• IE interfaces
• /
• v.20 no.3
• /
• pp.288-297
• /
• 2007

Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.12
• /
• pp.141-149
• /
• 2013

This paper presents a high-speed intrusion detection process for multi-core video surveillance systems. The high-speed intrusion detection was designed to a parallel process. Based on the analysis of the conventional process, a parallel intrusion detection process was proposed so as to be accelerated by utilizing multiple processing cores in contemporary computing systems. The proposed process performs the intrusion detection in a per-frame parallel manner, considering the data dependency between frames. The proposed process was validated by implementing a multi-threaded intrusion detection program. For the system having eight processing cores, the detection speed of the proposed program is higher than that of the conventional one by up to 353.76% in terms of the frame rate.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.2
• /
• pp.115-123
• /
• 2021

A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

• Design & Manufacturing
• /
• v.11 no.3
• /
• pp.35-40
• /
• 2017

PCR(Polymerase chain reaction) is a technique to replicate and amplify a desired part of DNA. It is used in various aspects such as DNA fingerprint analysis and rare DNA amplification of an extinct animal. Especially in the medical diagnosis field, it provides various measurement methods at the molecular level such as genetic diagnosis, and is a basic tool for molecular diagnostics. The internal shape of the plastic vial tube for PCR analysis used in the DNA detection process, and the surface roughness and internal cleanliness can affect detection and discrimination results. The plastic vial tube demanded by the developer of the PCR analysis equipment should be changed to a structure that eliminates the residual washing solution in the washing process to ensure the internal cleanliness. Thus the internal structure and the internal surface design for improving the PCR amplification efficiency are key issues to develop the plastic vial tube for the DNA detection process.

• Journal of the Korea Society of Computer and Information
• /
• v.23 no.1
• /
• pp.17-24
• /
• 2018

With improvement of speech recognition and natural language processing, dialog systems are recently adapted to various service domains. It became possible to get desirable services by conversation through the dialog system, but it is still necessary to improve separate modules, such as domain detection, intention detection, named entity recognition, and out-of-domain detection, in order to achieve stable service offer. When it misclassifies an in-domain sentence of conversation as out-of-domain, it will result in poor customer satisfaction and finally lost business. As there have been relatively small number of studies related to the out-of-domain detection, in this paper, we introduce a new method using a hierarchical Dirichlet process and demonstrate the effectiveness of it by experimental results on Korean dataset.

• Journal of Multimedia Information System
• /
• v.8 no.4
• /
• pp.211-220
• /
• 2021

The process of inspecting SMDs on the PCB boards improves the product quality, performance and reduces frequent issues in this field. However, undesirable scenarios such as assembly failure and device breakdown can occur sometime during the assembly process and result in costly losses and time-consuming. The detection of these components with a model based on deep learning may be effective to reduce some errors during the inspection in the manufacturing process. In this paper, YOLO models were used due to their high speed and good accuracy in classification and target detection. A SMD detection and classification method using YOLO networks based on robust data preprocessing and augmentation techniques to deal with various types of variation such as illumination and geometric changes is proposed. For 9 different components of data provided from a PCB manufacturer company, the experiment results show that YOLOv4 is better with fast detection and classification than YOLOv3.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.415-418
• /
• 1996

Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.702-705
• /
• 2006

Change detection is a core function of remote sensing. It can be widely used in public services such as land monitoring, damage assessment from disaster, analysis of city growth, etc. However, it seems that the change detection using satellite imagery has not been fully used in public services. For the person who is in charge of public services, it seems not to be ease to implement the change detection because various functions are combined into it. So, to promote the use of the change detection in public services, the standard, the process and the method for the change detection in public services should be established. And the software which supports that will be very useful. This study aims to promote the use of satellite imagery in public services by building up the change detection process which are suitable for general public services and developing the change detection software to support the process. The software has been developed using ETRI Components for Satellite Image Processing to support the interoperability with other GIS software.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.2
• /
• pp.192-197
• /
• 2020

Multivariate processes, such as large scale power plants or chemical processes are operated in very hazardous environment, which can lead to significant human and material losses if a fault occurs. On-line monitoring technology, therefore, is essential to detect system faults. In this paper, the ICA-based fault detection method is conducted using three different multivariate process data. Fault detection procedure based on ICA is divided into off-line and on-line processes. The off-line process determines a threshold for fault detection by using the obtained dataset when the system is normal. And the on-line process computes statistics of query vectors measured in real-time. The fault is detected by comparing computed statistics and previously defined threshold. For comparison, the PCA-based fault detection method is also implemented in this paper. Experimental results show that the ICA-based fault detection method detects the system faults earlier and better than the PCA-based method.

• Journal of the Korea Institute of Building Construction
• /
• v.12 no.3
• /
• pp.299-314
• /
• 2012

One of reasons for introducing Building Information Modeling (BIM) is to support clash detection tasks by means of a 3D product model. In the conventional construction project process, clashes have been found during construction phase. However, it can cause cost overrun and time delay. In order to investigate and correct clash detections at design phase, relevant business process and guide for this task should be provided. This study aims to identify hindrances in clash detection tasks at the design phase and analyze its current process using IDEF0 model. Despite the convenience of IDEF0 as a systems analysis tool, professional participants might have difficulties to understand their own tasks according to business process. For this reason, in this research, Business Process Model and Notation (BPMN) is introduced to provide ideal process and required decision making governance. The provide BPMN model will provide insights for a BIM-based collaborative environment to enhance the constructability through the construction project.