• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.204-206
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• 2022

Digital twin, which is evaluated as the core of smart factory advancement, is a technology that implements a digital replica in the virtual world with the same properties and functions of assets in the real world. Since the smart factory to which digital twin is applied can support services such as real-time production process monitoring, production process simulation, and predictive maintenance of facilities, it is expected to contribute to reducing production costs and improving productivity. AAS (Asset Administration Shell) is an essential technology for implementing digital twin and supports a method to digitally represent physical assets in real world. In this paper, we design AAS for manufacturing data gathering to be used in real-time CNC (Computer Numerical Control) monitoring system in operation by considering manufacturing facility in smart factory as assets.

• IE interfaces
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• v.13 no.3
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• pp.503-511
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• 2000

The main theme of this research is a case of e-Business implementation in part manufacturing industry, especially in a PCB manufacturing company. The characteristics of part manufacturing industry are as follows. First, an ERP system runs as a legacy system that is ready to be combined with e-Business system. Secondly, the number of customers is very small. The customers are not many individuals but only a few big electronic enterprises that are strategically affiliated with the part manufacturing company. This means that the e-Business of the part manufacturing industry needs to focus on sharing pertinent information throughout the transactions with the customers, not on data-warehousing or data-mining customers' potential needs or requests. In this paper, we extracted e-Business opportunity domains from a PCB manufacturing company, a typical part manufacturing industry. We are intended to enhance information sharing between customers and the company, and provide functions of transactions necessary in the whole value chain from order to shipment. Implementing the e-Business system on the Web can increase the visibility of customers, and further, the company can be transformed into an extended enterprise where the relationship with the customers becomes very close and interleaved. Also, the Cyber Office functionality of the e-Business system can support the salespersons effectively, so that they can spend more time on customer satisfaction. Such efforts, in the future, can be a basis for active adaptation to the industry transformations such as forming e-community and participating in the marketplace.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.281-286
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• 2013

As the product lifecycle is getting shorter and various models should be released to respond to the needs of customers and markets, automation-based flexible production line has been recognized as the core competitiveness. According to these trends, system vendors supply cell-level systems such as FMC(Flexible Manufacturing Cell) that is integration of core functions of FMS(Flexible Manufacturing System) and RMC(Reconfigurable Manufacturing Cell) that can easily extend components of FMC. In the cell-based environment, flexible management for shop floor composed of existing job shop, FMCs and RMCs from various system vendors has emerged as an important issue. However, there could be some problems on integrated operation between heterogeneous cells to use vendor-specific cell controllers and on seamless information flow with high level systems such as ERP(Enterprise Resource Planning). In this context, this paper proposes process management systems supporting integrated shop operation of heterogeneous multi-cell based flexible manufacturing environment: First of all, (1) Integrated Shop Operation System to apply the process management system is introduced, and (2) Multi-Layer BOP(Bill-Of-Process) model, a backbone of the process management system, is derived with its data structure. Finally, application of the proposed model is illustrated through system implementation results.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.1
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• pp.50-59
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• 2023

Objectives: This study was designed to examine the effect of risk assessment on employee safety behavior in manufacturing workplaces. In addition, this study attempted to explore factors related to the occupational safety and health system in the workplace affect the risk assessment of manufacturing sites. Methods: This research is a cross-sectional study using the Korea Occupational Safety and Health Agency's 2018 Occupational Safety and Health data. The sample for study is 1,967 manufacturing workplaces. Data were analyzed using descriptive statistics, t-test, ANOVA, chi-square test, and hierarchical multiple regression analysis using SPSS (ver.25.0). Results: As a result of the multiple hierarchical regression analysis, it was found that risk assessment had an effect on employee safety behavior (t=4.435, p=<.001). Furthermore, the size of the workplace affected employee safety behavior (t=2.494, p=<.001). In addition, the presence of safety and health management organizations affected employee safety behavior (t=4.301, p=<.001). The factors of the safety and health organization (𝑥²=35.245, p=<.001), the occupational safety and health committee (𝑥²=149.440, p=<.001), and the supervisor (𝑥²=16.472, p=<.001) were identified as factors that increased the possibility of risk assessment in the manufacturing workplaces. Conclusions: In this study, it was found that risk assessment is a factor that increases the level of workers' safety behavior in manufacturing workplaces. Therefore, it is necessary to provide institutional support for activating risk assessment at manufacturing workplaces.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.26 no.4
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• pp.454-465
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• 2016

Objectives: The purpose of this study was to evaluate trends in asbestos exposure among asbestos-handling industries from 2000 to 2005. Methods: The data included the number of industries and workers exposed, concentrations of asbestos and the amount exceeded, and the type and size of industry by year. These data were collected by 46 regional employment and labor offices in Korea using work environment monitoring reports. A total of 1,481 samples from 284 industries were extracted from the reports and were analyzed with no data modification. Results: The means of asbestos concentration decreased from $0.84f/cm^3$ to $0.03f/cm^3$ during the period 2000-2005. Among the total of 1,481 samples, 11 samples(0.7%) exceeded the KOEL, and 178 samples(12.0%) were ACGIH TLV. The insulating paper product manufacturing industry was found to have the highest level of asbestos, followed by the fireproofing manufacturing industry, brake lining products manufacturing industry, commutator products manufacturing industries, and construction materials manufacturing industry. The number of asbestos handling industries decreased from 48 industries with 1,155 employees to 37 industries during the period of 2000 to 2005, but the number of asbestos workers expanded to the point that 1,182 employees could be found in 2005. Conclusion: Based on these results, the strengthening of the KOEL and new regulations turned out to help reduce asbestos exposure levels. This study recommends that retrospective exposure to asbestos based on various industry types should be assessed.

• 전자공학회논문지 IE
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• v.46 no.2
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• pp.46-52
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• 2009

The manufacturing system was used to communicate between controller and GUI system by RS232C. The controller is deal with processing the equipments such as cylinders, motors, sensors, and so on. The Gill system received the signal from actuator controller by direct communication ways, RS232C, and presented the data to user to analyze the all of status for manufacturing system. In this point, it is important that communication use the RS232C. The way is helpful to be able to reduce cost, have simple structure, and easily maintain the stable communication status. Otherwise, the way has some problem to loss signal or data under the high speed communication. So it needs to complement the communication process to without loss data. In this research, we made the communication algorithm and implement the process to reduce losing data when it send or receive the signal using RS232C between controller and manufacturing system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3330-3344
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• 2023

This paper proposes an antenna performance prediction model in the autonomous driving radar manufacturing process. Our research work is based upon a challenge dataset, Driving Radar Manufacturing Process Dataset, and a typical AutoML machine learning workflow engine, Pycaret open-source Python library. Note that the dataset contains the total 70 data-items, out of which 54 used as input features and 16 used as output features, and the dataset is properly built into resolving the multi-output regression problem. During the data regression analysis and preprocessing phase, we identified several input features having similar correlations and so detached some of those input features, which may become a serious cause of the multicollinearity problem that affect the overall model performance. In the training phase, we train each of output-feature regression models by using the AutoML approach. Next, we selected the top 5 models showing the higher performances in the AutoML result reports and applied the ensemble method so as for the selected models' performances to be improved. In performing the experimental performance evaluation of the regression prediction model, we particularly used two metrics, MAE and RMSE, and the results of which were 0.6928 and 1.2065, respectively. Additionally, we carried out a series of experiments to verify the proposed model's performance by comparing with other existing models' performances. In conclusion, we enhance accuracy for safer autonomous vehicles, reduces manufacturing costs through AutoML-Pycaret and machine learning ensembled model, and prevents the production of faulty radar systems, conserving resources. Ultimately, the proposed model holds significant promise not only for antenna performance but also for improving manufacturing quality and advancing radar systems in autonomous vehicles.

• Smart Media Journal
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• v.9 no.3
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• pp.31-40
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• 2020

Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.11-20
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• 2020

As the manufacturing environment becomes more complex, traditional simulation models alone are having a lot of difficulties in reflecting real-time manufacturing situations. Although the Digital Twin concept is actively discussed as an alternative to overcome theses issues, many studies are being carried out only in the product design phase. This research presents a Digital Twin-based manufacturing environment framework for applying the Digital Twin concept to the manufacturing process. Twin model that is operated in virtual space, physical system and databases describing the actual manufacturing environment, are proposed as detailed components that make up the framework. To check the applicability of proposed framework, a simple Digital Twin-based manufacturing system was simulated in a conveyor system using Arena software and Excel VBA. Experiment results have shown that the twin model is transmitted real time data from the physical system via DB and were operating in the same time unit. The Excel VBA fitted parameters defined by cycle time based on historical data that real-time and training data are being accumulated together. This study proposes operating method of digital twin model through the simple experiment examples. The results lead to the applicability of Digital twin model.

• The Korean Journal of Health Service Management
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• v.11 no.1
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• pp.107-115
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• 2017

Objectives : The purpose of this study was to examine the relationship between the health behavior and prevalence of chronic diseases among manufacturing workers. It would provide fundamental data in the development of health promotion programs for manufacturing workers. Methods : Data on 3,171 employees who underwent health check-ups by the National Health Insurance Service in L company, G City from March to December 2014 were analyzed. The statistical analysis of frequency, chi-square test, and multiple logistic regressions were performed using SPSS 18 program. Results : The results of this study show that obesity and over-weight are the health behaviors that influence the prevalence of chronic diseases in manufacturing employees. Conclusions : The implementation of public health projects to improve the voluntary participation of the employees can enhance their health, improve the productivity, and influence their quality of life positively by changing the health behaviors.