• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.49-58
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• 2019

In this paper, we propose an edge cloud platform architecture for implementing smart factory. The edge cloud platform is one of edge computing architecture which is mainly focusing on the efficient computing between IoT devices and central cloud. So far, edge computing has put emphasis on reducing latency, bandwidth and computing cost in areas like smart homes and self-driving cars. On the other hand, in this paper, we suggest not only common functional architecture of edge system but also light weight cloud based architecture to apply to the specialized requirements of smart factory. Cloud based edge architecture has many advantages in terms of scalability and reliability of resources and operation of various independent edge functions compare to typical edge system architecture. To make sure the availability of edge cloud platform in smart factory, we also analyze requirements of smart factory edge. We redefine requirements from a 4M1E(man, machine, material, method, element) perspective which are essentially needed to be digitalized and intelligent for physical operation of smart factory. Based on these requirements, we suggest layered(IoT Gateway, Edge Cloud, Central Cloud) application and data architecture. we also propose edge cloud platform architecture using lightweight container virtualization technology. Finally, we validate its implementation effects with case study. we apply proposed edge cloud architecture to the real manufacturing process and compare to existing equipment engineering system. As a result, we prove that the response performance of the proposed approach was improved by 84 to 92% better than existing method.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.717-726
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• 2020

The physical characteristics of the major varieties of perilla were analyzed to use as basic data for the design of a high-quality, high-efficiency perilla cleaner and stone separator. Because the size, thousand-grain weight, angle of repose, angle of friction, bulk density and terminal velocity of perilla have significant differences according to the perilla variety, the different of characteristics by variety should be considered for performance improvement of a perilla cleaner and stone separator. Therefore the cleaner and stone separator using a sieve could be improved by the application of a detachable sieve or by using equipment such as a 2 - 3 stage sieve and regulating the slope. Moreover, because differences in the terminal velocity occur due to the differences in the size and thousand-grain weight according to the perilla variety, a blower with an adjustable fan speed was considered for the design of the improved cleaner. Additionally, it was shown that the length of perilla has the greatest correlation based on a comparison of the coefficients of the other characteristics. Accordingly, the length of perilla could be used as a major factor for the fine adjustment and parts replacement of the device. These results can be used as basic data for a high-quality, high-efficiency perilla cleaner and stone separator. In the future, the development of the machine and follow-up studies based on the basic data are needed to determine the optimized operating conditions and mechanism of action.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.100-106
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• 2021

Measuring Intima-media thickness (IMT) with ultrasound images can help early detection of coronary artery disease. As a result, numerous machine learning studies have been conducted to measure IMT. However, most of these studies require several steps of pre-treatment to extract the boundary, and some require manual intervention, so they are not suitable for on-site treatment in urgent situations. in this paper, we propose to use deep learning networks U-Net, Attention U-Net, and Pretrained U-Net to automatically segment the intima-media complex. This study also applied the HE, HS, and CLAHE preprocessing technique to wireless portable ultrasound diagnostic device images. As a result, The average dice coefficient of HE applied Models is 71% and CLAHE applied Models is 70%, while the HS applied Models have improved as 72% dice coefficient. Among them, Pretrained U-Net showed the highest performance with an average of 74%. When comparing this with the mean value of IMT measured by Conventional wired ultrasound equipment, the highest correlation coefficient value was shown in the HS applied pretrained U-Net.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.208-219
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• 2021

In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.51-56
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• 2022

With the development of industrialization, the amount of food and waste is rapidly increasing. Accordingly, the government is aware of the seriousness and is making efforts in various ways to reduce it. As a part of that, the volume-based food system was introduced, and although there were several trials and errors at the beginning of the introduction, it shows a reduction effect of 20 to 30%. These results suggest that the volume-based food system is being established. However, the waste is caused by foreign substances in the process of recycling resources by collecting them from the 1st collection to the 2nd collection process. Therefore, in this study, to solve these problems fundamentally, artificial intelligence is applied to classify foreign substances and improve them. Due to the nature of food waste, there is a limit to obtaining many images, so we compare several models based on CNNs and classify them as abnormal data, that is, CNN-based models are trained on various types of foreign substances, and then models with high accuracy are selected. We intend to prepare improvement measures for maintenance, such as manpower input to protect equipment and classify foreign substances by applying it.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.81-87
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• 2006

The rubblization technique is breaking the aged concrete pavement slab into rubblized concrete aggregate, and use it as an base material at its original position, then builds overlay above the rubblized base. This method has been successively used in USA due to the advantage of good constructibility, cost-effectiveness as well as the capability of preventing of reflection cracks. However, constructibility and economic performance of rubblization on typical Korean concrete pavements needed to be investigate since to typical Korean concrete pavements have thick slab, as well include lean concrete subbase course. Multi-head type breaker suitable for Korean condition was designed and developed. This multi-head type breaker was designed to rubblize old concrete to the suggested optimum rubblized-depth and rubblized-concrete-aggregate size to prevent reflection crack and maintain high bearing capacity. This machine was used for the test of rubblization of old concrete pavement on a non-use old concrete and a in-serviced road. In these two tests, engineering properties of rubblized base and constructability and cost were investigated. In both tests, the old concrete rubblized to targeted size and depth, and high-level bearing capacity was achieved. Also, superior constructability and lower cost compared with traditional reconstruction was examined.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.320-327
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• 2023

In this study, an FPGA-based sealer inspection system was developed to inspect the sealer applied to install vehicle glass on a car body. The sealer is a liquid or paste-like material that promotes adhesion such as sealing and waterproofing for mounting and assembling vehicle parts to a car body. The system installed in the existing vehicle design parts line does not detect the sealer in the glass rotation section and takes a long time to process. This study developed a line laser camera sensor and an FPGA vision signal processing module to solve this problem. The line laser camera sensor was developed such that the resolution and speed of the camera for data acquisition could be modified according to the irradiation angle of the laser. Furthermore, it was developed considering the mountability of the entire system to prevent interference with the sealer ejection machine. In addition, a vision signal processing module was developed using the Zynq-7020 FPGA chip to improve the processing speed of the algorithm that converted the profile to the sealer shape image acquired from a 2D camera and calculated the width and height of the sealer using the converted profile. The performance of the developed sealer application inspection system was verified by establishing an experimental environment identical to that of an actual automobile production line. The experimental results confirmed the performance of the sealer application inspection at a level that satisfied the requirements of automotive field standards.

• The Journal of Bigdata
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• v.8 no.2
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• pp.83-95
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• 2023

Big data analytics and AI play a critical role in the development of smart plants. This study presents a big data platform for plant data and an 'AutoML platform' for AI-based plant O&M(Operation and Maintenance). The big data platform collects, processes and stores large volumes of data generated in plants using Hadoop, Spark, and Kafka. The AutoML platform is a machine learning automation system aimed at constructing predictive models for equipment prognostics and process optimization in plants. The developed platforms configures a data pipeline considering compatibility with existing plant OISs(Operation Information Systems) and employs a web-based GUI to enhance both accessibility and convenience for users. Also, it has functions to load user-customizable modules into data processing and learning algorithms, which increases process flexibility. This paper demonstrates the operation of the platforms for a specific process of an oil company in Korea and presents an example of an effective data utilization platform for smart plants.

• Journal of Animal Environmental Science
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• v.2 no.1
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• pp.27-39
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• 1996

A survey was conducted for dairy farmer to estimate the optimum number of machine and equipment in 1994. Labor hours, operation costs and operation methods for each dairy processing were investigated and analyzed for the farmers to find the expected numbers of machine and equipment on the basis of the desired farm scale. And also, the estimated models were compared and analyzed with the conventional models which more than half dairy farmers used bucket milker in tie stall barn. Some of the results are as follows : 1. Analysis results of conventional model showed that a dairy farm could raise to 15 heads of dairy cow with family labor of 1.5 men, labor hours of 2, 700 in you and total operation costs of 734 thousand won per head. 2. The result, used in conjunction with minimum operation costs in tie stall barn, showed that 28 dairy cows could be raised by using concentrates feeding by hoppers, water supply by water cups, milking by pipeline milker, and manure cleaning by barn cleaner with total operation costs of 520 thousands won per head. 3. The total operation costs of a loose barn system is higher than those of tie stall barn system to raise about 30 heads. For the loose barn system, the herringbone parlour was used for milking, concentrate feeding by automatic concentrate feeder, water supply by thermal insulation feeder, and manure cleaning by scraper with total operation costs of 582 thousands won per head every year.

• Journal of Sericultural and Entomological Science
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• no.12
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• pp.37-45
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• 1970

The processing management forms of our country's filature factories in 1969 are summarized as follows. (1) About 80％ of total cocoon collection is made within 5 days involving peak day, and 10％ of cocoon collection is finished until 3 days before and after the peak day, (2) About 92％ of alive cocoons transported on unpaved road, and about 40％ of the cocoons purchased by all factories are loaded on trucks from common selling station which is far beyond 40km, therefore a new packing system of alive cocoons to drop the damage of cocoon qualities, should be taken. (3) 22％ of all factories in our. country have only low-temperature cocoon drying machine. Therefore the installment of hot-air cocoon drying machine is required urgently. (4) In view of cocoon qualities in our country, the grouping method of cocoon for reeling. taken by about 50％ of the factories at percent, which classify cocoons for reeling as high group (1,2,3,4 grades) and low group(5,6 grades), will have to be replaced by the method tat classify them high group (1,2 grades) middle group (3,4 grades), low group (5,6 grades). (5) The .ratio of cocoon assorting stood about 10％ in multi-ends reeling, about 15％ in automatic reeling, conclusively, the ratio of cocoon assorting for automatic reeling was higher tan that for multi-ends reeling. One person's ability for a day in cocoon assorting reaches to about 80-100kg. (6) Cocoon cooking condition requires the increase of the cooking time, the pressure and temperature used to be prolonged as much as the qualities of cocoons are material cocoon ior automatic and double cocoon machines are treated uncompletely. (7) Automatic silk reeling is being performed at 1-2$^{\circ}C$ lower in reeling water temperature and operated at about twice velocity. (8) The temperature and humidity of rereeling room stood at 25$^{\circ}C$, 67.2％ R.H and 32.3$^{\circ}C$, 51.9％ R.H of rereeling machine are showed, Average rereeling velocity is 233m/min and large reefs charged for one person are 7.5 reels and form of skein used in all factories is double skein. (9) About 73％ of water sources for filature used under-earth water. About 48％ of all filature factories in our country have not yet water purifying equipments. Installation of the equipment for these factories seems to be urgent, (10) Denier .balance, sizing reel, seriplane, are being used in most factories as self-inspection apparatus. (11) More than 90％ of the factories use the vacum tank in rereeling process and about 20％ of them use it in cocoon cooing process (12) Only 21％ of the factories use chemicals in filature process. About all them use "Seracol 100" in cocoon cooking process and "Seracol 500" in rereeling process, (13) Above survey results explain each all factories show large difference in the processing management. Therefore, it is believed that intercommunication through seminar or technical exchange will contribute to the production evaluation of cocoon in our filature industry.