Electrical failure analysis for root-cause determination
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Root Cause Analysis
Failure causes
Failure mechanism
Mode (computer interface)
Component (thermodynamics)
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The power system need to sustain high reliability due to its complexity and security. The reliability prediction method is usually based on independent failure. However, the common cause failure affects many components simultaneously in a system, and it turns out the system collapse seriously in a wide range. Therefore, to improve the reliability of the power system practically, the analysis using the common cause failure is required. This paper describes the common cause failure modeling combined with independent failure. Using the dynamic fault tree, the incorporated independent failure and common cause failure are proposed and analyzed, and it is applied to the power substation in order to examine the method.
Common cause failure
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The emphasis of electronic product reliability analysis and assessment is to determine the high-risk links.Based on the analysis consideration of failure mechanism,use the analysis method associated with components,failure mode,failure mechanism and impact factor,through the physical model and an electronic analysis case,realize the whole process which determined the high-risk links and product reliability,and concludes that failure mechanism analysis is more practical than failure mode analysis at last.
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This paper reports on attempts to perform detailed failure mode analysis of selected boiler pressure-part failures of medium-size fossil-fuel-fired electricity-generating units. The objective of a root-cause failure analysis is to identify the origin of the conditions that allowed failure by the observed failure mechanism to occur. Sample collection (of failed, partially failed, and of unfailed referee samples) for use in detailed laboratory studies to determine the failure mechanism (e.g., corrosion-fatigue cracking or rupture due to hydrogen damage) was an integral part of the investigative effort. Topics considered include the identity of the problem, the location of the problem, the timing of the problem, the magnitude of the problem, and analysis for cause. A physical description of the defect and definition of its failure mechanism were critical elements in the Kepner-Tregoe problem-solving method because knowledge of the type of failure mechanism was used to direct data-collection efforts in related areas.
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This scope of this paper is to provide an extension to the Function Failure Design Method (FFDM). We first implement a more robust knowledge base using Failure Mode/Mechanism Distributions 1997 (FMD-97). Then failure rates from Nonelectric Parts Reliability Data (NPRD-95) are added to more effectively determine the likelihood that a failure mode will occur. The proposed Functional Failure Rate Design Method (FFRDM) uses functional inputs to effectively offer recommendations to mitigate failure modes that have a high likelihood of occurrence. This work uses a past example where FFDM and Failure Modes and Effects Analysis (FMEA) were compared to show that improvements have been made. A four step process is presented to show how the FFRDM is used during conceptual design.
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The paper applies the interrelated method of common cause failure to work out the parameters of common cause model with Bayesian estimate based on the classification and impact vector assessment of events involving component, and considering special function of check valve, and applies GO Methodology to work out the fault probabilities in start-up and operation process of the system. Its result shows that the common cause failure is very important in the reliability analysis for the redundancy system.
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It is found there are some deep-rooted causes that lead to functional failures of some crucial components on modern equipment, these deep-rooted causes probably can not be eliminated effectively by traditional maintenance works, and then the same failures take place again soon after. By analyzing characteristics of failure control theory and relationships between these various failures, this paper put forward the idea that the failure life process, in a broader sense, could be described in terms of cycle, therefore, this process is called failure life cycle (FLC), the cycle can be divided into five phases including incubation phase, root cause phase, medium characteristics cause phase, potential failure phase, and function failure phase. By applying the idea of process control, a failure life control method based on Markov process is established, to root out the direct causes and root causes of failure life comprehensively in the process of equipment operation, hence the failure could be thoroughly eliminated. Finally an example is introduced to verify rationality and validity of this method.
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Design for reliability requires a different approach from failure reporting and corrective action system (FRACAS) and test, analyze and fix (TAAF) both of which are tools for reliability improvement of already designed hardware. The physics of failure analysis approach should be used focusing on each failure mode separately. Through a step by step design analysis and test process, the number of potential failure modes should be reduced. As many failure modes as possible should be mitigated by appropriate design changes and the remaining failure modes should be controlled through adequate design stress vs. strength margins. The failure modes with insufficient margins (meaning high likelihood of occurrence in the time of interest) should be extensively analyzed and tested to ensure that they do not contribute to an unacceptable number of failures in the field. The use of this method requires that the equipment manufacturer also actively collect and list failure modes for previous products as well as for components, materials and processes.
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It is now widely recognised that the synthesis of the reliability of a series mechanical system from generic component failure data can present some difficulty as the product rule can provide a pessimistic prediction of the reliability of a mechanical system. In this paper this difficulty is further examined. The effects on synthesised system reliability values of a number of different assumptions relating to component failure data analysis are examined theoretically. It is a characteristic feature of many types of mechanical system, that the failure of one component can result in the consequential failure of other components in the system. A given component could thus fail as a consequence of the failure of another component in the system or it could fail in its own right independently of all other components in the system. A given set of generic component failure data could include failures of both types. The theoretical implications of different failure mechanism assumptions are considered and their effects on the predicted values of system reliability are examined. The relevance of the theoretical analysis is demonstrated by briefly considering a number of specific examples of the different types of physical failure mechanism involved and these are considered in relation to a number of mechanical system types. Order from BSRA as No. 54, 853.
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Failure modes and effects analysis (FMEA) is one of the most important analysis tools in reliability engineering However, some failure causes may be very difficult to detect when using only FMEA, and we found no methodical way to circumvent this limitation. This article describes the inter-crossing method, that significantly decreases the chance of failing to notice failure causes. The method that we propose is systematic; it enables one to "scan" the design and to expose elusive failure causes.
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