• Journal of the Economic Geographical Society of Korea
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• v.23 no.4
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• pp.373-394
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• 2020

The strengthening of multilateral international sanctions against North Korea has raised questions as to how effective they are in exerting pressure on the country's economy. In this paper, we address this question by examining their impact on the country's integration into regional and global apparel production networks. North Korea has in the past decade become an increasingly competitive exporter of apparel on the basis of consignment-based processing arrangements. Official trade data shows a sharp drop in North Korean exports of clothing since the sectoral ban in 2017. There is evidence to suggest, however, that exports have continued on a more informal and clandestine basis. North Korea's integration into apparel production networks has also taken the form of the dispatch of workers to factories in China's northeastern border regions. Yet there is evidence that the recent sanctions imposed on such practices has similarly led to illicit practices such as working on visitors' visas, often with the help of Chinese enterprises and local government. The resilience of North Korea's integration into apparel production networks follows a capitalist logic and is result of the highly profitable nature of apparel production for all actors concerned and a correspondingly strong desire to evade sanctions. As such, the analysis contributes to the literature on sanctions that suggests that the measures may contribute to emergence of growing informal and illicit practices and to the role of the clandestine economy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.658-663
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• 1994

The classification and coding of part for group technology applications continus to be labour intensive and time-consuming process, and therefore much effort is dedicated to the structure and creation of automatic coding systems. IN this paper, Neural networks is used to generate processes-related digit as well as part geometry-related digit of the TS code where part name is provided as input.since part name, which is appropriately designated, provides much information about part geometry and manufacturing processes. THe developed GT recommendation system is integrated with interactive TS coding system and database in order to handle the changes of production environment, such as the change of production part of plant. It is found to recommend codes accurately and promises to be a useful tool for consistent, reliable and convenient coding processes.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.53 no.3
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• pp.134-141
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• 2004

Recently, neural network techniques are widely used in adaptive and learning control schemes for production systems. However, in general it takes up a lot of time to learn in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult for the PID gains suitably, lots of researches have been reported with respect of turning schemes of PID gains. A neural network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed neural network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accidents.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.717-719
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• 2003

Recently Neural Network techniques have widely used in adaptive and learning control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of neural networks constructed as a result is not obvious. And in practice since it is difficult to the PID gains suitably lots of researches have been reported with respect to turning schemes of PID gains. A Neural Network-based PID control scheme is proposed, which extracts skills of human experts as PID gains. This controller is designed by using three-layered neural networks. The effectiveness of the proposed Neural Network-based PID control scheme is investigated through an application for a production control system. This control method can enable a plant to operate smoothy and obviously as the plant condition varies with any unexpected accident.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.78-101
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• 2017

High-quality industrial control is critical to ensuring production quality, reducing production costs, improving management levels and stabilizing equipment and long-term operations. WiFi-based Long Distance (WiLD) networks have been used as remote industrial control networks. Real-time performance is essential to industrial control. However, the original mechanism of WiLD networks does not minimize end-to-end delay and restricts improvement of real-time performance. In this paper, we propose two algorithms to obtain the transmitting/receiving phase cycle length for each node such that real time constraints can be satisfied and phase switching overhead can be minimized. The first algorithm is based on the branch and bound method, which identifies an optimal solution. The second is a fast heuristic algorithm. The experimental results show that the execution time of the algorithm based on branch and bound is less than that of the heuristic algorithm when the network is complex and that the performance of the heuristic algorithm is close to the optimal solution.

• 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 Geographical Society
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• v.51 no.5
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• pp.667-690
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• 2016

This paper reviews the evolution process of global production network(GPN) discourse, from its origin to the recent theorization, namely GPN 2.0. In so doing, the discursive formation of global production networks is introduced in comparison with a competing discourse global commodity/value chains, with particular attention to conceptual and analytical lacunae in the latter. This article also outlines how the global production network perspective has become a useful discursive and practical tool that allows the examination of the nexus of global economy, transnational corporations, and regional development. Subsequently, a theoretical dearth in the approach is discussed in reference to key critiques, and in this context Yeung and Coe's recent theorization GPN 2.0, which is centered on casual mechanisms and network configurations is reviewed. This paper suggests that the theory adequately addresses the problem of casuality lacking in its precedented conceptual framework, and that it helps exploring the formation and evolution processes of varied production networks(including intrafirm coordination, interfirm control, strategic partnership, and extrafirm bargaining) in connection with competitive dynamics and risky environments. As a result of the theorization, the difference between GPN and the chain approaches has become more apparent, and the idea of extrafirm bargaining is particularly important in the differentiation. Extrafirm bargaining is seen to be a comprehensive networking form inclusive of such GPN 1.0 analytical concepts as value, embeddeness, and power, and research attentive to, and engaging with, the extrafirm networks is expected to help transcending the chain governance approaches' analytical excess of interfirm linkages and industry-centeredness.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.1-21
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• 2006

Abstract The purpose of this paper is to analyze production and innovation networks of manufacturers in the rural, long-live areas of Gangwon Jeju and to suggest an ideal regional development model of rural areas in the knowledge-based information age. For this purpose, we compared the areas of Gangwon Jeju with the long-live belt areas in the rural pan of the Honan region and Gwangju Jeonju, the urban part of Honam. The findings from the study are summarized as follows. Firstly, the stronger the local networks in terms of supply of the necessary input materials and labor, the more successful the manufacturing industry is in the given area. Secondly, the more diverse and lasting the networks (in terms of the location of manufacturers, local area and national area) and cooperation agents(businesses, research institutions, the local government, the central government) they have, the more prosperous the manufacturing industry is. These results indicate that the successful development model for rural areas requires that we take the approach of fostering potential innovation capabilities of total areas by fully utilizing their innate resources so as to create an internal cooperative network and further build extensive networks encompassing external entities to create a virtual innovation cluster.

• Journal of Microbiology and Biotechnology
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• v.22 no.7
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• pp.939-946
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• 2012

Antibiotic production with Streptomyces sindenensis MTCC 8122 was optimized under submerged fermentation conditions by artificial neural network (ANN) coupled with genetic algorithm (GA) and Nelder-Mead downhill simplex (NMDS). Feed forward back-propagation ANN was trained to establish the mathematical relationship among the medium components and length of incubation period for achieving maximum antibiotic yield. The optimization strategy involved growing the culture with varying concentrations of various medium components for different incubation periods. Under non-optimized condition, antibiotic production was found to be $95{\mu}g/ml$, which nearly doubled ($176{\mu}g/ml$) with the ANN-GA optimization. ANN-NMDS optimization was found to be more efficacious, and maximum antibiotic production ($197{\mu}g/ml$) was obtained by cultivating the cells with (g/l) fructose 2.7602, $MgSO_4$ 1.2369, $(NH_4)_2PO_4$ 0.2742, DL-threonine 3.069%, and soyabean meal 1.952%, for 9.8531 days of incubation, which was roughly 12% higher than the yield obtained by ANN coupled with GA under the same conditions.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.4
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• pp.876-891
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• 2014

Previous studies of ethnic enclaves did not provide an adequate explanation of the geographical contexts and spatial implications of industrial production systems, as a result of emphasizing ethnic networks with stagnant participation from geographers. The objective of this study was to identify and examine the formation mechanism of Korean ethnic enclaves through the case of Bom Retiro's Korean garment industrial district in Brazil, specifically by performing an integrated review of the development path of Bom Retiro, the garment industry's production systems, and ethnic networks. The research findings indicated that the formation of this region's ethnic enclave was indeed highly influenced by ethnic networks; however, it was also affected by the development path of the region as a migrant garment industrial district and spatial convergence pertaining to the production systems of garment industries. Moreover, the formation of Bom Retiro's ethnic enclave also involved active participation of non-ethnic immigrant communities and local Brazilians.