• Journal of Information Technology Services
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• v.20 no.1
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• pp.81-92
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• 2021

As the degree of economic development of society increases, the maintenance issues on the existing social overhead capital becomes essential. Accordingly, the adaptation of the concept of Level of service in highway maintenance is indispensable. It is also crucial to manage and perform the service level such as road assets to provide universal services to users. In this regards, the purpose of this study is to improve the maintenance service rating model and to focus on the assessment items and weights among the improvements. Particularly, in determining weights, an Analytic Hierarchy Process (AHP) is performed based on the survey response results. After then, this study conducts unsupervised neural network models such as Self-Organizing Map (SOM) and Davies-Bouldin (DB) Index to divide proper sub-groups and determine priorities. This paper identifies similar cases by grouping the results of the responses based on the similarity of the survey responses. This can effectively support decision making in general situations where many evaluation factors need to be considered at once, resulting in reasonable policy decisions. It is the process of using advanced technology to find optimized management methods for maintenance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.61-67
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• 2022

In this paper, we propose a model that can convert some of the simulation program resources to a mobile environment. Recently, smart factories that use PLCs as controllers in the manufacturing industry are rapidly becoming widespread. However, in the situation where it is difficult to operate due to the shortage of PLC operation personnel, the actual situation is that a platform for PLC operation education is necessary. Currently most PLC-related educational platforms are based on 2D, which makes accurate learning difficult and difficult. When a simulation program is applied to distance learning in a general PC environment, many elements are displayed on the monitor, which makes screen switching inconvenient. Experiments with the proposed model confirmed that there was no frame deterioration under general circumstances. The average response time by the request frame was 102 ms, and it was judged that the learner was not at the level of experiencing the system delay.

• Journal of the Korean Society of Safety
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• v.37 no.5
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• pp.22-32
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• 2022

The domestic smart factory is being built and spread rapidly, mainly by mid-sized companies and large enterprises according to the government's active introduction and support policy. But these factories only promote production system and efficiency, so harmfulness and risk factors are not considered. Therefore, to derive harmful risk factors in terms of industrial safety for 12,983 government-supported smart factory workplaces from 2014 to 2019, industrial accident status analysis compared workplaces with automation facilities and government-supported workplaces with automation facilities. Also, to reduce risks associated with domestic smart factory processes, twenty government-supported workplaces with automation facilities underwent analysis, evaluating risks through a status survey using the process evaluation table. In addition, the status survey considered region, size, industry, construction level, and accident rate; the difference in risk according to the structure of the process was confirmed. Based on the smart factory process evaluation results, statistical analysis confirmed that serial, parallel, and hybrid structures pose different risk levels and that the risks of mixed structures are greater. Finally, safety control system application was presented for risk assessment and reduction in the smart factory process, reflecting the results of disaster analysis and actual condition investigation.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.149-156
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• 2022

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).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.133-135
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• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.259-261
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• 2021

In this paper, VR smart factory XR content tailored to process execution scenarios was produced to reflect the characteristics of XR content, which is highly dependent on HDM, unlike general-purpose content software for UX/UI design and usability evaluation of digital twin-based XR content in manufacturing. HMD equipment called Qculus Quest2 was used to perform the process execution task scenario for XR content, and content production was made through Unity Engine and SteamVR Plugin.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.664-673
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• 2018

The industrial control system (ICS) has operated as a closed network in the past, but it has recently been linked to information and communications services and has been causing damage due to cyber attacks. As a countermeasure, the Information Communication Infrastructure Protection Act was enacted, but it cannot be applied to various real control environments because there is only a one-way policy-from a control network to a business network. In addition, IEC62443 defines an industrial control system reference model as an international standard, and suggests an area security model using a firewall. However, there is a limit to linking an industrial control network, operating as a closed network, to an external network only through a firewall. In this paper, we analyze the security model and research trends of the industrial control system at home and abroad, and propose an industrial control system security model that can be applied to the actual interworking environments of various domestic industrial control networks. Also, we analyze the security of firewalls, industrial firewalls, network connection equipment, and one-way transmission systems. Through a domestic case and policy comparison, it is confirmed that security is improved. In the era of the fourth industrial revolution, the proposed security model can be applied to security management measures for various industrial control fields, such as smart factories, smart cars, and smart plants.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.789-799
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• 2018

This article presents machine learning based approach on Big data to analyzing time series data for anomaly detection in such industrial complex system. Long Short-Term Memory (LSTM) network have been demonstrated to be improved version of RNN and have become a useful aid for many tasks. This LSTM based model learn the higher level temporal features as well as temporal pattern, then such predictor is used to prediction stage to estimate future data. The prediction error is the difference between predicted output made by predictor and actual in-coming values. An error-distribution estimation model is built using a Gaussian distribution to calculate the anomaly in the score of the observation. In this manner, we move from the concept of a single anomaly to the idea of the collective anomaly. This work can assist the monitoring and management of Smart Factory in minimizing failure and improving manufacturing quality.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.5
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• pp.31-37
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• 2017

In this Paper, we have Improved the Manufacturing Process of Liquid Aluminum Sulfate using the Design of Automated Measurement Systems. The Manufacturing Process of Liquid Aluminum Sulfate uses a Large Weight. The Quality of a Product Depends Highly on the Proportion of the Raw Material Input in the Production Process. Therefore, it is Very Important to Accurately Measure the Amount of Raw Material. For Automation Design, Load Cell Sensor which can Measure Large Weight Accurately and PLC Technology which is most used in Automation Process are Applied. The Content of Aluminum Oxide in the Aluminum Sulfate Produced before the Automation Design Varies from 8.023% to 8.250%. However, after Automation Design, the Amount of Change from 8.09% to 8.19% was Greatly Reduced. As a Result, we could Reduce the Quality Defect rate Due to Weighing Errors and Reduce Safety Accidents by Applying Automation System.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.31-36
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• 2020

Virtual simulation education, which is one of the methods of executing engineering education, is spreading. In general online education, only theoretical learning-centered lessons and practical training of simple small projects are conducted remotely, and it is necessary to disseminate various educational contents. Due to the spread of smart factories these days, most producers use automatic control to produce, inspect and package their products. The operation of automation equipment is controlled by using electricity, and electricity-related learning is operated in various departments. Due to the characteristics of electricity, it is difficult to learn online due to safety issues and high cost of practical equipment. In this paper, we provide a simulation-based electrical control panel distance learning model to improve the sense of accomplishment of education related to electrical training. Through the experiment of the proposed model, it was confirmed that the learning was more satisfied with the virtual simulation education than the online education using the existing equipment. It is expected that it can be used as a basic course for automation equipment education in the future.