• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.527-537
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• 1990

This paper describes an intelligent control-based job scheduler, named ESIJOBS, for flexible manufacturing system. In order to construct rulebase of this system, traditional rules of job scheduling in FMS are examined and evaluated. This result and the repetitional simulations with graphic monitoring system are used to form the rulebase of ESIJOBS, which is composed of three parts:six part selection rules, four machine center selection rules, and twenty-one metarules. Appropriate scheduling rule sets are selected by this rulebase and manufacturing system status. The performances of all simulations are affected by random breakdowns of major FMS components during each simulation. Six criteria are used to evaluate the performance of each scheduling. The two modes of ESIJOBS are simulated and compared with combinational 24 rule-set simulations. In this comparison ESIJOBS dominated the other rule-set simulations and showed the most excellent performance particularly in three criteria.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.05a
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• pp.458-461
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• 2008

We carry out non-steady state finite element simulation of a porthole extrusion process for manufacturing a radiation pipe under isothermal assumption. It is assumed that welding takes place at the moment that the material contacts the plane of symmetry. Welding phenomena are revealed by observing the contacting mechanism of the material passed through the portholes. It is emphasized that mesh density control and intelligent remeshing during welding process govern the solution accuracy and the program applicability. AFDEX 3D is employed.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.1-8
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• 2021

This study proposes a systems engineering approach for the development of an advanced planning & scheduling (APS) system for a cosmetic case manufacturing factory. The APS system makes production plans and schedules based on the injection process, which consists of 27 plastic injection machines in parallel to control recommended inventory of products. The system uses machine operation/failure information and defective product/work-in-process tracking information to support intelligent scheduling. Furthermore, a genetic algorithm model is applied to handle the complexity of heuristic rules and machine/quality constraints in this process. As a result of the development, the recommended inventory compliance rate is improved by scheduling the 30-day production plan for 15 main products.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.3
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• pp.6-14
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• 2014

Touch panels are widely used in the modern display industry as the cover glass of smart mobile phones and tablet PCs. Glass cutting machines are commonly used to cut the panels into their proper sizes. Vibration of these glass cutting machines is assumed to be the main factor leading to the creation of burrs, notches, cracks, scratches and chips on the cut surfaces, eventually causing defects of the cover glass. In this study, the vibrations of a glass cutting machine used for the shearing of cover glass components were analyzed through an experiment and a computer simulation. The structural properties leading to vibration were also analyzed in an effort to determine design alterations which can suppress these vibrations. Moreover, each design alteration was applied to a computer simulation model to determine the effect of different alteration on suppressing vibration. The results show that simple design alterations can substantially suppress vibrations of glass cutting machines.

• Laser Solutions
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• v.11 no.4
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• pp.21-28
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• 2008

Remote Laser welding technology for manufacturing automotive body is studied. Laser welding and industrial robot systems are used for the robot based laser welding system. The laser system is used 1.6kW Fiber laser(YLR-1600) of IPG. The robot system is used HX130-02 of Hyundai Heavy Industry(payload : 130kg). The robot based laser welding system is equipped with laser scanner system for remote laser welding. The welding joints of steel plate and steel plate coated with zinc are butt and lapped joints. The quality test of the laser welding are through the observation the shape of bead on plate and cross-section of welding part. During past three years the laser system, 4kW Nd:YAG laser (HL4006D) of Trumpf was used and the robot system, IRB6400R of ABB (payload:120kg) was used. The new laser source, robot and laser scanner system are used to increase the processing speed and to improve the process efficiency. This paper introduces the robot based remote laser welding system to resolve the limited welding speed and accuracy of the conventional laser welding system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.200-205
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• 2005

The objectives of this study were to introduce the easiest and most proper applications of datamining in industrial processes. Applying datamining in manufacturing is very different from applying it in marketing. Misapplication of datamining in manufacturing system results in significant problems. Therefore, it is very important to determine the best procedure and technique in advance. In previous studies, related literature has been introduced, but there has not been much description of datamining applications. Research has not often referred to descriptions of particular examples dealing with application problems in manufacturing. In this study, a datamining roadmap was proposed to support datamining applications for industrial processes. The roadmap was classified into three stages, and each stage was categorized into reasonable classes according to the datamining purposed. Each category includes representative techniques for datamining that have been broadly applied over decades. Those techniques differ according to developers and application purposes; however, in this paper, exemplary methods are described. Based on the datamining roadmap, nonexperts can determine procedures and techniques for datamining in their applications.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.2
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• pp.137-146
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• 2019

This study proposed a new technique to control of mobile robot based on voice command for (Human-Robot Cooperative operation in manufacturing precess). High performance voice recognition and control system was designed In this paper for smart factory. robust voice recognition is essential for a robot to communicate with people. One of the main problems with voice recognition robots is that robots inevitably effects real environment including with noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we describe an robust voice recognition system which can robustly recognize voice by adults and students in noisy environments. It is illustrated by experiments the voice recognition performance of mobile robot placed in a real noisy environment.

• Journal of Power Electronics
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• v.19 no.2
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• pp.549-559
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• 2019

This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.65-73
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• 2010

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

• Electronics and Telecommunications Trends
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• v.36 no.1
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• pp.64-70
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• 2021

The future society will be changed through an artificial intelligence (AI) based intelligent revolution. To prepare for the future and strengthen industrial competitiveness, countries around the world are implementing various policies and strategies to utilize AI in the manufacturing industry, which is the basis of the national economy. Manufacturing AI technology should ensure accuracy and reliability in industry and should be explainable, unlike general-purpose AI that targets human intelligence. This paper presents the future shape of the "autonomous factory" through the convergence of manufacturing and AI. In addition, it examines technological issues and research status to realize the autonomous factory during the stages of recognition, planning, execution, and control of manufacturing work.