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 Cooperationbased 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.

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).

The smart factory is an important system that can reduce defects, maximize productivity, and respond to customer needs, from the labor-intensive era of traditional small and medium-sized manufacturing companies through the automation era to CPS using ICT. However, small and medium-sized manufacturers often fall short of the basic stage due to economic and environmental constraints, and there are many companies that do not even recognize the concept of a smart factory. In this situation, to expand the smart factory of small and medium-sized enterprises, the project to support the establishment of a smart factory for the win-win between large and small enterprises. The win-win smart factory construction support project provides a customized differentiation program support project according to the size and level of the company for all domestic manufacturing SMEs regardless of whether or not they are dealing with Samsung. In this study, we analyze the construction status and introduction performance of companies participating in the win-win smart factory support project to find out whether they have been helpful in management and to find efficient ways to improve support policies, and to suggest the direction of continuous support projects to improve the manufacturing competitiveness of SMEs in the future.

Developed countries that have experienced decline in productivity due to the economic crisis in the past have come to recognize the smart factory as an important means to strengthen the competitiveness of the manufacturing industry due to the increase in labor costs, the avoidance of the manufacturing industry, and the resolution of the shortage of skilled manpower. The necessity of nurturing manpower for self-maintenance was felt through identifying factors for successful smart factory introduction by companies and providing smart factory education. Therefore, the effects of educational satisfaction and operational competency on self-efficacy as a parameter and self-efficacy as a parameter were analyzed using research models and hypotheses to determine whether there was an effect between job satisfaction as a dependent variable. As a result of the analysis, it was found that the mediating effect of self-efficacy and self-efficacy on job satisfaction was found to have significant effects on operational competency and self-efficacy as parameters, as well as educational satisfaction and operational competency. The implication of this study is that continuous education and innovation activities are important in order to increase the business performance of companies, and through this, the manufacturing competitiveness of SMEs can be improved.

In SMEs, technological innovation is recognized as an important tool in terms of sustainable growth. This study analyzed the determinants of technological innovation by using the information of the corporate panel DB composed of local SMEs. The internal factors were added with technological innovation capacity and production capacity and the industrial cluster environment was first applied to external factors. Also, whether the industrial cluster environment influences technological innovation through R&D capabilities, the mediating effect was tested with the Sobel Test. Among the internal and external factors, the most important determinant was marketing ability, and a policy was proposed to develop measures to increase R&D capability with mediating effect. Among the technological innovation variables, which are dependent variables, the most determinant factor was the proportion of new product sales. For this, it is considered that additional research such as longitudinal research with the concept of repetition and parallax using the corporate panel DB is necessary.

This study relates to acquiring biological signal without attaching directly to the user using UWB(Ultra Wide Band) radar. The collected information is the respiratory rate, heart rate, and the degree of movement during sleep, and this information is used to measure the sleep state. A breathing measurement algorithm and a sleep state detection algorithm were developed to graph the measured data. Information about the sleep state will be used as a personalized diagnosis by connecting with the medical institution and contribute to the prevention of sleep related diseases. In addition, biological signal will be linked to various sensors in the era of the 4th industrial revolution, leading to smart healthcare, which will make human life more enriching.

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises’ sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

This study measured the particulate matter (PM) in a subway tunnel using a dust spectrometer and estimated the PM10 and PM2.5 using a Kriging method. For the hourly measurement, a probe was attached inside the cabin and put through the window to collect data from the outside. The Kriging method is a spatial analysis method, and time and spatial data were applied in the subway tunnel along with a PM concentration map. The result of the measurement shows that PM10 is 31.9~271.3 μg/m3 and PM2.5 is 30.9~209.5 μg/m3. In addition, The pollutant map shows that some sections have a higher concentration than other sections because of the depth and curvature of tunnel and traffic volume on the section and local construction. Also, the results show that differences concentration at different times of sampling could be distinguished. The highest concentration was found at 3 pm while the lowest was at 12 pm. We expect to use the pollutant map in planning air quality improvements for the tunnel.

In this study, we numerically analyzed flow and particle transport near the electrostatic precipitator in the tunnel according to train runs. When there was no train running, flow field was formed by a precipitator. Flow emitted from precipitator blocks the path along the tunnel, and therefore most contaminated air passes through the precipitator and can be cleaned. On the other hand, flow pattern during the train run was affected by train induced wind. A strong straight flow was generated at the front of train, and back flow was formed in the opposite line. When a train runs upward only (train start from suction section to blow section), the subway train transports contaminated particles along the tunnel. For downward train runs only case, the cleaned air reentered the contaminated section with train wind. Both train runs case showed combined flow and particle concentration pattern of both single train runs.

레이저 주사 공초점 현미경은 비접촉, 비파괴적인 방법으로 수백 ㎚ 크기의 물질의 이미지를 관찰할 수 있다. 본 연구에서는 공초점 현미경을 이용하여 V₂O5 박막의 표면에 성장된 수백 ㎚ 크기의 나노로드를 관찰하였으며, 공초점 현미경의 파장 의존성을 확인하기 위해 동일한 위치에 대해 짧은 파장대인 405 ㎚와 긴 파장대의 633 ㎚의 레이저 광원을 사용하여 이미지를 구현하였다. 실험결과, 긴 파장인 633㎚의 광원을 사용한 이미지에서는 번짐 현상이 심해져 명암대비가 작아지고 나노로드의 경계를 명확하게 분해하지 못하였지만, 짧은 파장인 405 ㎚의 광원을 사용하면 명암대비가 커지고 나노로드의 이미지를 명확하게 분해할 수 있었다. 따라서 짧은 파장의 광원을 사용한 공초점 현미경은 주사전자현미경(SEM)을 대신한 새로운 나노구조의 측정방법으로 이용될 수 있을 것으로 기대된다.

Paying close attention to those new to an organization, whether fresh or experienced, whose primary interest is in (re)socialization, the current study intends to (1) further the concept of mentoring from a bilateral relationship to a community and culture fostered by developmental networks, (2) propose an integrated conceptual framework for organizational socialization, and (3) suggest implications for practice and future research. This study reviews, analyzes, and integrates research assets and subsequently re-conceptualizes the aggregate information as valid propositions and a conceptual framework. The findings include (1) 11 propositions regarding the relationships among network characteristics (embeddedness, diversity), developmental functions (career support, psychosocial support, and role modeling), and socialization outcomes (learning and attitudinal outcomes); and (2) an integrated conceptual framework that depicts a comprehensive mechanism through which developmental networks conduce to organizational socialization of newcomers. Implications are that developmental networking must be an individual’s fundamental competency and an essential part of organizational onboarding processes, and imperative for both members’ career development and innovative organizational culture. By integrating research assets on the developmental phenomenon into conceptualizations, this study furthers the concept of mentoring to organizational culture and stimulates a substantive discourse for theory-building towards organizational socialization from the developmental network perspective.