FTA technique addressing fault criticality and interactions in complex consumer communications

α-Cut method based importance measure for criticality analysis in fuzzy probability – Based fault tree analysis

International Maritime Organization (IMO) implements the principles of risk management through a systematic process called Formal Safety Assessment (FSA). FSA is a structured and systematic methodology, aimed at enhancing maritime safety, including protection of life, health, the marine environment and property, by using risk analysis and cost benefit assessment. One of the most widely used hazard identification and risk analysis techniques in FSA is Fault Tree Analysis (FTA) method. However, only basic conventional methodology of the FTA technique is used in FSA. When dealing with large fault trees, the limitations of FTA in terms of accuracy and the efficiency become apparent. It is necessary for IMO to improve FTA method in FSA. In recent years, the Binary Decision Diagram (BDD) method has been developed that solves fault trees and overcomes the disadvantages of the conventional FTA approach. In this paper, the BDD method is introduced for the application in FSA, as it has never been used in FSA studies. A commonly used construction method and some basic event ordering methods of BDD are described. By applying BDD to FTA, two main issues concerned in FSA, minimal cut set and top event probability, can be obtained efficiently and accurately comparing to the analysis using a conventional FTA method.

Smart transmitters are increasingly being deployed in safety critical systems. Although the processing and diagnostic features provided by digital systems are advantageous, it introduces additional complexity in reliability modelling of systems. The conventional Fault Tree Analysis (FTA) method for system reliability analysis has its shortcomings in modelling digital systems, to incorporate its dynamic system interaction and failure modes in detail. This is because some of the failure modes may arise due to the dynamic interactions between the modules of the system. Dynamic Flowgraph Methodology (DFM) was identified as one of the optimistic approaches to handle these interactions. DFM approach combines multi‐valued logic modelling and analysis capabilities to handle systems consisting of components that have multiple degraded states and exhibit dynamic behaviour. However, only few DFM tools have been developed and some of them are not available in public domain. The DFM approach relies heavily on development and implementation of its decision tables. The logic information present within the decision tables can be meticulously implemented using Petri Nets. Also, there are plenty of free Petri Nets tools available online. Thus, the idea of DFM was used in this work to capture the dynamic interactions by developing decision tables. The decision tables were transformed into the Petri Net models to perform the analysis. The paper demonstrates the potential of the hybrid DFM – Petri Net approach for dynamic reliability analysis of smart transmitter.

Objective To investigate IMRT planning process using the combined application of failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by reference to the report of Task Group 100 of the AAPM, and stablish and optimize the quality. Methods A multidisciplinary team detailed the process mapping of IMRT planning using Eclipse TPS. The team evaluated the potential failure modes (FMs) of every process step. The evaluation was divided into two groups according to whether quality management (QM) was considered. For every FM, occurrence (O), severity (S) and detectability (D) by consensus were evaluated, and the product of O, S and D yielded the risk priority number (RPN), which permitted the ranking of the FMs. Finally, FTA was used to determine the root factors contributing to the riskiest failure modes. Results The IMRT plan process consisted of 10 major sub-processes and 33 steps, which amounted to 47 failure modes. For the group without quality management, the RPN of FMs was between 13.2-271.8, 27 of which had RPN≥80, and 18 FMs had S≥8. For the group with quality management, the RPN of FMs was between 11.2-158.4, 11 of which had RPN≥80. The difference of RPN between the two groups was statistically significant (RPN of the group without QM=101.17±66.34, RPN of the group with QM=59.54±35.64, t=8.501, P<0.05). Finally, FTA was used to determine the root factors contributing to the FMs, i. e., prescription dose definition and importing images. Conclusions The FMEA and FTA methods are operable and practical, which can systematically and comprehensively analyze the potential failures and risks existing in the process of IMRT plan. And the FMEA and FTA can contribute to establish and optimize the quality management program in radiotherapy. Key words: Intensity modulated radiotherapy; Failure modes and effects analysis; Failure tree analysis; Quality management

Wind turbines are complex and expensive equipment, requiring high reliability and low maintenance costs. However, most of the existing fault tree analysis (FTA) methods for reliability analysis of wind turbines assume that the repair of wind turbines can restore them to as good as new condition, which is called perfect repair. This assumption may not be realistic in practice, as the repair may not fully recover the original performance or functionality of the equipment or may introduce new defects or errors. This phenomenon is called imperfect repair, which can reduce the reliability of wind turbines over time. To consider the imperfect repair effect in reliability analysis, we present a new FTA approach in this study. In order to predict and assess the failure intensity and dependability of wind turbines under imperfect repair, the proposed FTA technique uses a log-linear proportional intensity model (LPIM). Failure probability, failure rate, and mean time to failure can all be improved with the suggested FTA technique for wind turbines operating with poor repair. The proposed FTA method can also identify the critical components or failure modes most affected by the imperfect repair effect and suggest preventive maintenance actions to improve the reliability of wind turbines. We demonstrate the applicability and effectiveness of the proposed FTA method through a case study on a real or hypothetical wind turbine system under imperfect repair. The findings indicate that the proposed FTA method offers a more precise and authentic assessment of the reliability of wind turbines in the presence of imperfect repair, in contrast to existing FTA methods that assume perfect repair. The findings also demonstrate that the electrical system, hydraulic system, gearbox, generator, and blade are the most critical components or failure modes affecting the system's reliability.

&lt;div class="htmlview paragraph"&gt;Fault tree analysis (FTA) evolved from the aerospace industry in the 1960’s. A fault tree is deductive logic model that is generated with a top undesired event in mind. FTA answers the question, “how can something occur?” as opposed to failure modes and effects analysis (FMEA) that is inductive and answers the question, “what if?” FTA is used in risk, reliability and safety assessments. FTA is currently being used by several industries such as nuclear power and chemical processing. Typically the automotive industries uses failure modes and effects analysis (FMEA) such as design FMEAs and process FMEAs. The use of FTA has spread to the automotive industry. This paper discusses the use of FTA for automotive applications. With the addition automotive electronics for various applications in systems such as engine/power control, cruise control and braking/traction, FTA is well suited to address failure modes within these systems. FTA can determine the importance of these failure modes from various perspectives such as cost, reliability and safety. A fault tree analysis of a car starting system is presented as an example.&lt;/div&gt;

A new method for fuzzy fault tree analysis

Detailed software analysis requires a manageable and exhaustive problem solving technique. An approach, the fault locator and weighting system (FLAWS), is described. FLAWS is coupled with a software tool, the data structure analysis system (DSAS), to facilitate techniques for detailed software analysis. DSAS reads the target system code from source files and builds an exhaustive database of the target code, making detailed analysis of large systems manageable. The commands of a target language have been translated to a compatible graphical representation. Safety critical portions of a 200 KSLOC program have been diagrammed using these graphical elements. The resulting diagrams are schematics of the system logic. These schematics tie all identified inputs to their associated outputs, including all coding errors. The FLAWS process and database permit exhaustive connectivity analysis of new target system code. FLAWS uses conventional fault tree analysis (FTA) symbolism and is generally applicable to large software systems. >

Summary Such classic risk-assessment techniques as failure mode and effect analysis(FMEA) and fault-tree analysis (FTA) are in common use by engineers but have anumber of shortcomings. Dynamic simulation, a new computer technique, countersmany of these deficiencies by introducing a time element that accommodatesrealistic component-failure characteristics and testing and inspectionactivities. This paper demonstrates how FMEA and FTA have been used to helpdesign North Sea well completions and how dynamic simulation models complexsystems realistically to allow comparison of designs and to provide insightinto operating availability and component-testing frequencies. Introduction Both single- and dual-string gas-lift completions are commonly used in theNorth Sea, but it is not obvious which design provides greater safely andreliability. The single completion (Fig. 1) with annular safety valve issimpler to operate and to work over, but during normal production, it has alarge volume of high-pressure gas beneath the tubing hanger that acts on thehanger, tubing spool, production casing, and wellhead seals. The alternativedual-string design (Fig. 2), in which production is routed through the longstring and injection gas through the second or short string, reduces the gasinventory above the safety valve and removes the lift-gas pressure from theannulus. It is a more complicated system to operate and to maintain, however, and it has more component parts. To assist with the selection of completiontype, a conventional risk analysis was undertaken to rank the risks associatedwith each completion during both production and workover modes and to identifycritical components to allow for possible design changes. An FMEA provided aqualitative comparison of the two designs, and an FTA quantified the risks. While these static techniques successfully identified the critical components, they could not address such problems as changes in the well system withproblems as changes in the well system with time, undetected failures, effectsof inspection and maintenance, or components with failure distributions otherthan exponential. Use of a dynamic simulator, which simulates the performanceof the completion throughout many life cycles, provided a more realistic riskassessment and allowed sensitivity tests to be performed on maintenance andtest frequencies and undetected failures. We assumed that such conditions aswater cut and reservoir pressure were identical for both completion types. Theoretically, the influence of such conditions and the effect of varyingequipment sizes can be modeled by adjusting the reliability data, but eachspecific situation requires its own analysis. Reliability data were provided byRefs. 1 and 2, in addition to some proprietary data. Uncertainties are alwaysassociated with reliability data, and the application of the data isnecessarily based on judgment. Risks expressed numerically should be treated ascomparative rather than absolute. Note that, in the static and dynamic studiespresented here, different types of failure presented here, different types offailure distributions were used because more realistic distributions dmexponential ones were available for use in the dynamic simulation. Static Analysis FMEA. After definition of the two well systems to be compared (Figs. 1 and2), the first step in assessing the reliability of each system was to preparean FMEA. This involved identification of possible component failures and theirconsequences to provide a qualitative comparison of the inherent risks in eachsystem. To provide a basis for comparison of the FMEA for each well system, weprepared a list of very critical events (VCE's) prepared a list of verycritical events (VCE's) and critical events (CE's) to summarize each analysis. Events were defined as follows. VCE (Severity 1): loss of control of the well, possible loss of life, and evacuation necessary. CE (Severity 2): loss of oneor more safety barriers but not all barriers, evacuation possible, and majorworkover required. possible, and major workover required. Comparison of VCE'sand CE's for each system provided a qualitative assessment as to which systemwas likely to be more or less hazardous. FTA. FTA techniques previously applied to well-completion designs were usedin this study to provide a quantitative comparison of different designs. TheFTA is based on the component identification carried out in the FMEA, but theFTA differs from the FMEA because it is a top-down approach. Therefore, the topevent of interest (i.e., catastrophic wellhead-system failure) is defined and alogic tree is constructed of lower-level failures until the component-failurelevel is reached at the bottom of the tree. JPT P. 1374

In many industrial systems, where safety is of the utmost importance, it is necessary that expedient tools for accident analysis are available and employed at the design stage. Such tools must be able to handle large systems in a systematic way and display the factors that are of vital importance for the functionality of the system. The technique of fault tree analysis (FTA) is commonly used to assess the failure probability of such systems. The fault tree represents the failure logic of the system in an inverted tree structure and has the advantage that it provides very good documentation of the way the failure logic was developed. Conventional fault tree quantification requires a number of assumptions regarding the system. One of these is that the basic events in the tree occur independently. This condition is not satisfied when sequential failures are encountered. Employing alternative methods, such as Markov methods, can result in the loss of the documentation that represents the failure logic of the system. The cause-consequence diagram method is a tool that, like fault tree analysis, documents the failure logic but has the extra capability enabling the analysis of systems subject to sequential failures. In addition, the cause-consequence diagram identifies the complete set of system responses to any given initiating event. This paper is concerned with the cause-consequence diagram method and its application to sequentially operating systems. It extends previous work by providing more rigorous guidelines to enable the construction of the diagram and an analysis methodology that can be used when dependencies exist between the events featured in the decision boxes. A new symbol distinguishing between events that exist at a specified point in time and those that occur at that time is introduced to facilitate the analysis.

Recently, the development of reliability analysis system for combat system is required, because, necessities of integrated reliability analysis research are emphasized. In this paper, we develop a system which analyzes vulnerabilities for tank(or armored vehicle) based on the fault tree analysis(FTA) technique. The FTA is representative technique of reliability analysis to find cause of fault and calculate probability of fault. To do this, we propose a method to apply FTA technique into domain of vulnerability analysis for tank. Also, we develop the vulnerability analysis system using the proposed method. The system analyzes hit probabilities of components of tank based on multiple shot-lines, and calculates kill probabilities. The analyzed and calculated data support vulnerability analysis of tank. 키워드 : FTA, 피격 확률, 기능별 취약성, 취약성 분석, 전차 Key word : Fault tree analysis, Hit probability, Kill probability, Vulnerability analysis, Armored fighting vehicleJournal of the Korea Institute of Information andCommunication Engineering

The Italian construction sector suffered more than the other industrial sector the negative effects of the world economic crisis. A consequence has been a change in its organization concerning labour and managent on the health and safety issues. Evidence of this can be found in an increase of fatal accidents and occupational diseases. In particular occupational diseases became a health concern in construction. The aim of the presented research work is to assess the hazard of asbestos fibres inhalation due to decommissing of old industrial promises with roofing of asbestos. The developed approach starts from a probabilistic assessment of the risk, using the Risk Analysis tools, the Fault Tree Analysis (FTA) and the Failure Mode and Effect Analysis (FMEA). Risk assessment through the FTA is based on a backward approach: it starts from the malfunction of the system, called Top Event, in order to look for the triggering causes (events); on the contrary, the FMEA analysis is based on a forward approach: they start from a set of events and go on in order to analyse what kind of malfunctioning these can generate in the system. Both the FTA and the FMEA are applied to three approved decontamination techniques (encapsulation, confinement and removal), and for each of them operational phases, equipment, building products and PPE (Personal Protective Equipment) are evaluated highlighting the procedures needed to operate in complete safety. With this approach the main factors that contribute to the increase of the risk of asbestos fibres inhalation are detected: preliminary analysis and assessment of the state of building decay, the use and maintence of PPE and machinery, and the supervision during main working phases.

Fault Tree Analysis (FTA) is a powerful analytical technique for analyzing system reliability and safety by enumerating any possible safety-critical failure modes, which is very useful for identifying the risks and weaknesses in the system. Therefore, FTA is widely applied to the safety evaluation of large-scale and mission-critical systems. However, the following problems are usually pointed out when building a fault tree for a complex system: 1) System modeling is a hard and time consuming work, and 2) FTA models are difficult to be validated. In this paper, we propose a new method for system reliability analysis based on Multilevel Flow Models (MFM) and Goal Tree-Success Tree (GTST) methods. We use Goal Tree (GT) methodology to model the target system at a higher and system level, and use the Success Tree (ST) together with MFM at a lower and functional level. In this way, modeling effort could be significantly reduced. In this paper, an algorithm is also presented to translate the GTST-MFM model into ST model based on which qualitative reliability analysis can be performed by the Fusell-vesely algorithm. In this paper, a Low Head Safety Injection System (LHSIS) is taken as a case study to exemplify how to apply our proposed GTST-MFM method to model the system and to validate fault trees directly built by deductive method.

Quality assurance is a critical aspect in the production systems, affecting product quality and safety. Defects and failures of manufactured components will diminish overall product quality, which could vulnerably risk consumer safety. This study focuses on quality assurance analysis of train component manufacturing systems. According to the quality control data, the number of defects recorded was about 10-12, on average, for each wagon produced. The defect mainly occurred while making the underframes, car body, and even the small components. This led to the tardiness of product delivery for 1-2 months. This study aims to analyze non-conformance report data and identify the potential failure modes, potential effects, and root causes. To do so, we integrated systematically FMEA (Failure Mode and Effect Analysis) and FTA (Fault Tree Analysis). First, RPN (Risk Priority Number) score was calculated to determine risk priority. Second, Pareto analysis was performed to select defects that most contributing to overall failures, which were then analyzed using FTA to obtain root causes. The results show that 8 defects exceed the critical RPN score of 209. Materials and personnel are identified as two major contributor failure events from three selected defects. The recommendation for further improvements is provided based on various defect categories to prevent similar defects. The findings demonstrate that the combined use of FMEA and FTA is effective in identifying failures and root causes within complex and long production cycle systems.

Fault Tree Analysis (FTA) is a method that directly focuses on the modes of failures. The FTA is a graphical representation of the major faults or critical failures associated with a product, as well as the causes for the faults and potential countermeasures. The aim of this research paper is to calculate the probability of the top event – the failure of the process using FTA and propose a technique to prioritize factors for action design and reduce the likelihood of a top event failure based on manufacturers' requirements. We have constructed a qualitative fault tree to produce office components packed and sealed in blister packs using a KOCH KBS-PL machine. We defined the top event G – the production of office components, packed and sealed in blister packs on the machinery KOCH KBS-PL. Then we defined events leading to top events down to individual failure factors. Based on the links between the fault tree and the probability of failure, we performed a quantitative analysis to determine the probability of failure of individual events. We found out that the probability of failure of G is 5.04%. Subsequently, we identified which factors most significantly reduce the resulting probability of failure of factor G. These are the factors: E – feed rate, F – cooling, AL – incorrect setting and D – break. It has been proven that by controlling these 4 factors, we can reduce the probability of failure of top event G to 2.36%, provided that effective measures are taken. The final proposal meets the requirements of several manufacturers for a fast, efficient, and cost-effective solution. We have created a proposal that saves time, has minimal software and hardware requirements, and is easy to use. The efficiency and effectiveness of the proposal was that we identified the weakest points in the fault tree that most significantly cause the top event to fail. This prioritized the factors for the design of the measures.