• Archives of design research
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• v.12 no.4
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• pp.89-98
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• 1999

The application of tool which has grown rapidly by the age was used for the product development, however as today the computer digitalization has been fixed to the necessary process in every factory-made mass production, making the sensitive desire of designer the digitalization through systematic, rational information database building from the planning level of product to the final mass production in such a environment change. It should satisfy a variety of needs of consumer. The enterprise that hopes to get a winner in the present age brought in computer with useful tool to process information efficiently. The computer has displayed much more excellent computation ability than human to come up to their expectation and the growth of electronic technology was possible to make the computer's high-efficiency, economy and integration. No matter what we have a good economy and integration. No matter what we have a good information there is no meaning unless we are able to use it' so we should take it out by the our need. Therefore, this paper observes a future-oriented possibility of computer & Telecommunication in information society, information-oriented design environment and the trends of minimal and integrated computer. We will improve the designer's ability to develop a novel product that have the diversification of them using application, aiming at computer utilization and image identification design strategy of product in the age of network telecommunication.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.392-399
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• 2023

This paper proposes a deep learning model to determine the region and depth of cabbage cores for robotic automation of the cabbage core removal process during the kimchi manufacturing process. In addition, rather than predicting the depth of the measured cabbage, a model was presented that simultaneously detects and classifies the area by converting it into a discrete class. For deep learning model learning and verification, RGB images of the harvested cabbage 522 were obtained. The core region and depth labeling and data augmentation techniques from the acquired images was processed. MAP, IoU, acuity, sensitivity, specificity, and F1-score were selected to evaluate the performance of the proposed YOLO-v4 deep learning model-based cabbage core area detection and classification model. As a result, the mAP and IoU values were 0.97 and 0.91, respectively, and the acuity and F1-score values were 96.2% and 95.5% for depth classification, respectively. Through the results of this study, it was confirmed that the depth information of cabbage can be classified, and that it can be used in the development of a robot-automation system for the cabbage core removal process in the future.

• Food Science and Preservation
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• v.31 no.4
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• pp.612-622
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• 2024

We examined the physicochemical properties and microbial safety of Enoki mushrooms during storage at 5℃ for 9 weeks, with different packaging containers that are corrugated, Al-coated, and without packaging (control). The weight change of Enoki mushrooms in the different containers due to moisture loss was 1.9%, 0.9%, 0.6% for control, corrugated, and Al-coated packaging, respectively. The degree of browning rapidly increased as the storage period increased in the control sample. However, corrugated and Al-coated packaging suppressed the browning degree. The changes of color L-, a-, and b-vlaues were minimal changes in Al-coated packaging. There was no significant difference in the total amino acids, polyphenol oxidase, and peroxidase in corrugated packaging and Al-coated packaging, regardless of the storage period. The microbial growth such as total aerobic bacteria, yeast, and mold of Enoki mushroom during the storage period, were significantly suppressed in Al-coated packaging samples as compared to the control and corrugated packaging. In conclusion, Al-coated packaging has beneficial effects such as preventing moisture loss, maintaining browning degree, inhibiting oxidative enzyme reaction, and ensuring microbial safety of Enoki mushrooms during the storage period. Al-coated packaging is considered effective for extending the shelf-life and improving the storage and distribution of mushrooms.

• Journal of Internet of Things and Convergence
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• v.10 no.5
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• pp.73-85
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• 2024

In recent years, China has been committed to promoting energy-saving and emission-reduction measures across various industries. In the steel production process, wet dust removal technology is widely adopted. However, the existing dust removal equipment, particularly the cyclone separator, suffers from insufficient dewatering efficiency, leading to a "rain" phenomenon during waste gas emission, which in turn causes secondary environmental pollution. The design of the guide vane wheel is crucial for enhancing the dewatering efficiency of the cyclone separator. Therefore, this study, based on fluid mechanics and flow field analysis theories, utilizes the FLUENT software to simulate and analyze the blade angle and flow area of the guide vane wheel. By combining the flow field analysis and simulation results with the specific parameters of the equipment, the structure of the cyclone separator's guide vanes was optimized and applied to actual production. Practice has proven that the optimized cyclone separator significantly improved dewatering efficiency and effectively reduced the rain phenomenon around the chimney, thereby enhancing environmental quality. The research of this project is conducive to the later application of artificial intelligence, the Internet of Things, big data, cloud computing, and other technologies in the 5G+ smart steel factory of the steel industry. It lays the foundation for using digital twin technology to carry out 3D modeling of the plant area, in order to facilitate the reappearance and simulation of the entire production process.