• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.4
• /
• pp.87-92
• /
• 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 Korea Society of Industrial Information Systems
• /
• v.29 no.3
• /
• pp.67-77
• /
• 2024

Increasing energy efficiency in factories is an activity aimed at optimizing resource allocation in manufacturing processes to establish production plans. However, this strategy may not apply effectively when night shifts are unavoidable. Additionally, continuous fluctuations in production requirements pose challenges for its implementation in the factory. Recently, with the rapid proliferation of electric vehicles (EVs), technology utilizing electric vehicle batteries as energy storage systems has gained attention. Technology using these batteries can be an alternative for factory energy management. In this paper, a factory energy management method using EV batteries is proposed. The proposed method is analyzed using PSCAD/EMTDC software, considering the state of charge of EV batteries and Time-of-Use (TOU) rates. The proposed method was compared with production scheduling established considering predicted power usage and TOU rates. As a result, production scheduling saved 4,152 KRW per day, while the proposed method saved 7,286 KRW in electricity costs. Through this paper, the possibility of utilizing EV batteries for factory energy management has been demonstrated.

• Journal of Institute of Convergence Technology
• /
• v.3 no.1
• /
• pp.37-40
• /
• 2013

Plant factory industry as a new agriculture is in the spotlight. In this paper, we experimented plant factory applied photovoltaic system and LED lighting. For growing the plant, red, blue and white LED were placed into 1:4:3. Electric power generated by the photovoltaic system was supplied on DC power supply instead of AC. The designed and experimented power generation amount per day of photovoltaic system were 2,860 Wh and 2,272 Wh respectively. Plant has not been grown at the dead space of LED lighting so it is required to array LED lighting.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.4
• /
• pp.211-218
• /
• 2012

In this paper, we propose a system architecture of the AMI to be applied in the modern agricultural sector. Agricultural electricity costs in South Korea is very inexpensive compared with other industries. It is expected to increase oil prices to rise over the medium to long term so the facilities must to be installed for farmers in terms of energy savings and energy costs. The research and development of plant factory which can replace the ills of modern agriculture is very active. The technologies of smart grid and plat factory are good paradigm of next generation agricultural sector. Good use of smart grid technologies, the traditional energy consumption industries, agriculture sector can be self-sufficiency industry. In this article the AMI architecture is developed and it will be applicable for modern farmers plant factory.

• Journal of Power System Engineering
• /
• v.18 no.6
• /
• pp.159-165
• /
• 2014

On this work, the importance of industrial ventilation was investigated and examined the theoretical point and problems about general ventilation of factory exposed on high temperature during summer. As a case study, the ventilation planning of the printed circuit board (PCB) etching process for an electronic company was carried out and each of those characteristics were compared by installing actual ventilation systems and measuring the changing state of the working environment in accordance with ventilation method during summer. The purpose of the study is to present an efficient ventilation method for a factory with a closed structure under high temperature environment. In summary, for a factory with a sealed structure such as the target PCB manufacturing factory in this study, the forced supply and exhaust method was the most appropriate ventilation method for maintaining a low.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.4
• /
• pp.769-779
• /
• 2015

In this paper, the ideal standard design and construction of plant factory systems with the Green IT technologies is proposed. For feasibility and problem analysis, a container-type plant factory which was integrated with hardware and software of elemental technologies was operated as a test bed. This operation testing and research will be the foundation of the future construction and operation of large plant factories.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.817-819
• /
• 2019

다양한 학습 모델이 발전하고 있는 지금, 학습을 통한 다양한 시도가 진행되고 있다. 이중 에너지 분야에서 많은 연구가 진행 중에 있으며, 대표적으로 BEMS(Building energy Management System)를 볼 수 있다. BEMS의 경우 건물을 기준으로 건물에서 생성되는 다양한 DATA를 이용하여, 에너지 예측 및 제어하는 다양한 기술이 발전해가고 있다. 하지만 FEMS(Factory Energy Management System)에 관련된 연구는 많이 발전하지 못했으며, 이는 BEMS와 FEAMS의 차이에서 비롯된다. 본 연구에서는 실제 공장에서 수집한 DATA를 기반으로 하여, 전력량 예측을 하였으며 예측을 위한 기술로 시계열 DATA 분석 방법인 LSTM 알고리즘을 이용하여 진행하였다.

• The Journal of Economics, Marketing and Management
• /
• v.8 no.3
• /
• pp.23-36
• /
• 2020

Purpose: The purpose of this study is to identify the strategic direction of organizations and their employees to efficiently utilize smart factories and enhance business performance among Korean manufacturing companies. Research design, data, and methodology: We derived a structured research model to check the mediated effect of utilization of smart factory between the characteristics of smart factory and the innovation activities. Results: Quality characteristics of smart factory and Innovation activities were all found to have a statistically significant effect on utilization of smart factory, utilization of smart factory was found to have a statistically significant effect on the business performance. And it has been shown that the utilization of smart factory is partially mediated relative to the quality characteristics of smart factory and business performance and relative to innovation activities and business performance. Conclusions: Smart factory builders can reflect the areas that affect utilization of the smart factory in their strategies by considering the quality characteristics of the smart factory and innovation Activities. Therefore, smart factory builders can identify the quality characteristics of smart factory and reflect them in the process and analyze active utilize measures through the innovative activities of the employees of the organization, thereby influencing business performance.

• Journal of the Korean Solar Energy Society
• /
• v.34 no.5
• /
• pp.43-52
• /
• 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 Society of Machine Tool Engineers Conference
• /
• 2004.04a
• /
• pp.459-465
• /
• 2004

Micro-factory is a small system to produce a small parts and this manufacturing system has advantages such as energy saving, resources saving, and manufacturing space saving. Micro-factory are classified according to production type and has many applications in various industry. In this paper, the basic concept and applications of micro-factory are introduced.