• Journal of the Korean Society for Precision Engineering
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• v.32 no.1
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• pp.17-24
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• 2015

Smart factory requires 4 Zero factors including Zero Waiting-time, Zero Inventory, Zero Defect, Zero Down-time) that needs IT convergence for production resources of 4M1E(Man, Machine, Material, Method, Energy) in real time and event processing in all type of manufacturing enterprises. This paper will be explaining about core emerging production IT convergence technologies including cyber device security, 4M1E integration, real time event driven architecture, common platform of manufacturing standard applications, smart factory to-be model for small and medium manufacturing enterprises.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.67-71
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• 2016

The purpose of this study was to explore olfactory sensitivity of odors from injection molding processing. To do this, the experiment was carried out in an injection molding factory, and participants were exposed to the environment where odor-substances (Formaldehyde, Benzene, Toluene, Ethylbenzene, Xylene, Styrene) exist. In addition, we used the subjective scale using semantic adjectives as an olfactory sensitivity. As a result, the assessment structure of olfactory sensitivity was composed of eight factors (irritant, thermal, tense, unique, like-dislike, active, stable, masculine), and the main factor which was irritant characteristics explained 20% of the total olfactory sensibility. These results suggested that odors from injection molding processing would cause more negative emotional responses than the flavor which is mainly used in olfactory sensitivity. This study, as a basic study of the improvement in a factory environment for the efficiency of work, has limits in that it was conducted to the extent of identifying the olfactory sensitivity structure of those who were at a laboratory and who were exposed to the environment of odor substance induced in the injection molding processing. Therefore, for the method of removing malodorous substance, the effect of materials which can neutralize it, and the comparison of a direct performance in the environment where negative sensitivity structure exists, a series of studies which aim to improve the environment of injection molding factories, such as performance assessment in the environment of a factory and an office need to be conducted. It is expected that when these studies are put together, the improvement guidelines will be provided as a type that can maximize the effectiveness of work in the factory environment where injection molding processing is done.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1832-1842
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• 2010

This paper introduces a new automatic processing system: "Contents Factory" for the mass production of contents. Through the contents factory, we provide an authoring environment to improve the usability and the efficiency in producing contents. The contents factory integrates recycling techniques for contents resources, contents development engines, authoring tools, and interfaces into a total processing system. Since it is multi-platform based including mobile devices as well as PCs, one can easily produce complete PC and mobile contents from raw resources. We produced an example, "Sejong square" via the contents factory in order to demonstrate its effectiveness and usability.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.219-227
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• 2019

Manufacturing methods have been changed from labor-intensive methods to technological intensive methods centered on manufacturing facilities. As manufacturing facilities replace human labour, the importance of monitoring and managing manufacturing facilities is emphasized. In addition, Big Data technology has recently emerged as an important technology to discover new value from limited data. Therefore, changes in manufacturing industries have increased the need for smart factory that combines IoT, information and communication technologies, sensor data, and big data. In this paper, we present strategies for existing domestic manufacturing factory to becom big data based smart-factory through technologies for distributed storage and processing of manufacturing facility data in MongoDB in real time and visualization using R programming.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.36T no.2
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• pp.42-47
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• 1999

This paper suggests a model of a visual information system for factory automation. The model is composed of a visual processing system with client-server model and RPC(Remote Procedure Calling); a main server for controlling the whole factory automation process; and a processing server which processes the visual information only. To verify its efficiency, the suggested model is realized on the bill recognition system.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.87-92
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• 2019

This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.9
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• pp.85-92
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• 2020

In this study, the automatic processing of the wing ribs of large aircraft was simulated. Specifically, in the simulation for the automatic processing of the fly ribs, the process of the automated loading device with a robot was examined, along with the wing rib processing and manufacturing automation processes. Moreover, the process time, corresponding to all the stages in the wing rib processing, was calculated. The results pertaining to the machining and manufacturing times of 34 wing ribs (Nos. 1-17), as obtained through the proposed simulation approach, indicated that the total machining time for the left and right wing ribs and rib guns was 537.7 h. The production time was calculated as 1,117.4 h. It is considered that the processing of the wing ribs of large aircraft can be automated in a factory, based on the results of the proposed simulation process.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.2
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• pp.51-58
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• 2014

Manufacturing industry is one of the core sectors providing national competitiveness and economical impact Today's manufacturing industry is required to fulfill so called Sustainable Factory paradigm from the perspectives of environmental and social development. To cope with the requirements, researches for achieving sustainability in manufacturing system are actively carried out in the world from various perspectives. In this paper, we analyzed systemic characteristics of sustainable manufacturing system, and developed verification & validation strategy based on traceability between system requirement and functionality. The developed methods were applied to a European Project called the Foundation for the Sustainable Factory of the Future (FoFdation). Specifically, we analyzed and verified the deliverables of FoFdation by deriving systems architecture in terms of Component, Function, and Items. The results indicated that the FoFdation is pretty much compliant with the concept of Ubiquitous Factory, and can be used as an International Reference Model for the Smart Factoy, a world wide hot topic under the paradigm of IOT (Internet-Of-Things), if information processing part is supplemented.

• Architectural research
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• v.15 no.3
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• pp.167-174
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• 2013

Due to increasing competition of construction companies, it is required to optimize the management of construction projects and "lean" concepts are rapidly spreaded in construction industry. Steel work accounts for a large proportion in construction work, and a variety of attempts to efficiently perform steel work has currently made. And since rebar (Engineer-to-Order) can be engineered through design once order is placed, it gives the great impact on construction, thus, entire management is required. The purpose of this study is to present the method to increase the efficiency of field processing method of steel work in terms of lean construction. Once we examine process of steel work and identify the flow, we would like to analyze which processes should be improved through value analysis approach and present the improvement plans. Also, this study examines cases of field processing and factory processing, and it identifies the waste factors in the procurement process. Finally, this study would like to present the result of analysis from the perspectives of value. The rebar delivery process is divided into several steps and the duration of every step is surveyed. Using duration data, VAT (Value added time) can be calculated for analyzing the efficiency of the process.