• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.13-24
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• 2021

Industrial networks has been developing various technologies from fieldbus technology to industrial Ethernet and time-sensitive networking. The industry expects that the 5G mobile network will solve the diverse and highly specific industrial site requirements. Accordingly, 3GPP has been developing standard functions to provide ultra-high reliability, ultra-high speed, ultra-connection, and ultra-low latency services, and 3GPP Rel-16 began developing ultra-low latency and ultra-high reliability communication functions for 5G mobile networks to support vertical industries. In this paper, we show the related standardization trends and requirements to apply industrial IoT service scenarios to 5G mobile networks, and in particular, we introduce 5G system features and extended 5G system architecture to provide time sensitive communication and time synchronization services.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.194-201
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• 2010

This paper discuss a performance evaluation of the synchronization algorithm for hybrid networks in industrial environments. The proposed algorithms minimizes synchronization errors which were caused from channel, Propagation, and frequency delays. The modified RBS and offset synchronization methods can be operated by adjustment parameters. The differential BP (Back-off Period) adjustment can synchronize the local time of each node with master node's time in hybrid networks. For the performance analysis, the data transmission time between the wired and wireless devices are investigated. The experimental results show the performance evaluations in terms of the polling service time and an average end-to-end delay.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.87-101
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• 2013

In industrial applications, sensor networks have to satisfy specified time requirements of exchanged messages. IEEE 802.15.4 defines the communication protocol of the physical and medium access control layers for wireless sensor networks, which support real-time transmission through guaranteed time slots (GTSs). In order to improve the performance of IEEE 802.15.4 in industrial applications, this paper proposes a new traffic scheduling algorithm for GTS. This algorithm concentrates on time-critical industrial periodic messages and determines the values of network and node parameters for GTS. It guarantees real-time requirements of periodic messages for industrial automation systems up to the order of tens to hundreds of milliseconds depending on the traffic condition of the network system. A series of simulation results are obtained to examine the validity of the scheduling algorithm proposed in this study. The simulation results show that this scheduling algorithm not only guarantees real-time requirements for periodic message but also improves the scalability, bandwidth utilization, and energy efficiency of the network with a slight modification of the existing IEEE 802.15.4 protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2509-2528
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• 2012

Time division multiple access (TDMA) is a widely used media access control (MAC) technique that can provide collision-free and reliable communications, save energy and bound the delay of packets. In TDMA, energy saving is usually achieved by switching the nodes' radio off when such nodes are not engaged. However, the frequent switching of the radio's state not only wastes energy, but also increases end-to-end delay. To achieve high energy efficiency and low delay, as well as to further minimize the number of time slots, a multi-objective TDMA scheduling problem for industrial wireless mesh networks is presented. A hybrid algorithm that combines genetic algorithm (GA) and simulated annealing (SA) algorithm is then proposed to solve the TDMA scheduling problem effectively. A number of critical techniques are also adopted to reduce energy consumption and to shorten end-to-end delay further. Simulation results with different kinds of networks demonstrate that the proposed algorithm outperforms traditional scheduling algorithms in terms of addressing the problems of energy consumption and end-to-end delay, thus satisfying the demands of industrial wireless mesh networks.

• Journal of the Korean Geographical Society
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• v.40 no.1 s.106
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• pp.78-95
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• 2005

The purpose of this paper is to analyze industrial and innovation networks of long-live area of Honam Region and to suggest a policy direction for regional development of rural areas where have been neglected in the knowledge-based information society. Four counties (Sunchang, Damyang, Gokseong, and Gurye) in the Southwestern region of Korea are regarded as long-live belt of Korea. Production and innovation networks :Ire analyzed based on intensive surveys of firms in the belt. Major findings from the surveys are as follows. First, there are considerably strong local networks of production firms in terms of supply of input materials and labor. There are strong backward industrial linkages of the production firms with agricultural activities and considerable forward linkages with tourism industry. In addition, Internet is becoming a useful tool for sales of the new products. Second, the analysis of the innovation networks in the long-live area suggests the development of 'virtual innovation cluster' in the era of knowledge-based information society. The results imply that this innovation networks can be developed as a virtual innovation cluster in the rural areas, which can be the basis for the development of rural innovation systems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.132-139
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• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Journal of the Korean association of regional geographers
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• v.10 no.4
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• pp.787-799
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• 2004

The industrial community in a metropolis has played an essential role to keep business in a large city. This paper aims to analyze the realities of trade network among enterprises at Buksungro Tools Commercial Cooperative in Daegu. The urban style industrial community is found at Buksungro in Daegu. There are more than one hundred small-sized enterprises. Major trades among enterprises are occurred within and/or by the area. The long-term trade networks within the Buksungro Tools Commercial Cooperative have played the key role to maintain the industrial community. The trade relationship has depended on business networks based on social capital rather than commercial mechanism. The trade networks have been established through credit transactions as well as handling troublesome orders. The trade networks help to transfer technology and to learn the tacit knowledge among firms. The long-term trade networks are more influenced by the social accessibility than spatial accessibility.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.10 no.2
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• pp.1-17
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• 2000

We investigated dissatisfaction of elements of local exhaust system, needs for local exhaust system, and information networks for local exhaust system from June 1998 to September 1999 using the questionnaire structured. It contained questions concerning general characteristics of factory and local exhaust system, troubles and dissatisfaction of elements of local exhaust system, and information networks for local exhaust system. The collected data were analyzed by descriptive statistics analysis. Information networks for local exhaust system were analyzed by multidimensional scaling using path distance of network analysis and by graph analysis using Krackplot. Among complaints of local exhaust system, that of duct has show the highest percentage of complaint. In the information network for local exhaust system, Seoul is positioned in the center of network with mediating role.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.3
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• pp.201-209
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• 2005

Empty moves are necessary when there are imbalances among transportation demands from source locations to destination locations and the transportation demands require empty equipment that must be supplied to source locations. When the amount of the inflow exceeds that of the outflow or the amount of the outflow exceeds that of the inflow, repositioning empty equipment is necessary. Examples of the empty equipment are containers, chassis, and pallets. This paper addresses how to estimate the empty moves on several typical transportation networks. Types of transportation networks considered are chain, tree, cycle, tree of cycles, and hybrid networks. Simple procedures are suggested for determining the optimal empty flows. Numerical examples are provided to illustrate procedures in this paper.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.2
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• pp.83-89
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• 2005

In this paper a new algorithm of learning and evolving artificial neural networks using gene expression programming (GEP) is presented. Compared with other traditional algorithms, this new algorithm has more advantages in self-learning and self-organizing, and can find optimal solutions of artificial neural networks more efficiently and elegantly. Simulation experiments show that the algorithm of evolving weights or thresholds can easily find the perfect architecture of artificial neural networks, and obviously improves previous traditional evolving methods of artificial neural networks because the GEP algorithm imitates the evolution of the natural neural system of biology according to genotype schemes of biology to crossover and mutate the genes or chromosomes to generate the next generation, and the optimal architecture of artificial neural networks with evolved weights or thresholds is finally achieved.