• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1144-1151
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• 2021

The pressing process is a compression process in which a product is made by applying force to a heated or unheated material to transform it into the desired shape. Due to the characteristics of press equipment that produces products through continuous compression for a short time, product defects occur continuously, and systems for solving these problems are being developed using various technologies. This paper proposes a real-time defect detection system based on an artificial intelligence algorithm that detects defects. By attaching various sensors to the press device, the relationship between equipment status and defects is defined and collected based on a big data platform. By developing an artificial intelligence algorithm based on the collected data and implementing the developed algorithm using an embedded board, we will show the practicality of the system by applying it to the actual field.

• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.15-21
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• 2019

X-rays with shorter wavelengths than ultraviolet light have very good penetration power. It is convergence in industrial and medical fields has been used a lot. n particular, in the industrial field, various researches have been conducted on the detection of foregin body inside metal that can occur in the production process of products such as metal using x-ray, a non-destructive inspection device. Detectors are becoming increasingly popular for the popularization of DR (Digital Radiography) photography methods that digitally acquire X-ray video images. However, there are cases where foreign body detection is impossible depending on the sensor noise and sensitivity inside the detector. When producing a metal product, since the defective rate of the produced product may increase due to contamination of the foreign body, accurate detection is necessary. In this paper, we provide a correction model for X-ray images acquired in order to improve the efficiency of defect detection such as foreign body inside metal. When applied to defect detection in the production process of metal products through the proposed model, it is expected that the detection of product defects can be processed accurately and quickly.

• Journal of Korean Society for Quality Management
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• v.52 no.2
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1979-1983
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• 2011

FRP(Fiber Reinforced Plastic) support insulators for DC(direct current) were developed and their electrical and mechanical characteristics were investigated. Electrical tests were carried out to measure flashover voltages under common use frequency condition. Tensile and bending tests were performed for the mechanical characteristics. The test results showed that FRP support insulators have superior voltage resistances and strengths to porcelain insulators. Field test also is carried out to measure adaptation and to compensate the defect. The test result showed that a new product has no defect in electrical and mechanical.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10a
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• pp.21-24
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• 2003

In hot forming process of the backward end-bulkhead of a pressure hull, the blank diameter and the tool clearance are the critical factors which influence wrinkling defect, forming load and shape completeness of the product. Two F.E.A softwares with the elasto-plastic material model and rigid plastic model were utilized to predict the occurrence of wrinkling defect. Tool clearance was determined by considering the increase of blank thickness, die strength and the stretching effect. Heat treatment condition after the hot forming to recover the original properties of the material was estabilished by specimen-based heat treating experiment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.41
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• pp.135-145
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• 1997

The statistical approach to quality control aims at alerting its user to any variations in the properties of a manufactured product. Motorola developed and pursued a quality management program called six sigma. The goal of six sigma programs is to improve customer satisfaction through reducing and eliminating defects. six sigma uses several statistical measure to characterize defect levels and process capabilities. The upper and lower specification limits are $\pm6\sigma$(sigma) from nominal, and the process mean is centered at nominal. only 0.002PPM are outside specification limits. Cp=2. this is the design target in a six sigma program. This article presents an important tool available for quality control of a production process at the occurrence of defects in manufactured products at view low levels to improve the efficiency of the manufacturing productivity and to satisfy customer through the reduction of defect rates. To understand the consequences of the level of quality on competitive position, a more technical perspective is needed.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.9-16
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• 2012

It is often thought that when a fire is found in parked motor vehicles, the fire may occur after an engine stops. Also, it is easy to judge that when motor vehicle fires occur during engine stopping, it may be caused by arson or electrical causes irrespective of a fuel system. This study analyzed motor vehicle fires which occurred in operation but were found after parking and revealed that these fires were caused by the defect of a fuel system and the same motor vehicle types had fires by the same causes. Moreover, this study provided judgement process of major fire causes and periods for fire investigators to apply when investigating fires of parked motor vehicles. And this fire is related to automotive products liability.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.32-39
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• 2004

Traditional forging of a hollow T-shaped part has been applied to forge a solid T-shaped product from a solid billet and then to machine the hollow in that. In a case, a hollow T-shaped part can be forged by backward-extruding from a solid billet. In this study, four types of forging were suggested for manufacture of hollow T-shaped parts. Forging simulations for each of these forging methods were carried out to investigate folding defect, metal flow pattern, effective strain, and forging loads. Experimental works were carried out to be compared with the simulation results. Here, the ratio of the thickness of the hollow tube to that of the flange was selected to investigate a forging defect like folding.

• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.79-101
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• 1994

In modern manufacturing, a product consists of many components created by different processes. Variations in the individual component dimensions and in the processes may result in unacceptable final assemblies. Thus, engineers have increased pressure to properly set tolerance specifications for individual components and to control manufacturing processes. When a proper variation stack-up analysis is not performed for all of the components in a functional system, all component parts can be within specifications, but the final assembly may not be functional. Thus, in order to improve the performance of the final assembly, a proper variation stack-up analysis is essential for specifying dimensional tolerances and process control. This research provides a detailed case example of the use of variation stack-up analysis using a Monte Carlo simulation method to improve the defect rate of a complex process, which is the commutator brush track undercut process of an armature assembly of a small motor. Variations in individual component dimensions and process mean shifts cause high defect rate, Since some dimensional characteristics have non-normal distributions and the stack-up function is non-linear, the Monte Carlo simulation method is used.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.4
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• pp.31-36
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• 2001

A spin coater is a machine to coat wafer or LCD display with thin film. Vibration in the spin coater may be one of main troubles in the coating process. In this paper, we focus on the difference between two spin coaters. Vibration sources are identified by experimental approach and are compared to find the difference between the two spin coaters. Also, the particle concentration is observed by laser particle counter (LPC) for the two spin coaters, when the spin coaxers are working. It is also considered whether the defect rate is proportional to the particle concentration. The result shows that particle generation in the coating process is related to excessive vibration of the spin coater shaft and the particles influence the defect rate of the thin film product.