• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_1
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• pp.645-658
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• 2021

In this paper, we propose a new approach to intelligent control based on fuzzy logic for work efficiency improvement of smart factory by the applicaion of ariticulated robot. The intelligent control that is applied to the working process by the joint of robotic manipulator is the main focus to improve a work efficiency for implimentation of smart factory in general manufacturing process. In this study, we propose a new method of a fuzzy model and then develop a nonlinear relationship between interaction forces and manipulator position using a fuzzy model. The reliability of the proposed control method is illustrated by simulation and experiments.

• Proceedings of the Korea Association of Crystal Growth Conference
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• 1999.06a
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• pp.361-369
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• 1999

New method of control based upon a physical model of the Stepanov growth technique has been developed. The controller keeps the system stable and completely denies operator's interference into the process. The system demonstrates very reliable results under commercial production of shaped sapphire crystals.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.12
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• pp.297-304
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• 2019

The technological advances such as communication, sensor, and artificial intelligence lead smart factory construction. Smart factory aims at efficient process control by utilizing data from the existing automation process and intelligence technology such as machine learning. As a result of constructing smart factory, productivity increases, but costs increase. Therefore, small companies try to make a step-by-step transition from existing process to smart factory. In this paper, we have proposed a remote control system that support data collection, monitoring, and control for manufacturing equipment to support the construction of CNC cutting machine based small-scale smart factory. We have proposed the structure and design of the proposed system and efficient sensing data transmission scheme. To check the feasibility, the system was implemented for CNC cutting machine and functionality verification was performed. For performance evaluation, the web page access time was measured. The results means that the implemented system is available level.

• IE interfaces
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• v.19 no.1
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• pp.34-42
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• 2006

This paper presents a scheme for a hierarchical production scheduling and control system for a refrigerator factory with mixed model assembly lines. The setting of the factory is as follows. There are three mixed-model assembly lines called main line A, B and C and two batch lines that supply parts to the main lines. For each of the main lines, three work-centers are dedicated to them. The sub-lines and work-centers produce parts in batch type. An incoming production order from the master planner is characterized by its product type, amount, and due date. Under this situation, the proposed scheme has several features to schedule and control the above mentioned factory; 1) select the starting time and the place (assembly line) for an order processing, 2) devise a way to control orders to be processed as scheduled, and 3) reschedule orders when something unexpected happen. Finally, this paper provides a case study where the proposed scheme is applied to.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 1996.05a
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• pp.1-10
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• 1996

Factory-style plant production systems of various kinds are the final goal of greenhouse production systems. These systems facilitate planning for constant productivity per unit area and labor under various outside weather conditions, although energy consumption is intensive. Physical environmental control in combination with biological control can replace the use of agricultural chemicals such as insecticides, herbicides and hormones to regulate plants. In this way, closed systems which do not use such agricultural chemicals are ideal for environmental conservation for the future. Nutrient components in plants can be regulafied by physical environmental control including nutrient solution control in hydroponics. Therefore, specific contents of nutrients for particular plants can be listed on the container and be used as the basis of customer choice in the future. Plant production systems can be classified into three types based on the type of lighting: natural lighting, supplemental lighting and completely artificial lighting (Plant Factory). The amount of energy consumption increases in this order, although the degree of weather effects is in the reverse order. In the addition to lighting, factory-style plant production systems consist of mechanized and automated systems for transplanting, environmental control, hydroponics, transporting within the facility, and harvesting. Space farming and development of pharmaceutical in bio-reactors are other applications of these types of plant production systems. Various kinds of state-of-art factory-style plant production systems are discussed in the present paper. These systems are, in general, rather sophisticated and mechaized, and energy consumption is intensive. Factory-style plant production is the final goal of greenhouse production systems and the possibilities for the future are infinte but not clear.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.218-223
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• 1993

In this paper, we present a full digital control scheme which controls currents and speed of the permanent magnet AC servo motor with large range of bandwidth and high performance. The current equations of the permanent magnet AC servo motor are linearized by feedback linearization technique. Both acceleration feedforward terms and IP controllers, whose gains are functions of motor speed, are used in order to control motor currents. In addition the phase delays in current control loops are compensated by placing phase lead-lag compensators after current commands, which make it possible to avoid high gains in the current controllers. Unity power factor can be achieved by the proposed current controller. Pulsewidth modulation is performed by way of the well-known comparison with a triangular carrier signals. The velocity controller is designed on the basis of the linearized model of the permanent magnet AC servo motor by the proposed current controller. The performance of the entire control system is analyzed in the presence of uncertainty in the motor parameters. The proposed control scheme is implemented using the digital signal processor-based controller composed of an Analog Device ADSP 2111 and a NEC78310. The pulsewidth modulation (PWM) signals are generated through a custom IC, SAMSUNG-PWM1, which has the outputs of current controllers as input. The experimental results show that the permanent magnet AC servo motor can be always driven with high dynamic performance by the proposed full digital control scheme of motor speed and motor current.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.25-38
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• 2019

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11a
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• pp.1-30
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• 2000

The higher stage of development of plant factory is discussed, that involves technologies such as process control for the plant growth environment, mechanization for material handling, system control for production and computer applications. Further, the advantages of a plant factory include production stabilization, higher production efficiency, and better quality management of products through a shortened growing period, better conditions, lower labor requirements, and easier application of industrial concepts. Finally, to realize the ultimate plant factory using both solar and artificial light, the intelligent approach from control engineering, physiological ecology and artificial intelligence(AI) may be inevitable and introduced based on some works done by authors.

• Journal of Mechanical Science and Technology
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• v.14 no.4
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• pp.380-392
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• 2000

A typical production-distribution system consist of three main echelons representing the retailer, distributors, and a factory each with an on-site warehouse. The system is sufficiently general and realistic to represent many industrial situations. However, decision functions and parameters have been selected to apply particularly to the production and distribution of consumer durables. The flows included in the model are materials, orders, and those information flows needed to support the material and order-rate decisions. In this work, a realistic production-distribution system has been used as a basic model, which consists of three sectors: retailer, distributor, and factory. That system is a nonlinear 25th-order continuous system interconnected between the echelons. Using a modern control algorithm, a typical multi-echelon production-distribution system using a dynamic controller is numerically simulated in the nominal plant and in the perturbed plant when the piecewise constant manufacturing decision is limited by a factory manufacturing upper-limit due to capital equipment, manpower, and factory lotsize.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.109-115
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• 2019

Smart Factory is a part of and a key point of the 4th industrial revolution. It performs optimization from the whole viewpoint, using comprehensive data of the post-process data by utilizing various sensors, controllers, and mobile devices beyond the existing factory automation level. In this paper, we design and implement an IoT platform that can detect the safety factors of the workers, the environmental factors of the factory, and real time monitoring at the control center, among the fields to implement smart factory. To accomplish this, we construct a monitoring device that provides sensor information control, server transmission of sensor information, and visualization of collected information. By using this system, it is possible to maintain the temperature and humidity for the optimum working environment in the factory. and also, By using the beacon, it is possible to measure the working time of the worker and trace the position.