• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• The Journal of Korean Academy of Prosthodontics
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• v.54 no.3
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• pp.210-217
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• 2016

Purpose: The aim of this study was to evaluate the marginal and internal adaptation of monolithic zirconia restoration made without physical model by digital intraoral scanner. Materials and methods: A prospective clinical trial was performed on 11 restorations as a pilot study. The monolithic zirconia restorations were fabricated after digital intraoral impression taking by intraoral scanner (TRIOS, 3shape, Copenhagen, Denmark), computer-aided designing, and milling manufacturing process. Completed zirconia crowns were tried in the patients' mouth and a replica technique was used to acquire the crown-abutment replica. The absolute marginal discrepancy, marginal gap, and internal gap of axial, line angle, and occlusal part were measured after sectioning the replica in the mesiodistal and buccolingual direction. Statistical analysis was performed using Kruskal-Wallis and Mann-Whitney U test (${\alpha}=.05$). Results: From the adaptation analysis by replica, the statistically significant difference was not found between mesiodistal and buccolingual sections (P>.05), but there was significant difference among the measurement location (P<.01). The amount of absolute marginal discrepancy was larger than those of marginal gap and internal gap (P<.01). Conclusion: Within the limitations of this study, the adaptation accuracy of model-free monolithic zirconia restoration fabricated by intraoral scanner exhibited clinically acceptable result. However, the margin of zirconia crown showed tendency of overcontour and cautious clinical application and follow up is necessary.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.125-140
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• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.70-81
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• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Journal of Navigation and Port Research
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• v.47 no.3
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• pp.167-173
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• 2023

The manufacturing industry is the backbone of the Korean economy. Among them, the petrochemical industry is a strategic growth industry, which makes a profit through reexports based on eminent technology in South Korea which imports all of its crude oil. South Korea imports whole amount of crude oil, which is the raw material for many manufacturing industries, by sea transportation. Therefore, it must respond swiftly to a highly volatile tanker freight market. This study aimed to make an early warning model of crude oil shipping market using a signal approach. The crisis of crude oil shipping market is defined by BDTI. The overall leading index is made of 38 factors from macro economy, financial data, and shipping market data. Only leading correlation factors were chosen to be used for the overall leading index. The overall leading index had the highest correlation coefficient factor of 0.499 two months ago. It showed a significant correlation coefficient five months ago. The QPS value was 0.13, which was found to have high accuracy for crisis prediction. Furthermore, unlike other previous time series forecasting model studies, this study quantitatively approached the time lag between economic crisis and the crisis of the tanker ship market, providing workers and policy makers in the shipping industry with an framework for strategies that could effectively deal with the crisis.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.

• Journal of Dental Rehabilitation and Applied Science
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• v.40 no.3
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• pp.169-178
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• 2024

Recently, several attempts have been made to integrate AI into the field of dentistry. To overcome the limitations of traditional fixed prosthetic fabrication methods such as CAD-CAM (computer-aided design-computer-aided manufacturing), AI programs are being developed for automated crown fabrication, and various studies are underway to applicate in clinical situation. In these case studies, single-unit fixed prostheses were fabricated using an AI program (Dentbird Crown, Imagoworks Inc, Seoul, Korea) in both the anterior and posterior regions and the fabrication time and accuracy were compared with previously used CAD-CAM method. The first case is a 44-year-old woman who presented for re-fabrication of a zirconia prosthesis due to a prosthesis fracture on the lingual side of the upper right lateral incisor. The second case is a 53-year-old male patient who presented for a crown restoration on an upper left first molar following root canal treatment, where he received a final zirconia restoration. In both cases, the first prosthesis was designed manually using a CAD program, the second prosthesis was designed using AI alone, and the third prosthesis was designed using AI and then modified by CAD program, and the three designs were superimposed to compare suitability. When evaluated after temporary placement, the final prosthesis demonstrates adequate stability, retention and support, resulting in functional and esthetic satisfaction.

• Journal of the Korean Academy of Esthetic Dentistry
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• v.30 no.2
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• pp.71-90
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• 2021

The virtual patient dataset is a collection of diagnostic data from various sources acquired from a single patient into a coordinate system of three-dimensional visualization. Virtual patient dataset makes it possible to establish a treatment plan, simulate various treatment procedures, and create a treatment planning delivery device. Clinicians can design and simulate a patient's smile on the virtual patient dataset and select the optimal result from the diagnostic process. The selected treatment plan can be delivered identically to the patient using manufacturing techniques such as 3D printing, milling, and injection molding. The delivery of this treatment plan can be linked to the final prosthesis through mockup confirmation through provisional restoration fabrication and delivery in the patient's mouth. In this way, if the diagnostic data superimposition and processing accuracy during the manufacturing process are guaranteed, 3D digital smile design simulated in 3D visualization can be accurately delivered to the real patient. As a clinical application method of the virtual patient dataset, we suggest a decision-making method that can exclude occlusal adjustment treatment from the treatment plan through the digital occlusal pressure analysis. A comparative analysis of whole-body scans before and after temporomandibular joint treatment was suggested for adolescent idiopathic scoliosis patients with temporomandibular joint disease. Occlusal plane and smile aesthetic analysis based on the virtual patient dataset was presented when treating patients with complete dentures.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2430-2434
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• 2005

Automatic FPC punching instrument for the improvement of working condition and cost saving is introduced in this paper. FPC(flexible printed circuit) is used to detect the contact position of K/B and button like a cellular phone. Depending on the quality of the printed ink and position of reference punching point to the FPC, the resistance and current are varied to the malfunctioning values. The size of reference punching point is 2mm and the above. Because the punching operation is done manually, the accuracy of the punching degree is varied with operator's condition. Recently, The punching accuracy has deteriorated severely to the 2mm punching reference hall so that assembly of the K/B has hardly done. To improve this manual punching operation to the FPC, automatic FPC punching system is introduced. Precise mechanical parts like a 5-step stepping motor and ball screw mechanism are designed and tested and low cost PC camera is used for the sake of cost down instead of using high quality vision systems for the FA. 3D Mechanical design tool(Pro/E) is used to manage the exact tolerance circumstances and avoid design failures. Simulation is performed to make the complete vision based punching machine before assembly, and this procedure led to the manufacturing cost saving. As the image processing algorithms, dilation, erosion, and threshold calculation is applied to obtain an exact center position from the FPC print marks. These image processing algorithms made the original images having various noises have clean binary pixels which is easy to calculate the center position of print marks. Moment and Least square method are used to calculate the center position of objects. In this development circumstance, Moment method was superior to the Least square one at the calculation of speed and against noise. Main control panel is programmed by Visual C++ and graphical Active X for the whole management of vision based automatic punching machine. Operating modes like manual, calibration, and automatic mode are added to the main control panel for the compensation of bad FPC print conditions and mechanical tolerance occurring in the case of punch and die reassembly. Test algorithms and programs showed good results to the designed automatic punching system and led to the increase of productivity and huge cost down to law material like FPC by avoiding bad quality.

• Clean Technology
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• v.15 no.4
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• pp.265-272
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• 2009

In this study the experiments on the static adsorption of benzene were carried out using activated carbon made from sewage sludge. The experiment was performed at 303.15 K, 318.15 K and 333.15 K under the pressure up to 7.999kPa. Isothermal adsorption curves were obtained using Langmuir isotherm, Freundlich isotherm and Toth isotherm for comparison. Based on fitting the adsorption quantity of Benzene (q), the isothermal adsorption curves obtained from Langmuir isotherm and Toth isotherm showed the higher accuracy. Although there was little difference in accuracy between result from Langmuir isotherm and that from Toth isotherm, the adsorption quantity of Benzene (q) was expressed in terms of Langmuir isotherm because less parameters were required for Langmuir isotherm than for Toth isotherm. Moreover SEM images of the activated carbon from sewage sludge and the commercial activated carbon were taken to observe the pore size development. The results showed that the perforation development of the commercial activated carbon (DARCO A.C., SPG-100 A.C.) was better than that of activated carbon from sewage sludge. Adsorption quantity of benzene on commercial activated carbon was confirmed to be higher than that on activated carbon from sewage sludge. However the maximum adsorption quantity of benzene on activated carbon from sewage sludge was close to that on SGP-100 A.C. at 303.15K. Therefore, we may conclude that it is feasible to commercialize the process to manufacturing activated carbon from sewage sludge.