• Steel and Composite Structures
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• v.43 no.4
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• pp.501-509
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• 2022

Cracks are common defects in concrete structures. Thus far, crack inspection has been manually performed using the contact inspection method. This manpower-dependent method inevitably increases the cost and work hours. Various non-contact studies have been conducted to overcome such difficulties. However, previous studies have focused on developing a methodology for non-contact inspection or local quantitative detection of crack width or length on concrete surfaces. However, crack depth can affect the safety of concrete structures. In particular, although macrocrack depth is structurally fatal, it is difficult to find it with the existing method. Therefore, an experimental investigation based on non-contact infrared thermography and multivariate machine learning was performed in this study to estimate the hidden macrocrack depth. To consider practical applications for inspection, an experiment was conducted that considered the simulated piloting of an unmanned aerial vehicle equipped with infrared thermography equipment. The crack depths (10-60 mm) were comparatively evaluated using linear regression, gradient boosting, and random forest (AI regression methods).

• Smart Media Journal
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• v.11 no.9
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• pp.47-55
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• 2022

Quality control in the smart factory manufacturing process is an important factor. Currently, quality inspection of home appliance manufacturing parts produced by the mold process is mostly performed with the naked eye of the operator, resulting in a high error rate of inspection. In order to improve the quality competition, an automatic defect detection system was designed and implemented. The proposed system acquires an image by photographing an object with a high-performance scan camera at a specific location, and reads defective products due to scratches, dents, and foreign substances according to the vision inspection algorithm. In this study, the depth-based branch decision algorithm (DBD) was developed to increase the recognition rate of defects due to scratches, and the accuracy was improved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.952-956
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• 1995

It is known that the 3D Solid CAD system can provide various information which is useful for implementing CAPP and CAE. However the commercial 3D CAD systems available today do not support the handling of non-geometric information such as geometry tolerance and surface finish. It is impossible to input the non-geometric information during designof parts while CAPP needs the information for selecting machine tools. fiztures, inspection method, etc. In this paper the need of research on handling tolerance information In 3D CAD systems is considered. The development of inspection planning support system is also explained with an example. The development of inspection planning support systm receives the design geometry information from the 3D CAD system in the form of 2D draft and generates the inspection data base and the inspection sheet through the user interaction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.1-8
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• 2003

The operation and management of a plant require proper accounting for the constraints coming from reliability requirements as well as from budget and resource considerations. Most of the mathematical methods to decide the inspection time interval for plant maintenance by reliability theory are too complicated to be solved. Moreover, the mathematical and theoretical models are not usually cases in the practical applications. In order to overcome these problems, we propose a new the decision-making method of optimal inspection interval to minimize the maintenance cost by reliability theory and genetic algorithm (GA). The most merit of the proposed method is to decide the inspection interval for a plant machine of which failure rate $\lambda$(t) conforms to any probability distribution. Therefore, this method is more practical. The efficiency of the proposed method is verified by comparing the results obtained by GA-based method with the inspection model haying regular time interval.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.5
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• pp.157-161
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• 2007

There are technological changes to reduce the size and weight of electronic components and to accommodate multi-functions in them. To meet this trend, more complicated technological processes are required. To maintain the processes, more accurate inspection systems are also necessary. Therefore, new inspection methods are needed, which is differ from conventional inspection methods such as electrical test methods ICT(In-Circuit Test), FCT(Function Test) and visual test using optical equipments. One of the possible approaches is non-destructive test using X-ray. In this paper, an inspection method using X-ray is developed and applied to inspection of soldering state and internal defects of electronic components.

• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.67-74
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• 2019

Visual inspection is regarded as one of the critical activities for quality control in a manufacturing company. it is thus important to improve the performance of detecting a defective part or product. There are three probable working modes for visual inspection: fully automatic (by automatic machines), fully manual (by human operators), and semi-automatic (by collaboration between human operators and automatic machines). Most of the current studies on visual inspection have been focused on the improvement of automatic detection performance by developing a better automatic machine using computer vision technologies. However, there are still a range of situations where human operators should conduct visual inspection with/without automatic machines. In this situation, human operators'performance of visual inspection is significant to the successful quality control. However, visual inspection of components assembled into a mobile camera module belongs to those situations. This study aims to investigate human performance issues in visual inspection of the components, paying more attention to human errors. For this, Abstraction Hierarchy-based work domain modeling method was applied to examine a range of direct or indirect factors related to human errors and their relationships in the visual inspection of the components. Although this study was conducted in the context of manufacturing mobile camera modules, the proposed method would be easily generalized into other industries.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.5
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• pp.259-265
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• 2024

In this paper, we propose an automatic display defect detection system using image processing. The existing inspection by operators has the disadvantage that human errors may occur due to the operator's skill level, fatigue, etc., and that standardization and quantification are difficult. It also has disadvantages such as the limited inspection speed and the cost of the operator's education. The proposed system automatically detects various display defects through image processing algorithms. It was developed based on the Jetson Nano, one of the most popular SBCs (Single Board Computers), and it has a conveyor belt to automatically moves the display to the inspection position. By providing a human machine interface (HMI), the operator can check the inspection information in real time, and control the inspection flow. By storing the inspection results as a log file, the operator can check the inspection results at any time, such as the time taken to perform each algorithm and the location of the detected defects. In addition, a multi-threaded structure was adopted. The camera's operations and inspection algorithms are executed in parallel in different threads, which can shorten the inspection time compared to the system based on a single-threaded structure. The experimental results prove the defect detection capability of the system and the efficiency of the inspection time.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.405-406
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.399-400
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• 2007

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.401-402
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• 2007