• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.1-12
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• 2023

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.603-609
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• 2013

In this paper, we describe the analysis of inkjet-printed silver (Ag) patterns on epoxy-coated substrates according to several reliability evaluation test method guidelines for conventional printed circuit boards (PCB). To prepare patterns for the reliability analysis, various regular test patterns were created by Ag inkjet printing on flame retardant 4 (FR4) and polyimide (PI) substrates coated with epoxy for each test method. We coated the substrates with an epoxy primer layer to control the surface energy during printing of the patterns. The contact angle of the ink to the coated epoxy primer was $69^{\circ}$, and its surface energy was 18.6 $mJ/m^2$. Also, the substrate temperature was set at $70^{\circ}C$. We were able to obtain continuous line patterns by inkjet printing with a droplet spacing of $60{\mu}m$. The reliability evaluation tests included the dielectric withstanding voltage, adhesive strength, thermal shock, pressure cooker, bending, uniformity of line-width and spacing, and high-frequency transmission loss tests.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.184-191
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• 2017

Progress indicators provide information about downloading progress and the remaining time. Two common forms of indicator are bar and spinner. However, most studies have focused on the form of bar. Therefore, we are going to investigate which patterns of progress spinner show better perceived speed and satisfaction. Also the effects of provision of time information were studied. This study provided the progress spinner with different patterns with 4 seconds and 12 seconds download latencies. The participants evaluated overall satisfaction and perceived downloading speed. As a result, 'Speed Up' patterns showed the higher perceived downloading speed and satisfaction than 'Speed Down' patterns. In 4s situation, it was better with time information was absent. In 12s situation, it was higher in terms of the perceived downloading speed when time information was provided.

• IE interfaces
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• v.25 no.1
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• pp.79-86
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• 2012

Traditional business process management systems provide verification tools of process models to deploy and automate the models. However, there are not so many studies on how to maintain systematically collaborative process models such as supply chain processes when companies are willing to change and update the collaborative process models. In this paper, we analyze change patterns of collaborative processes and declare 19 change patterns. In addition, we apply the change patterns to the process interoperability patterns in order to identify the change problems in case of independent process changes of collaborative processes. As a result, we devise an independency checking algorithm of process changes in collaborative processes.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.247-254
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• 2018

Purpose: Although previous studies have performed on-farm evaluations for the control of airborne diseases such as foot-and-mouth disease (FMD) and influenza, disease control during the process of livestock and manure transportation has not been investigated thoroughly. The objective of this study is to predict common patterns of livestock-vehicle movement. Methods: Global positioning system (GPS) data collected during 2012 and 2013 from livestock vehicles on Jeju Island, South Korea, were analyzed. The GPS data included the coordinates of moving vehicles according to the time and date as well as the locations of livestock farms and manure-keeping sites. Data from 2012 were added to Esri software ArcGIS 10.1 and two approaches were adopted for predicting common vehicle-movement patterns, i.e., point-density and Euclidean-distance tools. To compare the predicted patterns with actual patterns for 2013, the same analysis was performed on the actual data. Results: When the manure-keeping sites and livestock farms were the same in both years, the common patterns of 2012 and 2013 were similar; however, differences arose in the patterns when these sites were changed. By using the point-density tool and Euclidean-distance tool, the average similarity between the predicted and actual common patterns for the three vehicles was 80% and 72%, respectively. Conclusions: From this analysis, we can determine common patterns of livestock vehicles using previous year's data. In the future, to obtain more accurate results and to devise a model for predicting patterns of vehicle movement, more dependent and independent variables will be considered.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.86.4-86
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• 2001

This paper presents the results of a visualization analysis of the correlation between the fiber orientation and flow pattern in injection molding using the Gate-magnetization method developed for the precise visualization of melt flow. The results of the comparisons of the fiber orientation angles with the flow patterns by the Gate-Magnetization method for GPPS mixed with glass fibers show the strong correlation between the flow patterns and fiber orientation angles. According to forward movement of the flow, the fiber orientation patterns move toward the side walls following the flow patterns. These results elucidate that fibers are oriented in the expansion process of the melt, and ...

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1450-1451
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• 2008

To investigate the reliability of the conductive lines patterned by ink-jet printing, we evaluated the reliability of the ink-jet printed silver (Ag) patterns according to the guide lines built up as assessments methods in the production of conventional rigid printed circuit boards. The assessment methods include the uniformity of line width and space, adhesive strength, dielectric withstand, solder float, thermal shock test and pressure cooker test (PCT). To prepare assesment vehicles, different regular test patterns were created by Ag ink-jet printing on the same polyimide substrate for each of assessment methods.

• Journal of the Ergonomics Society of Korea
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• v.33 no.6
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• pp.453-463
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• 2014

Objective:The purpose of this study is to identify motion patterns for cellular phone and propose a method to identify motion patterns using a motion capture system. Background: In a smart device, the introduction of tangible interaction that can provide new experience to user plays an important role for improving user's emotional satisfaction. Firstly, user's motion patterns have to be identified to provide an interaction type using user's gesture or motion. Method: In this study, a method to identify motion patterns using a motion capture system and user's motion patterns for using cellular phone was studied. Twenty-two subjects participated in this study. User's motion patterns were identified through motion analysis. Results: Typical motion patterns for shaking, shaking left and right, shaking up and down, and turning for using cellular phone were identified. Velocity and acceleration for each typical motion pattern were identified, too. Conclusion: A motion capture system could be effectively used to identify user's motion patterns for using cellular phone. Application: Typical motion patterns can be used to develop a tangible user interface for handheld device such as smart phone and a method to identify motion patterns using motion analysis can be applied in motion patterns identification of smart device.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.412-421
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• 2013

Motion picture industry is one of the most representative fields in the cultural industry and has experienced constant growth both worldwide and within domestic markets. However, little research has been undertaken for diffusion patterns of motion pictures, whereas various issues such as demand forecasting and success factor analysis have been widely explored. To analyze diffusion patterns, we adopted extended Bass model to reflect the potential demand of movies. Four clusters of selected movies were derived by k-means clustering method with criteria of opening strength and profitability and then compared by their diffusion patterns. Results indicated that movies with high profitability and medium opening strength are most significantly influenced by word of mouth effect, while low profitability movies display nearly monotonic decreasing diffusion patterns with noticeable initial adoption rates and relatively early peak points in their runs.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.290-295
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• 2016

This paper proposes a new method for the automatic detection of atrial fibrillation (AF), using Markov regime switching GARCH (1, 1) model. The proposed method is based on the observation that variability patterns of heart rate intervals during AF significantly differ from regular patterns. The proposed method captures the different patterns of heart rate intervals between two regimes : normal and AF states. We test the proposed method using Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) atrial fibrillation database, and demonstrate the effectiveness of the proposed method.