• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.97-104
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• 2019

The construction industry is heavily dependent on labor force as automation to building constructions is difficult due to its characteristics such on-site production, custom manufacturing production. Thus, while securing and fostering high-quality functional manpower for stable construction work are significant, the construction workforce has been persistently lacking compared to demand. Young workers are reluctant to enter the construction industry due to high labor intensity, unstable employment structure, and uncertainty for the future. The employment rate for new jobs in the construction industry is half as high as in others. Currently, the departments related to construction are organized in specialized high school to conduct training for young workers. The graduates have a low ratio of employment rate to the construction industry and functional capacities fallen short of expectations. In this study, the education and training conditions of specialized high schools were analyzed to derive problems and key improvements of the education system were drawn. As an improvement for the analysis results, it provides solutions such as giving advantages of previous education experience, expand industry-academic cooperation with businesses, and expand links with external educational institutions.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.69-78
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• 2023

With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.57-64
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• 2024

The introduction of Smart Factories has transformed manufacturing towards more objective and efficient line management. However, most companies are not effectively utilizing the vast amount of sensor data collected every second. This study aims to use this data to predict product quality and manage production processes efficiently. Due to security issues, specific sensor data could not be verified, so semiconductor process-related training data from the "SAMSUNG SDS Brightics AI" site was used. Data preprocessing, including removing missing values, outliers, scaling, and feature elimination, was crucial for optimal sensor data. Oversampling was used to balance the imbalanced training dataset. The SVM (rbf) model achieved high performance (Accuracy: 97.07%, GM: 96.61%), surpassing the MLP model implemented by "SAMSUNG SDS Brightics AI". This research can be applied to various topics, such as predicting component lifecycles and process conditions.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.159-173
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• 2002

The goal of this research is to develop of an intelligent injection mold process planning system using Case-Based Reasoning. Injection mold process planning is the planning of manufacturing process to produce an injection mold economically and efficiently. Automation of the process planning is required because the problems of handmade scheduling, the difficulty of training experts for process planning, the lack of domain experts, the spread of CAD/CAM system and flexible manufacturing. This research uses Case-Based Reasoning because the injection mold process planning is devised variously and complicatedly, but the process planning of similar injection molds is very similar to each other. The system that is developed by this research uses cases that are collected in a case base when planning the process of new injection mold. New injection mold process planning is devised by retrieving a case that was made from the most similar injection mold. This research presented and composed the cases of injection mold process planning, and devised a method of search and adaptation, and developed an intelligent injection mold process planning system with the experimental results.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.3
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• pp.280-287
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• 2009

High-tech microelectronics industry is known as one of the most chemical-intensive industries. In Korea, Microelectronics industry occupied 38% of export and 16% of working employees work in microelectronics industry. But, chemical information and health hazards of high-tech microelectronics manufacturing are poorly understood because of rapid development and its penchant for secrecy. We need to investigate on chemical use and exposure control. We Site-visits to 6 high-tech microelectronics manufacturing company which have cleanroom work using over 1,000kg organic solvents (5 semi-conductor chips and its related parts company, 1 liquid crystal display (LCD)). We reviewed their data on chemical use and ventilation system, and measured TVOCs (Total Volatile Organic Compounds) and carbon dioxide concentration. All cleanroom air passed through hepa filters to acheive low particle levels and only 1 cleanroom uses carbon filters to minimize the organic solvents exposures In TVOC screening test, Cleanroom for semi-conductor chips and its related parts company with laminar down flow system (e.g. class 1~100) showed nondetectable level of TVOCs concentration, but Cleanroom for liquid crystal display (LCD) with conventional flow system (e.g. class 1,000~10,000) showed 327 ppm as TVOCs. Acetone concentration in cleanroom for Jig cleaning, LC Injection, Sealing processes were 18.488ppm (n=14), 49.762 ppm (n=15), 8.656 ppm (n=14) as arithmetric mean. Acetone concentration in cleanroom for LCD inspection process was 40ppm (n=55) as geometric mean, where the range was 7.8~128.7ppm and weakly correlated with ventilation rate efficiency(r=0.44, p<0.05). To control organic solvents in cleanrooms, chemical and carbon filters should be installed with hepa filters. Even though their volatile organic compounds concentration was not exceed to occupational exposure limits, considering of entrance limited cleanroom environment, long-term period exposure effects and adverse health effects of cleanroom worker need further reseach.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.6
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• pp.458-467
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• 2016

Salt is the most important substance in physiological activities of the human body concerning transport of the ingested nutrients into the blood. Thus, the most ideal salt must not contain any harmful ingredients such as cadmium, mercury, lead, and arsenic. However, it is legal to include trace amounts of the hazardous ingredients in salt owing to a technical limitation, because salt is generally obtained from seawater. This paper reported an experimental result about a new method of manufacturing high-quality table salts without hazardous ingredients by using "$15^{\circ}C$ low-temperature vacuum drying technology," applied to the sequential extraction phenomenon of seawater with increasing the concentration. The world's best table salt can be produced if the present results are applied and extended to the traditional solar salt industry.

• Journal of the Korean Society of Physical Medicine
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• v.12 no.2
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• pp.113-120
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• 2017

PURPOSE: The purpose of this study was to investigate the effect of a physical therapy-based tailored exercise program on pain, accident incidence rates, the number of work days lost, and economical loss cost for workers in an automobile parts manufacturing company. METHODS: A total of 530 workers with musculoskeletal symptoms were given a physical therapy-based tailored exercise program twice a week, for one hour a day. This exercise program consisted of movement pattern correction, muscle stretching and strengthening, and postural correction exercises, according to principles of movement impairment syndromes and medical training therapy. From 2011 to 2016, the lost days of work, accident incidence rates, and loss cost were examined. The pain measured by VAS (visual analogue scale) and the number of workers participating in the exercise program from 2014 to 2016 were also measured. The single subjects A-B design was applied and analyzed. RESULTS: After applying the exercise program, pain decreased and the number of workers participating in the program increased. Accident incidence rates, number of work days lost, and economical loss cost decreased. There was a significant correlation between the number of workers who received exercise therapy by year and accident incidence rates, lost days of work, and economical loss cost (p<.05). CONCLUSION: It is necessary to expand the physical therapy-based tailored exercise program to prevent musculoskeletal disorders because it has a positive effect on both workers and employers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.203-208
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• 2021

At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.

• Journal of Korean Neurosurgical Society
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• v.62 no.2
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• pp.153-165
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• 2019

Objective : Spinal cord injury (SCI) is a very serious health problem, usually caused by a trauma and accompanied by elevated levels of inflammation indicators. Stem cell-based therapy is promising some valuable strategies for its functional recovery. Nestin-positive progenitor and/or stem cells (SC) isolated from pancreatic islets (PI) show mesenchymal stem cell (MSC) characteristics. For this reason, we aimed to analyze the effects of rat pancreatic islet derived stem cell (rPI-SC) delivery on functional recovery, as well as the levels of inflammation factors following SCI. Methods : rPI-SCs were isolated, cultured and their MSC characteristics were determined through flow cytometry and immunofluorescence analysis. The experimental rat population was divided into three groups : 1) laminectomy & trauma, 2) laminectomy & trauma & phosphate-buffered saline (PBS), and 3) laminectomy+trauma+SCs. Green fluorescent protein (GFP) labelled rPI-SCs were transplanted into the injured rat spinal cord. Their motilities were evaluated with Basso, Beattie and Bresnahan (BBB) Score. After 4-weeks, spinal cord sections were analyzed for GFP labeled SCs and stained for vimentin, $S100{\beta}$, brain derived neurotrophic factor (BDNF), 2',3'-cyclic-nucleotide 3'-phosphodiesterase (CNPase), vascular endothelial growth factor (VEGF) and proinflammatory (interleukin [IL]-6, transforming growth factor $[TGF]-{\beta}$, macrophage inflammatory protein [MIP]-2, myeloperoxidase [MPO]) and anti-inflammatory (IL-1 receptor antagonis) factors. Results : rPI-SCs were revealed to display MSC characteristics and express neural and glial cell markers including BDNF, glial fibrillary acidic protein (GFAP), fibronectin, microtubule associated protein-2a,b (MAP2a,b), ${\beta}3$-tubulin and nestin as well as anti-inflammatory prostaglandin E2 receptor, EP3. The BBB scores showed significant motor recovery in group 3. GFP-labelled cells were localized on the injury site. In addition, decreased proinflammatory factor levels and increased intensity of anti-inflammatory factors were determined. Conclusion : Transplantation of PI-SCs might be an effective strategy to improve functional recovery following spinal cord trauma.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.57-68
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• 2021

Successfully adapting to digital and customer-oriented transformation, the concept of lean manufacturing professes the philosophy of creating greater benefit while minimizing losses. These losses are operations that do not add value in the production process to ensure the efficiency, flexibility, and profitability of projects. In the context of broad automation and digitalization of all sectors of the economy, mechanisms for combining automation technologies and lean production are becoming available. Moreover, when it comes to the efficient use of financial, human, or material resources, it is clear that the use of Industry 4.0 technologies can be an effective tool for achieving the goals of lean production, as many of them pursue the same goal. In this context, this article aims to study the effectiveness of the implementation of project management concepts at the global level and identify the main factors influencing its effectiveness to ensure the achievement of lean production through LEAN technologies and Industry 4.0 technologies. To achieve this goal, several statistical indicators were selected and several statistical methods of analysis were used: pairwise correlation, regression analysis, methods of comparison, synthesis, and generalization. Statistical analysis was conducted according to a survey conducted by the Project Management Institute (PMI) in 2020. An economic-mathematical model of dependence of project effectiveness in different regions of the world on the level of implementation of project management approaches is built, which shows that the increase in project effectiveness by 85% is due to financial losses, technical training, and consumer orientation. These results allow project managers to develop appropriate strategies to improve project management approaches at all levels. It is established that LEAN technologies and technologies of Industry 4.0 have several tools that have a positive effect on minimizing losses following the concept of lean production. Besides, given that the technology of Industry 4.0 is focused on the automation of Lean Production technology, a mechanism for the introduction of lean production using these technologies and methods.