• Journal of Korean Society for Quality Management
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• v.51 no.2
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• pp.283-296
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• 2023

Purpose: The purpose of this study is to actually implement and verify whether welding defects can be detected in real time by utilizing deep learning AI solutions in the welding process of electric vehicle hairpin winding motors. Methods: AI's function and technological elements using synthetic neural network were applied to existing electric vehicle hairpin winding motor laser welding process by making special hardware for detecting electric vehicle hairpin motor laser welding defect. Results: As a result of the test applied to the welding process of the electric vehicle hairpin winding motor, it was confirmed that defects in the welding part were detected in real time. The accuracy of detection of welds was achieved at 0.99 based on mAP@95, and the accuracy of detection of defective parts was 1.18 based on FB-Score 1.5, which fell short of the target, so it will be supplemented by introducing additional lighting and camera settings and enhancement techniques in the future. Conclusion: This study is significant in that it improves the welding quality of hairpin winding motors of electric vehicles by applying domestic artificial intelligence solutions to laser welding operations of hairpin winding motors of electric vehicles. Defects of a manufacturing line can be corrected immediately through automatic welding inspection after laser welding of an electric vehicle hairpin winding motor, thus reducing waste throughput caused by welding failure in the final stage, reducing input costs and increasing product production.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.199-206
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• 2022

A malfunction or breakdown of a manufacturing facility leads to product defects and the suspension of production lines, resulting in huge financial losses for manufacturers. Due to the spread of smart factory services, a large amount of data is being collected in factories, and AI-based research is being conducted to predict and diagnose manufacturing facility breakdowns or manufacturing site efficiency. However, because of the characteristics of manufacturing data, such as a severe class imbalance about abnormalities and ambiguous label information that distinguishes abnormalities, developing classification or anomaly detection models is highly difficult. In this paper, we present an deep learning algorithm for anomaly detection of a manufacturing facility using reconstruction loss of CNN-based model and ananlyze its performance. The algorithm detects anomalies by relying solely on normal data from the facility's manufacturing data in the exclusion of abnormal data.

• Convergence Security Journal
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• v.17 no.2
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• pp.153-158
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• 2017

The robot imitates humans and recognizes the external environment and judges the situation. The robot is a machine that operates autonomously. Robots are divided into manufacturing robots and service robots. Service robots are classified as professional service robots and personal service robots. Because of the intensified competition of productivity in manufacturing industries, rising safety issues, low birth rate and aging, the robots industry is emerging. Recently, the robot industry is a complex of advanced technology fields, and it is attracting attention as a new industry where innovation potential and growth potential are promising. IT, BT, and NT related elements are fused and implemented, and the ripple effect is very large. Due to changes in social structure and life patterns, social interest in life extension and health is increasing. There is much interest in the medical field. Now the artificial intelligence (AI) industry is growing rapidly. It is necessary to secure global competitiveness through strengthening cooperation between large and small companies. We must combine R&D investment capability and marketing capability, which are advantages of large corporations, and robotic technology. We need to establish a cooperative model and secure global competitiveness through M&A.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.2
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• pp.57-64
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• 2017

A new paradigm based on distributed manufacturing services is emerging. This paradigm shift can be realized by smart functions and smart technologies such as Cyber Physical System (CPS), Artificial Intelligence (AI), and Cloud Computing. Most architectures define stack levels from Level 0 (equipment) to Level 4 (business area) and specify the services to be provided between them. Because of their a rough technical specification, there is a limitation on how to actually utilize a technology to actually implement a smart factory service with this architecture. In this paper, we propose a smart factory architecture that can be utilized directly from the perspective of a smart service system by making the use of System Engineering Process and System Modeling Language (SysML).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.573-576
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• 2022

Currently, the world has known many innovative technologies created to bring users to interact using the internet. The latest buzzword attracting attention both from industry and academia is the metaverse. The metaverse is a virtual environment in which people used virtual reality and augmented reality devices to carry out numerous virtual activities. At first, metaverse applications were mostly virtual games, but now with advances in research, many other applications and technologies are integrating the metaverse among which manufacturing, real estate, healthcare, military, and many others. The proper operation of these applications requires some technologies like blockchain and artificial intelligence. In this paper, we investigate the role of blockchain and AI in the metaverse. This work aims to present the eventual use cases of these technologies in the metaverse regardless of their application domain.

• Journal of the Korean Society of Safety
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• v.12 no.4
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• pp.57-62
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• 1997

The combined structure of hybrid composite made through the bonding process of materials of different properties greatly defines its mechanical characteristics, as the results of the experiments on materials of different properties show much dissimilarity. When carbon/epoxy materials are applied to hybrid composite, the carbon materials helps to improve the mechanical properties of the hybrid composite, and the epoxy reduces its fracture strain and impact resistance. Carbon fiber which is now in general commercialization is classified as high modulus or high strength system, and its manufacturing methods are various. The study of the materials having combined structure is focused on the numerical analysis of the layers of bonding surface in materials with difference modulus. The hybrid composite made through the multilayered bonding of reinforced aluminium sheets with aramid fiber now faces the marketing phase, and especially its excellent fatigue resistance and mechanical properties promote active researches on the similar products of hybrid composite. This study aims to investigate the effects of CFRP volume ratio and fiber's orientation over the properties of mechanical strength and fatigue life of the hybrid composite, AI7075/CFRP. To carry out this study, static tensile and fatigue tests were given to some of the panels which, made through the co-cure processing in an autoclave, have different CFRP volume ratio and carbon fiber orientations.

• Journal of Korea Game Society
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• v.16 no.6
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• pp.29-38
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• 2016

The Korean game industry has stopped growing due to internal and external instability. It is the fourth industrial revolution that has been mentioned as a new breakthrough in the domestic game industry in front of these internal and external instabilities. The fourth industrial revolution is changing the paradigm of the existing industrial structure, and has brought ecological changes not only to the manufacturing industry but also to the contents industry as a whole. In this paper, we will explore the development direction of domestic game industry through the 4th industrial revolution and study the relation between development of AI and AR / VR and game industry which will be the main core of the fourth industrial revolution in the future.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.99-106
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• 2012

This study analyzed about medium-sized companies with AIS systems and outsourcing services to relate that the system performance. In addition, for the most efficient outsourcing of AIS management plan were analyzed. In this study, studied the practical environment of AIS outsourcing that separated the operating departments and administrative departments and divisions information to small-mid size companies. The results of this study can be summarized as the first, small business outsourcing companies of AIS introduction of the initial accounting module if you run a higher job performance were analyzed. Second, AIS in the outsourcing of integrated modules for the system to operate through the performance was very high. Integrated operation to be analyzed according to the synergistic effect. The results of this study AIS in the future of manufacturing outsourcing, and how small and medium-sized building is expected to give alternation.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.148-154
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• 2021

We propose the AI Smart Factory Model for integrated management of production processes in this paper .It is an integrated platform system for the production of food packaging containers, consisting of a platform system for the main producer, one or more production partner platform systems, and one or more raw material partner platform systems while each subsystem of the three systems consists of an integrated storage server platform that can be expanded infinitely with flexible systems that can extend client PCs and main servers according to size and integrated management of overall raw materials and production-related information. The hardware collects production site information in real time by using various equipment such as PLCs, on-site PCs, barcode printers, and wireless APs at the production site. MES and e-SCM data are stored in the cloud database server to ensure security and high availability of data, and accumulated as big data. It was built based on the project focused on dissemination and diffusion of the smart factory construction, advancement, and easy maintenance system promoted by the Ministry of SMEs and Startups to enhance the competitiveness of small and medium-sized enterprises (SMEs) manufacturing sites while we plan to propose this model in the paper to state funding projects for SMEs.