• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.415-430
• /
• 2023

The Material·Part·Equipment industry is mostly an industry centered on small and medium-sized enterprises (SMEs) and is an important industry for revitalizing the local economy, which is the source of manufacturing competitiveness. In this study, we tried to derive the implications necessary for the development of the Material·Part·Equipment industries by analyzing the competitiveness of the Material·Part·Equipment industries in the Chungcheong region. To this end, we analyzed the industrial development stage and competitiveness of each region (Daejeon, Sejong, Chungnam, and Chungbuk) based on business scale factor, industrial growth rate, industrial specialization, and regional competitiveness for the Material·Part·Equipment industries in the Chungcheong region. Using data such as the number of employees, the number of businesses, and the amount of production in 2014 and 2019, significant industrial groups by region were identified considering the level of industrial specialization and regional competitiveness. In addition, by identifying the positions of these significant industrial groups in the stage of industrial development, suggestions for the development of the Material·Part·Equipment industries in the Chungcheong region were presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2012.05a
• /
• pp.378-379
• /
• 2012

Nowadays, great energy consumption in advanced electrical industry has called up the great y efficiency. Electric power IT industry such as intelligent electric power system is receiving great attention and being marked up as a new growth engine. Through Intelligent electric power system, the electric power supply can be balance optimized according to demand, giving huge cost savings advantage for energy imports, infrastructure construction and operation. Nevertheless, the intelligent system promotes better reliability in power supply. Manual electric power management using man power appears to be non-practical. Real time electric power management on all facilities and equipment can be done through an intelligent electric power system, any accident break out issue can be easily recorded and recognized. In this paper, a fully integrated intelligent switchgear electric management system is developed to monitor and remote control the electrical switch based on smart phone. The proposed system is superior than the existing switchgear management system's weakness and can sharply improve effectiveness and stability with low cost. In future, the proposed system is expected to be greatly contributed to the advancement of the IT industry in electric power management.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2008.11a
• /
• pp.733-737
• /
• 2008

Construction supply chain management focused on materials in construction industry plays a critical role which controls the success and failure of a project. For the efficiency of construction supply chain management, the framework which provides project participants with the information originated from whole construction logistics steps without the omission and discontinuation of information flow is required. The new management framework that can support this environment is necessary because of setting up the complicated and distributed environment including logistics information management by intelligent equipment, co-working management with pre-framework legacy system and various devices(UMPC and PDA etc.) as the information confirmation and electrical transmission tool between the project participants different from former construction supply chain management environment while recently developing ubiquitous technologies such as RFID/USN and intelligent equipment to support logistics process. Therefore, the objective of this study is to introduce the concept of SOA (Service Oriented Architecture) as an alternative of effective information integration under the complex and distributed environment and to propose the SOA-based application model for building intelligent construction supply chain management framework.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.6
• /
• pp.1142-1147
• /
• 2016

Recently, IoT(Internet of Things) has been extensively researching to provide intelligent services by fusing ICT. Especially with the advent of Germany's Industry 4.0, it is emphasized the importance of the industrial IoT to maximize the production capacity. Accordingly, a lot of efforts to spread the smart factory base of industrial IoT have continued domestically as well as abroad. But the current smart factory systems have controlled equipment using the data declared in the embedded systems. Therefore, it is difficult to control environment that lots of equipment is installed. In this paper, we proposed equipment control system based on data base access method for industrial IoT. This method controls the equipment using data base from parameter of equipment. Through experiments that the system apply to mold shot system with a number of variables, it is shown that the proposed method can efficiently control a number of devices.

• The KIPS Transactions:PartD
• /
• v.11D no.3
• /
• pp.709-716
• /
• 2004

This paper describes an intelligent real-time monitoring system of a semiconductor processing equipment, which determines normal or not for a wafer in processing, using multiple time-series pattern recognition. The proposed system consists of three phases, initialization, learning and real-time prediction. The initialization phase sets the weights and tile effective steps for all parameters of a monitoring equipment. The learning phase clusters time series patterns, which are producted and fathered for processing wafers by the equipment, using LBG algorithm. Each pattern has an ACI which is measured by a tester at the end of a process The real-time prediction phase corresponds a time series entered by real-time with the clustered patterns using Dynamic Time Warping, and finds the best matched pattern. Then it calculates a predicted ACI from a combination of the ACI, the difference and the weights. Finally it determines Spec in or out for the wafer. The proposed system is tested on the data acquired from etching device. The results show that the error between the estimated ACI and the actual measurement ACI is remarkably reduced according to the number of learning increases.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.744-747
• /
• 2004

An electric precipitator in a thermal electric power plant is essential equipment for preventing air environment pollution. However, it is difficult for the existing control systems to make efficient effects on dust collection. This is because AVC and ERC consist of independent, separate systems in the existing systems. To solve this problem, we developed an intelligent distributed control system, which makes optimal control possible through connection operations between the control systems. In this paper, we analyzed system performance and fly ash reduction effects through the developed system structure, development contents and its actual application to power plant.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.432-437
• /
• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently fuzzy controllers have become quite popular for robust control due to its capability of dealing with unstructured uncertainty. Thus in this paper we design an adaptive fuzzy controller using an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Simulation results show that satisfactory performance is achieved by the proposed controller.

• Journal of Mechanical Science and Technology
• /
• v.15 no.5
• /
• pp.544-554
• /
• 2001

A shop floor can be considered as an important level to develop Computer Integrated Manufacturing system (CIMs). However, a shop floor is a dynamic environment where unexpected events continuously occur, and impose changes to the planned activities. To deal with this problem, a shop floor should adopt an appropriate control system that is responsible for the coordination and control of the manufacturing physical flow and information flow. In this paper, a hybrid control system is described with a shop floor activity methodology called Multi-Layered Task Initiation Diagram (MTD). The architecture of the control model contains three levels: i.e., he shop floor controller (SFC), the intelligent agent controller (IAC) and the equipment controller (EC). The methodology behind the development of the control system is an intelligent multi-agent paradigm that enables the shop floor control system to be an independent, an autonomous, and distributed system, and to achieve an adaptability to change of the manufacturing environment.

• MALSORI
• /
• no.51
• /
• pp.137-149
• /
• 2004

A weather forecast service with speech recognition is described. This service allows users to get the weather information of all the cities by saying the city names with just one phone call, which was not provided in the previous weather forecast service. Speech recognition is implemented in the intelligent peripheral (IP) of the advanced intelligent network (AIN). The AIN is a telephone network architecture that separates service logic from switching equipment, allowing new services to be added without having to redesign switches to support new services. Experiments in speech recognition show that the recognition accuracy is 90.06% for the general users' speech database. For the laboratory members' speech database, the accuracies are 95.04% and 93.81%, respectively in simulation and in the test on the developed system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.19-22
• /
• 2001

In this paper, Streaming Current Monitor (SCM), Pilot Filter (PF) and Coagulant Feeding System(CFS) for fuzzy neural network are used as a coagulation control method in WTP and the results are compared. Several parameters such as coagulant dosage, pH, and turbidity have been changed to find the response characteristic of each equipment. SCM, PF and CFS responded for certain parameters but the range of sensitivity was different each other. It is demonstrated that WTP will be operated more efficiently when SCM, PF and CFS are used as coagulation control strategy.