• Journal of the Korean Solar Energy Society
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• v.34 no.5
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• pp.43-52
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• 2014

A plant factory system is getting the spotlight as alternatives to cope with the weather anomaly and food crisis because of the global warming. A study on 'Plant Processing Factory System' has been proceeded to develope 'low-carbon green growth' since our government selected it as the green technologies in 2010. The plant factory has played a major role in growth industries connected to many other fields like low-carbon as well as lighting and automated system. This study is aimed to solve the problems on low productivity and health problem of plant workers caused by highly concentrated carbon dioxide and low temperature in each process in the plant factory. It is aimed to research data to understand the actual conditions of plant workers and improve the thermal environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.923-924
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• 2014

스마트 기기의 보급은 산업 및 개인생활의 많은 영향을 주었으며, 스마트 기기를 이용한 다양한 서비스 모델에 대한 연구가 진행되고 있다. 특히 오픈 소스 프로그래밍 언어로 부각되고 있는 프로세싱(Prodessing) 개발 환경을 사용하여 안드로이드 운영체제를 사용하는 모바일 장치에 대한 어플리케이션을 간단하고 쉽게 만들 수 있다는 장점이 있다. 이런한 프로세싱 기반의 개발환경을 통하여 개발된 안드로이드 어플리케이션은 식물공장의 전체적인 환경요소를 모니터링 함과 동시에 단순화된 식물공장 내부를 원격에서 관리하고 제어할 수 있는 종합적인 관리시스템을 설계하고자 한다. 본 논문에서는 MIT 미디어 구룹에서 시작된 프로세싱 개발환경을 통하여 안드로이드 기반의 어플리케이션을 개발하여 식물공장에 대한 환경 모니터링과 환경 제어시스템을 제안하고자 한다.

• 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.

• 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).

• IE interfaces
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• v.11 no.3
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• pp.1-13
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• 1998

This paper addresses a scheduling scheme for Flexible Flow Shop(FFS) in the case that a factory is a sub-plant of an electronic device manufacturing plant. Under this environment, job orders for the sub-plants in the production route are generated together with job processing time bucket when the customer places orders for final product. The processing time bucket for each job is a duration from possible release date to permissible due date. A sub-plant modeled FFS should schedule these jobs orders within time bucket. Viewing a Printed Circuit Board(PCB) assembly line as a FFS, the developed scheme schedules an incoming order along with the orders already placed on the scheduled. The scheme consists of the four steps, 1)assigning operation release date and due date to each work cells in the FFS, 2)job grouping, 3)dispatching and 4)machine allocation. Since the FFS scheduling problem is NP-complete, the logics used are heuristic. Using a real case, we tested the scheme and compared it with the John's algorithm and other dispatching rules.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.5
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• pp.29-37
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• 2017

In this study, real-time monitoring is carried out in the factory site for product quality control such as improvement of productivity through facility automation, improvement of product quality, improvement of factory environment, check of facility maintenance status and check of product defect, And to establish a smart factory for the purpose of protecting the personal environment of the worker. The company is an auto parts company located in the province. The main research content is development of automation and monitoring system of oil filter clipping necessary for smart factory. Smart factory oil filter clipping automation is divided into electric air parts, solenoid valve and other parts processing process. Smart factory quality inspection monitoring system is implemented by server PC and S / W, client software, Operator PC, operating program, and input terminal application. This research data is expected to be very useful data for the auto parts venture companies that are promoting smart factories.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2297-2311
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• 1994

This paper presents the study on the development of a DNC, system IPIS(Interactive Plant Information System)/DNC, which can manage NC machines and robots as a distributed control method in the machine. processing factory. The IPIS/DNC system is composed of a host computer, satellites and NC machines. A set of software modules are developed on the host computer and the satellites separately. By modularizing each functions of the IPIS/DNC system and using multi-taking method, the functions such as NC program management, NC program distribution, and shop monitoring can be performed on the host computer, and the functions such as NC program transfer to the NC machines, and NC program editing can be performed on the satellites. A Relational database which is linked with job scheduling system is used for IPIS/DNC system.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.553-555
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• 2011

본 논문에서는 식물공장 내에 조도 변화를 측정하여 최적의 생육환경을 자동적으로 제어할 수 있도록 스마트폰 어플리케이션과 스마트폰에 내장된 조도센서의 결합을 통한 LED 제어 시스템을 제안한다. 스마트폰에 내장된 조도센서와 어플리케이션에 실행을 통해 외부 환경의 조도를 측정하고 무선 통신을 이용하여 식물공장 내 LED를 자동으로 제어한다. 제안된 시스템은 식물공장 내 LED의 스마트제어를 통한 전력낭비와 이산화탄소 배출량을 줄임으로써 제조원가 감소 및 품질향상에 기여할 수 있다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of Bio-Environment Control
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• v.22 no.2
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• pp.100-107
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• 2013

Unlike general microwave, QRD (Quadratic Residue Diffusor) Microwave used in this study is known as a new technology that enhances the sterilization effect with low power because it is possible to induce the average sterilization by changing wavelength phase difference. Therefore, basic research was conducted on the function that could sterilize culture media for plant factory by using environmentally friendly and low energy consuming QRD Microwave. The results are as follows: It was confirmed that there was no external deformation in the polyurethane foam and rock wool medium when changing the microwave level between 2 and 8 kW in different water content of culture media. However, PDA solid media at 2 kW were not dissolved in 60 and 180 seconds. All of the media were dissolved in other processing. There was little difference in the microwave irradiation level and surface temperature of the strain according to the processing time between Bacillus sp. and Burkholderia sp. In the sterility test according to the microwave irradiation level and processing time, it was confirmed that both Bacillus sp. and Burkholderia sp. grew in the microwave level 2 kW regardless of time. In the microwave level 6 kW, all experimental groups except the processing of Burkholderia sp. for 60 seconds were sterilized, and all of Bacillus sp. was killed in the all experimental groups. In the microwave level 8 kW, it was confirmed that both Bacillus sp. and Burkholderia sp. were sterilized regardless of time. The temperature in microwave-processed media after contaminating strains to each medium was maintained at more than 100 in polyurethane foam and rock wool medium after 60 seconds. In general, it was shown that it was possible to sterilize after 60 seconds. Therefore, it is considered that Bacillus sp. and Burkholderia sp. which are the biggest problems in the plant factory can be adequately sterilized by QRD Microwave used in this study.