• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.354-362
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• 2010

This paper presents a non-linear control chart based on support vector machine regression (SVM-R) to improve the accuracy of fault detection of cyclic signals. The proposed algorithm consists of the following two steps. First, the center line of the control chart is constructed by using SVM-R. Second, we calculate control limits by variances that are estimated by perpendicular and normal line of the center line. For performance evaluation, we apply proposed algorithm to the industrial data of the chemical vapor deposition process which is one of the semiconductor processes. The proposed method has better fault detection performance than other existing method

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2497-2504
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• 2000

This paper is aimed at defining items of fault, and then constructing rules of fault diagnosis and recovery using INBANCA technology for the purpose of managing the weh server. The fault items of web server consist of the process fault, server overload, network interface fault, configuration and performance fault. Based on these items, the actual fault management is carried out fault referencing. In order to reference the fault, we have formulated the system-level fault diagnosis production rule and the service-level fault diagnosis rule, conjunction with translating management knowledge into active network. Also, adaptive recovery mechanism of web server is applied to defining recovery rule and constructing case library for case-based web server fault recovery. Finally, through the experiment, fault environment and applicability of each proposed production rule and recovering scheme are presented to verify justification of proposed diagnosis rules and recovery mechanism for fault management. An intelligent case-based fault management scheme proposed in this paper can minimize an effort of web master to remove fault incurred web administration and operation.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1271-1280
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• 2020

The yield and quality of a micromanufacturing process are important management factors. In real-world situations, it is difficult to achieve a high yield from a manufacturing process because the products are produced through multiple nanoscale manufacturing processes. Therefore, it is necessary to identify the processes and equipment that lead to low yields. This paper proposes an analytical method to identify the processes and equipment that cause a defect in the plastic ball grid array (PBGA) during the manufacturing process using logistic regression and stepwise variable selection. The proposed method was tested with the lot trace records of a real work site. The records included the sequence of equipment that the lot had passed through and the number of faults of each type in the lot. We demonstrated that the test results reflect the real situation in a PBGA manufacturing process, and the major equipment parameters were then controlled to confirm the improvement in yield; the yield improved by approximately 20%.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.14-23
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• 2013

Fault management design of the satellite describes preparations for failures which can occur during operational phase. Fault management design contains detection and isolation function of anomaly, and also it contains function to maintain the satellite in safe condition until the ground station finds out a cause of failure and takes a countermeasure. Unlike normal operation, safing operation is automatically performed by Power Control and Distribution Unit and Integrated Bus Management Unit which loads Flight Software without intervention of ground station. Since fault management operation is automatical, fault management logic and functionality of relevant hardware should be thoroughly checked during ground test phase, and error which is similar to actual should be carefully applied without damage. Verification test for fault management design is conducted for various subsystems of satellite. In this paper, we show the design process of fault management design verification test for Electrical Power Subsystem and Attitude and Orbit Control Subsystem of Low Earth Orbit satellite flight model and the test results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3779-3784
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• 2012

Real-time process monitoring and diagnosis of industrial processes is one of important operational tasks for quality and safety reasons. The objective of fault diagnosis or identification is to find process variables responsible for causing a specific fault in the process. This helps process operators to investigate root causes more effectively. This work assesses the applicability of combining a nonlinear statistical technique of kernel Fisher discriminant analysis with a preprocessing method as a tool of on-line fault identification. To compare its performance to existing linear principal component analysis (PCA) identification scheme, a case study on a benchmark process was performed to show that the fault identification scheme produced more reliable diagnosis results than linear method.

• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.65-73
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• 2010

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

• Korean Management Science Review
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• v.12 no.1
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• pp.19-34
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• 1995

The objective of this paper is to present a framework for an expert system for fault diagnosis in an FMS (Flexible Manufacturing Systyem). First, a system is analyzed structurally and functionally, giving the relationships between the system's components. These relationships, represented by strata, are are then stored in a deep knowledge base (DKB). Next, the specific knowledge, represented by echelons, about the symptoms and their probable causes for each component is stored in a shallow knowledge base (SKB) in the form of rule. When the fault diagnosis process begins, it starts to search the DKB and then the SKB, which is called hybrid reasoning in artificial intelligence.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.780-785
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• 2010

The OPRoS (Open Platform for Robotic Services) framework is proposed as an application runtime environment for service robot systems. For the successful deployment of the OPRoS framework, fault tolerance support is crucial on top of its basic functionalities of lifecycle, thread and connection management. In the previous work [1] on OPRoS fault tolerance supports, we presented a framework-based fault tolerance architecture. In this paper, we extend the architecture with component-based fault tolerance techniques, which can provide more simplicity and efficiency than the pure framework-based approach. This argument is especially true for fault detection, since most faults and failure can be defined when the system cannot meet the requirement of the application functions. Specifically, the paper applies two widely-used fault detection techniques to the OPRoS framework: 'bridge component' and 'process model' component techniques for fault detection. The application details and performance of the proposed techniques are demonstrated by the same application scenario in [1]. The combination of component-based techniques with the framework-based architecture would improve the reliability of robot systems using the OPRoS framework.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1085-1095
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• 2000

In this paper, we have defined the rules and the algorithm for diagnosis and recovery of routing configuration fault on a system. By using them, we have implemented the Java-based system that can manage routing configuration fault automatically. To manage routing configuration fault, the production rule for network configuration management, the production rule for routing configuration fault diagnosis, and the production rule for routing configuration fault recovery have been proposed. Rule-based routing configuration fault management system has been implemented on the basis of backward chaining algorithm and applied for meta rules for the purpose of interconnecting the production rules. We have derived the experimental result from transition process of the rules, the Blackboard, the goals based on scenarios. Through the implementation of dynamically applicable system in heterogeneous and rapidly changing network environments, we have proposed the methodology for network configuration fault management. Also, we expect that network configuration manager can reduce time and cost wasted for routing configuration fault management.

• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.48-55
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• 2019

This paper presents a study on Fault History Management Equipment (FHME) of Unmanned Aerial Systems (UAS). UAS comprise of various types of electronic equipment for high reliability design for flight safety. Consequently, it is mandatory for each on-board equipment to have its own Built-In-Test (BIT) function, because rapid fault-detections for UAS are necessary. FHME is developed for the purposes of display, storage and management of such BIT results on ground. This paper describes the outline, development requirements, design and verification process of FHME.