shift from one station to another station. Active period of working station may cause other stations to wait for productions. Information when and where active periods occur helps to find bottlenecks in production systems. Based on these informations, we predict bottlenecks in applying AweSim simulation language. We compare the simulation results of conventional methods with those obtained from duration of active period method, and duration ratio method of both sole and shift bottleneck periods. Even though simulation results are from simple flow shop model, they are quite promising for predicting bottlenecks of production stations. We hope this study aids in decision making regarding the improving system production yield and allocation of available resources of system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.211-220
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• 2013

This paper proposes an algorithm that easily finds an optimal solution for linear bottleneck assignment problems. It is either threshold or augmenting path algorithm that is generally used to solve the bottleneck assignment problem. This paper proposes a reverse-delete algorithm that follows 2 steps. Firstly, the algorithm deletes the maximum cost in a given matrix until it renders a single row or column. Next, the algorithm improves any solution that contains a cost exceeding the threshold value $c^*_{ij}$. Upon its application to 28 balanced assignment problems and 7 unbalanced problems, the algorithm is found to be both successful and simple.