• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.535-546
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• 2024

This research aims to develop a model to objectively and quantitatively measure the skill level of aircraft body assembly workers. Because aircraft body assembly is predominantly a manual process, skills management is a key factor of manufacturing competitiveness. Currently, skills management relies on the subjective judgment of supervisors, which lacks objectivity and reliability. As a remedy, this study proposed a systematic skill management model based on objective and quantitative evaluation criteria. By considering prior research, we developed an evaluation model that takes into account both expertise and versatility of a worker. The model selected five major tasks required for aircraft body assembly and established evaluation criteria considering the difficulty and maturity of each task. We then conducted a pilot evaluation with over 200 workers in four SMEs to validate the practicality and effectiveness of the model. Consequently, we identified and addressed the limitations of the existing evaluation method, subdivided the skill levels based on the performance capabilities of each task, and proposed a career growth path. The developed evaluation model offers critical data for executives and managers to determine work assignments, education, training, performance incentives, and wages. It is expected to enhance the attraction of new talent and systematize skills management in aviation manufacturing in the future.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.45-53
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• 2024

A Smart factories are systems that enable quick response to customer demands, reduce defect rates, and maximize productivity. They have evolved from manual labor-intensive processes to automation and now to cyber-physical systems with the help of information and communication technology. However, many small and medium-sized enterprises (SMEs) are still unable to implement even the initial stages of smart factories due to various environmental and economic constraints. Additionally, there is a lack of awareness and understanding of the concept of smart factories. To address this issue, the Cooperation-based Smart Factory Construction Support Project was launched. This project is a differentiated support project that provides customized programs based on the size and level of the company. Research has been conducted to analyze the impact of this project on participating and non-participating companies. The study aims to determine the effectiveness of the support policy and suggest efficient measures for improvement. Furthermore, the research aims to provide direction for future support projects to enhance the manufacturing competitiveness of SMEs. Ultimately, the goal is to improve the overall manufacturing industry and drive innovation.

• Journal of the Korean Society of Safety
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• v.38 no.3
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• pp.77-84
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• 2023

Welding and cutting, which are representative tasks in handling firearms at industrial sites, are the basis for production and maintenance processes across all industries. They are also essential in the root industry. Specifically, they are widely used in the manufacturing industry, including equipment industries such as shipbuilding, automobiles, and chemicals, and subsequent maintenance work and general facility repair. However, such hot work carries a high fire risk owing to sparks scattering and inadequate management, resulting in a high occurrence of accidents. In response, the government and relevant organizations have recently revised the Occupational Safety and Health Act to prevent accidents during hot work. These revisions impose more stringent regulations than before, which are expected to help prevent actual fire accidents. However, whether the fire observer system, which is the core element of the revision, would be practically applied and maintained is unclear. Therefore, this study compared the fire observer system in the revised Occupational Safety and Health Act with those in the laws and systems of developed countries, conducted interviews with safety and health experts to assess the suitability of the new system for fire observer operations, and improvement plans were derived accordingly. Therefore, the laws and systems of developed countries grant more authority to fire observers compared with those of Korea. Moreover, professional training in handling emergency is required. Interviews with safety and health experts revealed that regardless of company size, the same operating standards were applied, and standards for deploying fire observers in various locations were unclear. Furthermore, there was a lack of professional education and training, and the role and authority of fire observers were limited. These findings revealed a problem in this sector. The results of this study are expected to serve as basic data for establishing a practical system for placing fire observers and supplementing laws, guidelines, and systems for preventing fire accidents.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.3
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• pp.300-307
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• 2017

Electroencephalography (EEG) is distinct from other medical imaging tests in that it is a functional test that helps to diagnosis disorders related to the brain, such as epilepsy. The most important abilities for a medical technologist when performing an EEG are knowing the exact location of the electrode and recording the EEG wave clearly, except for artifacts. Although theoretical education and practical training are both included in the curriculum for improving these abilities, sufficient practical training has been lacking due to problems like expensive equipment and insufficient practical training time. We try to solve these issues by manufacturing the training 10-20 electrode system and by estimating the efficiency and satisfaction of the training 10-20 electrode system through a questionnaire. The time required for practical training using this system was $43.58{\pm}9.647min$, which proved to be efficient. The satisfaction score of participants who experienced curriculum practical training was improved from $7.21{\pm}2.285$ to $9.46{\pm}1.166$. Based on these findings, it is considered that practical training via the use of the training 10-20 electrode system will solve the problems, such as lack of equipment and insufficient practical training time. Nonetheless, to further improve the training 10-20 electrode system, it must overcome the limitations of developing a device capable of checking the actual brain waves and validating the exact location of electrode attachment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.610-619
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• 2016

Digital manufacturing (DM) technology helps engineers design products promptly and reliably at low production cost by simulating a manufacturing process and the material behavior of a product in use, based on three-dimensional digital modeling. The computing infrastructure for digital manufacturing, however, is usually expensive and, at present, the number of professional design engineers who can take advantage of this technology to a product design accurately is insufficient, particularly in small and medium manufacturing companies. Considering this, the Korea Institute of Science and Technology Information (KISTI) and H University is operating a DM track in the form of Industry-University-Research Institute collaboration to train high-performance-computing-based DM professionals. In this paper, a series of courses to train students to work directly into DM practice in industry after graduation is reported. The operating cases of the DM track for two years since 2013 are presented by focusing on the progress in establishment, lecture and practice contents, evaluation of students, and course quality improvement. Overall, the track management, curriculum management, learning achievement of students have been successful. By expediting more active participation of the students in the track and providing more internship and job offers in the participating companies in addition to collaborative capstone design projects, the track can be expanded by fostering a nationwide training network.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.215-222
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• 2001

Neural network based models of semiconductor manufacturing processes have been shown to offer advantages in both accuracy and generalization over traditional methods. However, model development is often complicated by the fact that back-propagation neural networks contain several adjustable parameters whose optimal values unknown during training. These include learning rate, momentum, training tolerance, and the number of hidden layer neurOnS. This paper presents an investigation of the use of genetic algorithms (GAs) to determine the optimal neural network parameters for the modeling of plasma-enhanced chemical vapor deposition (PECVD) of silicon dioxide films. To find an optimal parameter set for the neural network PECVD models, a performance index was defined and used in the GA objective function. This index was designed to account for network prediction error as well as training error, with a higher emphasis on reducing prediction error. The results of the genetic search were compared with the results of a similar search using the simplex algorithm.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.97-104
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• 2023

Purpose: The web based KRAS risk assessment support system to facilitate risk assessment in small businesses and provides an assessment model for each type of business. In order to help understand risk assessment, private institutions have opened and operated training in charge of risk assessment. It will present the effectiveness of education in charge of risk assessment and measures to improve and revitalize it accordingly. Method: Using SPSS 22 for 670 workplaces that completed risk assessment personnel training within 5 years from 2017 to 2021, the disaster rate was analyzed through correlation analysis and t-test by dividing groups of less than 100 people into groups of 100 people. Result: Hypothesis 1-5 are adopted and reject 5-8. Conclusion: It is possible to consider the organization of a curriculum according to the size of a company for corporate education with more than 100 employees and to enhance the benefits of recognizing risk assessment.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.53-62
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• 2023

This paper has suggested the necessity of introducing training contents using XR(Extended reality) technology as a way to lower the high rate of nursing accidents among unskilled technical personnel in domestic shipbuilding industry, focusing on cable pulling using winch. The occurrence rate of nursing accidents in the domestic shipbuilding industry was almost double(197.4%) (2017~2020) when compared with other manufacturing industries. In particular, it is worth noting that more than 31.8% of nursing accidents in the shipbuilding industry occurred among workers whose job experience is no more than 6 months. Most of new workers are seen to have hard time due to several factors such as lack of work information, inexperience, and unfamiliarity with the working environments. This indicates that it is essential to incorporate more effective training method that could help new workers become familiar with technical skills as well as working environments in a short period of time. Currently, education/training at the domestic shipyard is biased toward technical skills such as welding, painting, machine installation, and electrical installation. Contrary, even more important training required to get new workers used to the working environment has remained at a superficial level such as explaining ship building processes using 2D drawings. This may be the reason why it is inevitable to repeat similar training at OJT (On-the-Job Training) even at the leading domestic companies. Domestic shipbuilding industries have been attracting a lot of new workers thanks to recent economic recovery, which is very likely to increase the occurrence of disasters. In this paper, the introduction of training using XR technology was proposed, and as a specific example, the process of pulling cables using winches on ships was implemented as XR-based training content by using Unity. Using the developed content, it demonstrated that new workers can experience the actual work process in advance through simulation in a virtual space, thereby becoming more effective training content that can help new workers become familiar with the work environment.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.11
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• pp.108-115
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• 2009

In metal forming technologies, the stamping process is one of the significant manufacturing processes to produce sheet metal components. It is important to design stamping process which can produce sound products without defect such as fracture and wrinkle. The objective of this study is to propose the feasible formability diagram which denotes the safe region without fracture and wrinkle for effective design of stamping process. To determine the feasible formability diagram, FE-analyses were firstly performed for the combinations of process parameters and then the characteristic values for fracture and wrinkle were estimated from the results of FE-analyses based on forming limit diagram. The characteristic values were extended through training of the artificial neural network. The feasible formability diagram was finally determined for various combinations of process parameters. The stamping process of turret suspension to support suspension module was taken as an example to verify the effectiveness of feasible formability diagram. The results of FE-analyses for process conditions within fracture and wrinkle as well as safe regions were in good agreement with experimental ones.