• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.21-28
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• 2023

In manufacturing companies that focus on small-scale production of multiple product varieties, defective products are manually selected by workers rather than relying on automated inspection. Consequently, there is a higher risk of incorrect sorting due to variations in selection criteria based on the workers' experience and expertise, without consistent standards. Moreover, for non-standardized flexible objects with varying sizes and shapes, there can be even greater deviations in the selection criteria. To address these issues, this paper designs a quality inspection system using artificial intelligence-based unsupervised learning methods and conducts research by experimenting with accuracy using a dataset obtained from real manufacturing environments.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.303-310
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• 2023

A single vision system limits the ability to accurately understand the spatial constraints and interactions between robots and dynamic workers caused by gantry robots and collaborative robots during production manufacturing. In this paper, we propose a 3D pose registration method for dynamic workers based on a multi-domain vision system for safety monitoring in manufacturing environments. This method uses OpenPose, a deep learning-based posture estimation model, to estimate the worker's dynamic two-dimensional posture in real-time and reconstruct it into three-dimensional coordinates. The 3D coordinates of the reconstructed multi-domain vision system were aligned using the ICP algorithm and then registered to a single 3D coordinate system. The proposed method showed effective performance in a manufacturing process environment with an average registration error of 0.0664 m and an average frame rate of 14.597 per second.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.127-136
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• 2024

Because the hazardous working environments and high labor intensity of the root industry can potentially impact the health of workers, current regulations have focused on measuring and controlling environmental factors, on a semi-annual basis. However, there is a lack of quantitative criteria addressing workers' health conditions other than the physical work environment. This gap makes it challenging to prevent occupational diseases resulting from continuous exposure to harmful substances below regulatory thresholds. Therefore, this paper proposes a machine learning-based method for determining the peak level of risk in root industry work environments and enables real-time safety assessment in workplaces utilizing this approach.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.368-379
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• 2013

Efficiency in work training is a perennial issue due to high-diversity low-volume production, particularly for manufacturers producing office machines which are manually assembled by workers. To reduce the training cost, parts used in training are usually reused; a trainer disassembles a product assembled by a worker in training. This paper proposes a training method that employs disassembly usually performed by a trainer. This method assigns both assembly and disassembly to a worker in training, in contrast to the conventional method. The effectiveness of the proposed method is experimentally discussed in terms of learning assembly motions and work procedure at each learning stage, namely, "undergoing learning," "immediately after learning," and "seven days after learning." The effectiveness of the training method is confirmed. The method improves the stability of work procedure recollection immediately after training. Furthermore, at seven days after training, it improves retention of the assembly motions and work procedure, and also promotes and maintains memory related to product structure.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.279-298
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• 2019

Many empirical studies are conducted in regards to protean career or boundaryless career. The concept and the notion of protean career and boundaryless career has extended so far. Yet, the gap in the literature exists. Previous literature focused on the relationship among protean career, boundaryless career, and subjective career success, but examined little about the influence of protean career and boundaryless career on positive career attitude or future learning readiness. Therefore, this study explores the moderating effect of supporting policy of career development among protean career orientation, boundaryless career, positive career attitude, and future learning readiness. There was moderating effect of supporting policy of career development among the relationships of protean career orientation and future learning readiness; the relationships of boundaryless career and future learning readiness. The moderating effect of supporting policy of career development implies that the intention of career development in self-directed way and learning are related. In addition, The role of HRD/HRM department which takes initiatives in career development can affect the learning readiness for future among workers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.263-272
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• 2022

As a result of climate change, the heatwave and urban heat island phenomena have become more common, and the frequency of heatwaves is expected to increase by two to six times by the year 2050. In particular, the heat sensation index felt by workers at construction sites during a heatwave is very high, and the sensation index becomes even higher if the urban heat island phenomenon is considered. The construction site environment and the situations of construction workers vulnerable to heat are not improving, and it is now imperative to respond effectively to reduce such damage. In this study, satellite imagery, land surface temperatures (LST), and long short-term memory (LSTM) were applied to analyze areas above 33 ℃, with the most vulnerable areas with increased synergistic damage from heat waves and the urban heat island phenomena then predicted. It is expected that the prediction results will ensure the safety of construction workers and will serve as the basis for a construction site early-warning system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.89-106
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• 2022

Recently, in Korea, the number of unemployed people who have lost their jobs involuntarily due to closure of workplaces, layoffs, and poor management stood at 788,000 in October 21, an increase of 44,000 from last August (Statistics Office, 2021). The average retiring age of workers is 49.7, so regardless of their intention, they often end up retiring early unavoidably. Meanwhile, it has been found that eight out of ten workers have startup intention; therefore, now their startup is regarded to be essential, not selective. The purpose of this study is to investigate if workers' entrepreneurial orientation, continuous learning, satisfaction with remuneration, and employment prospect are correlated with entrepreneurial intention and examine if innovative behavior mediates the relations. To sum up the results, first, innovativeness and risk sensitivity in entrepreneurship are found to have positive effects on workers' entrepreneurial intention. Restless challenges and innovative thinking at work are crucial variables to enhance entrepreneurial intention. Second, satisfaction with remuneration influences entrepreneurial intention positive effects, and continuous learning and employment prospect, too, have positive effects on entrepreneurial intention. As employment instability is increasing at work due to the rapidly changing corporate environment, Considering whether the current organization will strive for survival or prepare to start a business for sustainable economic activity, it is judged that there is a willingness to start a business for better compensation even if the satisfaction of compensation is high. In addition, it was confirmed that the possibility of employability with the career desired by the organization as well as the securing of practical competency and expertise through continuous learning are important variables in increasing the will to start a business. Third, relations between entrepreneurial orientation, satisfaction with remuneration, continuous learning, employment prospect, and entrepreneurial intention are found to be mediated by innovative behavior; however, its mediative effect in relations between innovativeness, risk sensitivity, and entrepreneurial intention in entrepreneurship is dismissed. Innovative behavior at work are found to be major variables to elevate entrepreneurial intention in relations between continuous learning, employment prospect, and satisfaction with remuneration.

• Industry Promotion Research
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• v.5 no.1
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• pp.47-52
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• 2020

In this study, parallel work-learning training, which was started in 2013 as a pre-employment promotion policy, is an important factor that determines the success or failure of training. As a time when various institutional supplementation is needed to encourage company participation, this study is to identify the factors of participation of companies participating in work-learning parallel. To this end, a questionnaire survey was conducted of companies participating in parallel work-learning in Chungnam, and the results were analyzed using the structural equation model. As a result of the study, the reason for the company's participation in parallel work-learning was firstly, 84% of government subsidy received education and training expenses. Second, 66% of workers were able to pay less than regular workers, and thirdly, it was easy to hire new employees in the field. 26%, 17% of them were invited by acquaintances for no particular reason. Therefore, the study suggests that participation in the work-learning parallel training contributes to the management costs, management of employee turnover, and human resource development. In future research, it is necessary to subdivide tests and estimates by conducting studies on regions, occupations, gender, wages, and years of service in Korea.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.728-735
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• 2022

Roofers get exposed to increased risk of knee musculoskeletal disorders (MSDs) at different phases of a sloped shingle installation task. As different phases are associated with different risk levels, this study explored the application of machine learning for automated classification of seven phases in a shingle installation task using knee kinematics and roof slope information. An optical motion capture system was used to collect knee kinematics data from nine subjects who mimicked shingle installation on a slope-adjustable wooden platform. Four features were used in building a phase classification model. They were three knee joint rotation angles (i.e., flexion, abduction-adduction, and internal-external rotation) of the subjects, and the roof slope at which they operated. Three ensemble machine learning algorithms (i.e., random forests, decision trees, and k-nearest neighbors) were used for training and prediction. The simulations indicate that the k-nearest neighbor classifier provided the best performance, with an overall accuracy of 92.62%, demonstrating the considerable potential of machine learning methods in detecting shingle installation phases from workers knee joint rotation and roof slope information. This knowledge, with further investigation, may facilitate knee MSD risk identification among roofers and intervention development.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.273-283
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• 2023

Education has recently witnessed a rapid increase in the use of edutech worldwide. This study focuses on Korean workers and explores an edutech-based learning model for vocational education and training. Based on analyses of edutech cases and interviews with edutech experts, a draft edutech model was designed and the validity was evaluated based on two Delphi surveys with a panel of experts in the field. The study's findings suggest that edutech-based employee education and training should prioritize LXP orientation (last CVR=1, last Mean=4.70) , implement adaptive learning through learning analytics (last CVR=1, last Mean=4.90), enhance the human touch effect using edutech (last CVR=1, last Mean=4.90), and emphasize the importance of designing curricula that apply edutech in a step-by-step learning process while incorporating suitable instructional design for the key technologies involved in vocational training programs. In addition, it was revealed that there is a strong need to implement a method that makes each stage of the learning process more effective (before, during, and after). Edutech-based vocational training program should consider the interests of all stakeholders, including learners, instructors, vocational training institutions, and government agencies. Given the promotion of government-sponsored vocational training projects in Korea, the findings of this research are likely to have significant implications for the future of Korea's education and training policies.