Top PDF DFTCalc: reliability centered maintenance via fault tree analysis (tool paper)

DFTCalc: reliability centered maintenance via fault tree analysis (tool paper)

DFTCalc: reliability centered maintenance via fault tree analysis (tool paper)

Technically, DFTCalc is realized via stochastic model checking of interactive Markov chains, yielding a flexible and efficient framework by exploiting state space generation via bisimulation minimisation. A first version of DFTCalc was reported in [1] concerning fault tree analysis only. This paper reports the extensions of DFTCalc with preventive and corrective maintenance models and their analysis. To handle the ad- ditional complexity, we have implemented context-dependent model-generation, which significantly reduces the state space. We show the application of DFTCalc on standard case studies from the literature, as well as industrial cases from railway engineering. Paper organization. Section 2 introduces fault trees and maintenance, Section 3 their analysis in DFTCalc, Section 4 the case studies, and Section 5 concludes the paper.
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Application of Reliability Centered Maintenance on Horizontal Boring Machine - A Case Study

Application of Reliability Centered Maintenance on Horizontal Boring Machine - A Case Study

the RCM effectiveness on the balancing system of horizontal boring machine in private sector Madhya Pradesh , by using tools s u c h a s FMEA (Failure Modes and Effects Analysis), FTA (Fault Tree Analysis), MTBF (Mean time between failure) and MTTR (Mean time to repair). The failure characteristics of system components (cylinder, Direction control valve and pump) have been compared in terms of RPN, Criticality number, MTBF and MTTR. Fault tree analysis performed on the balancing system enabled to explore the root causes of component failure with help of hydraulic balancing circuit. FMEA analysis provided RPN (Risk priority number) and criticality numbers which indicated higher failure risk for Direction control valve, whereas MTBF and MTTR values suggested pump has higher failure chance. By preparing a logic diagram for each of the components, the contribution o f each one for the
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Fault tree analysis and artificial neural network modelling for establishing a predictive ship machinery maintenance methodology

Fault tree analysis and artificial neural network modelling for establishing a predictive ship machinery maintenance methodology

Maintenance deals with systems that are subject to deterioration and failure with usage and age. For systems on board ships, it is extremely important to avoid failures during actual operation because it can be dangerous or disastrous in terms of performance, safety and economic losses. The performance of the vessel generally deteriorates with time as a result of fouling or degradation of machinery systems and components. Unwanted failures result in economic impact in form of higher maintenance costs and lower machine reliability and availability. With reduced manning levels and the ever increasing competition, ship maintenance has become one of the major challenges in the marine industry. Technological advances and high cost of ownership have resulted in considerable interest in advanced maintenance techniques. As a consequence, the maritime industry is seeking for increased reliability, maximum uptime and optimal operational efficiency, as well as ensuring safe and sustainable environmental performance in harsh environments.
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Reliability modelling of automated guided vehicles by fault tree analysis

Reliability modelling of automated guided vehicles by fault tree analysis

button, such as driving, operating, control and power supply units, are critical components; (2) The further FTA results disclose that among all identified key components, the AGV software control system, drive unit, attachments and power supply battery are most vulnerable components to failure because they are found having the largest failure probability at the end of whole mission; (3) The FTA calculation has suggested that the AGV is more likely to fail in the completion of the phase ‘dispatch to station’ and the phase ‘travelling to storage’ because these two phases show the largest phase unreliability values. But it is worth to note that such a judgement is only based on the assumptions given in Section 3. In reality, the judgement result would be different, depending on the real reliability data collected from the AGVs; (4) Research has shown that the AGV being inspected is overall a very reliable material distribution vehicle in the warehouse. But Fig.5 has indicated that the reliability of the AGV will degenerate if it completes more missions without maintenance; (5) Through this research, it can be concluded that the proposed FMECA-FTA approach is indeed an effective method for assessing and evaluating the safety and reliability issues in AGVs.
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Reliability Analysis of Automatic Transmission Based on T S Fuzzy Fault Tree

Reliability Analysis of Automatic Transmission Based on T S Fuzzy Fault Tree

In order to solve the lack of automatic transmission slippage fault data, the uncertainty of the link between the source of the fault and the degree of fail- ure, the lack of applicability of the traditional Boolean logic gate, the T-S model and fuzzy theory and the revision of the confidence index are pro- posed. The expert survey method was combined and the analysis method was introduced into the fault tree. The T-S model is introduced into the typical fault analysis, using the fuzzy possibility to describe the failure probability of the component. The connection between events is described with the T-S gate. The fault degree of the component is described by the fuzzy number, the model simulation is used to simulate the fault analysis, and the contribution or importance of the top event to the failure of the component is obtained. The fuzzy possibility and fault diagnosis of the top event are calculated. Without knowing the fault mechanism accurately, we can find the weak link of the system, and provide reference for automatic transmission slip fault di- agnosis and maintenance.
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Fault tree analysis and artificial neural network modelling for establishing a predictive ship machinery maintenance methodology

Fault tree analysis and artificial neural network modelling for establishing a predictive ship machinery maintenance methodology

As part of the above, this paper focuses in combining a Fault Tree model and then an Artificial Neural Network (ANN) for forecasting selected machinery parameters. Fault Tree Analysis (FTA) is a top-down approach which uses failure rates, mean time between failures and minimal cut sets to evaluate the reliability and availability of the examined system [4]. FTA can be applied both in a qualitative and quantitative way. The objective of a Fault Tree is to evaluate the probability of occurrence of the top event. Moreover, Fault Trees are also used to display the causes and consequences of events, identify system critical components and evaluate changes in design amongst other things. Fault Tree diagrams provide important information regarding the likelihood of a failure occurring and the means by which this failure could occur. They can be constructed at any point of a design stage and the FTA results can help improve system safety.
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Reliability Modelling of Automated Guided Vehicles by the Use of Failure Modes Effects and Criticality Analysis, and Fault Tree Analysis

Reliability Modelling of Automated Guided Vehicles by the Use of Failure Modes Effects and Criticality Analysis, and Fault Tree Analysis

degree of AGVs can be maximised at the same time [3]; Wu and Zhou created a simulation model to avoid collisions, deadlock, blocking and minimise the route distance as well with a coloured resource-oriented Petri Net [4]. However, little effort has been made to investigate the safety and reliability issues of the AGV components/subassemblies and their probability of success in completing a prescribed mission. Although Fazlollahtabar recently created a model to maximise the total reliability of the AGVs and minimise the repair cost of AGV systems [5], they considered the AGV as a whole. Hence, fundamental questions, such as ‘How could AGVs fail?’ and ‘What are the possibilities of their failure?’, have not been answered.To answer these questions, Duran and Zalewski tried to identify the basic failure modes of the light detection and ranging (LIDAR) system and the camera-based computer vision system (CV) on AGVs in 2013 by the approach of Fault Tree Analysis (FTA) and Bayesian Belief Networks (BBN) [6]. In that work, human injury, property damage and vehicle damage were defined as the top events in the fault tree. However, the research did not cover all components and subassemblies in AGVs. A complete investigation of the safety and reliability issues of all AGV components and subassemblies is important not only to ensure the high reliability and availability of AGVs and their success of delivering prescribed tasks, but also to optimise their maintenance strategies. Research is conducted in this paper to identify the critical risks of all AGV components and the crucial mission phases in an AGV operation. Failure Modes Effects and Criticality Analysis (FMECA) and Fault Tree Analysis (FTA) will be adopted to achieve this. Hence, the contribution of this paper is in developing an efficient approach to investigate the reliability of AGVs taking into account the profiles of the mission undertaken.
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Fault Tree Analysis in the Reliability of Heavy Fuel Oil Supply

Fault Tree Analysis in the Reliability of Heavy Fuel Oil Supply

It has to be emphasized that the analysis of engine faults that have occurred in two years, using RCM (Reliability Centred Maintenance) can be found and are dominant in the heavy- fuel-oil system (Bukša et al., 2008; Mokashi et al., 2002). Due to the reason mentioned, for this study a system of heavy-fuel-oil two stroke marine diesel engine MAN B&W 5L90MC, has been chosen. A simulation has been conducted on the Full Mission Engine Room simulator Kongsberg Norcontrol. The main engine is low-speed 5-cylinder confi guration, two-stroke, turbocharged, reversible diesel engine. The main engine specifi cations: cylinder bore 900 mm; piston stroke 2,900 mm; number of cylinders 5; number of air coolers 2; number of turbo chargers 2; corresponding engine speed 74 rpm; mean indicated pressure 13.0 bar; scavenge air pressure 2.1 bar; turbine speed 8,000 rpm; specifi c fuel oil consumption 168 g/kWh.
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Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains.

Time-dependent reliability analysis of wind turbines considering load-sharing using fault tree analysis and Markov chains.

Due to the high failure rates and the high cost of operation and maintenance of wind turbines, not only manufacturers but also service providers try many ways to improve the reliability of some critical components and subsystems. In reality, redundancy design is commonly used to improve the reliability of critical components and subsystems. The load dependencies and failure dependencies among redundancy components and subsystems are crucial to the reliability assessment of wind turbines. However, the redundancy components are treated as a parallel system, and the load correlations among them are ignored in much literature, which may lead to the wrong system’s reliability and much higher costs. For this reason, this article explores the influences of load-sharing on system reliability. The whole system’s reliability is quantitatively evaluated using fault tree analysis and the Markov chain method. Following this, the optimisation of the redundancy allocation problem considering the load-sharing is conducted to maximise the system reliability and reduce the total cost of the system subjecting to the available system cost and space. The results produced by this methodology can show a realistic reliability assessment of the whole wind turbine from a quantitative point of view. The realistic reliability assessment can help to design a cost-effective and more reliable system and significantly reduce the cost of wind turbines. Keywords
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Application of Waspas in Ehancing Reliability Centered Maintenance for Ship System Maintenance

Application of Waspas in Ehancing Reliability Centered Maintenance for Ship System Maintenance

Another example, is the RCM logic tree used for selection of the maintenance strategy which has been criticized as being a very time consuming exercise (Waeyenbergh and Pintelon, 2004). The technique also lacks the ability to rank maintenance strategy alternatives, thereby making the decision process difficult. Although alternative approaches have been reported in the literature, the developed techniques also have one challenge or another. For example, Lazakis et al. (2012) applied an integrated fuzzy logic set theory and TOPSIS. The practical application of the fuzzy logic technique however is still doubt because of the computational complexity it brings into the decision making process (Zammori and Gabbrielli, 2012). Goossens and Basten (2015) used AHP in a solving maintenance strategy selection problem for naval ship systems. However, formation and analysis of numerous pairwise judgments from experts make the decision process difficult.
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RELIABILITY ASSESSMENT OF POWER EQUIPMENT IN A DISTRIBUTION SUBSTATION USING FAULT TREE ANALYSIS

RELIABILITY ASSESSMENT OF POWER EQUIPMENT IN A DISTRIBUTION SUBSTATION USING FAULT TREE ANALYSIS

Due to lack of efficiency in the power sector in Nigeria, the Nigerian Electricity Supply Industry (NESI) was unbundled into eighteen companies comprising of 6 generating companies (GENCOs), 1 transmission company (TRANSYSCO) and 11 distribution companies (DISCOs). The intention of this metamorphosis was to ensure improved system reliability, but this is very difficult to achieve because of the poor system maintainability that has been occurring for a very long time. The issue of maintenance of electric power equipment is of paramount national interest [2].
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Reliability Analysis of Vertical Broaching Machine by Fault Tree Analysis (FTA) Method

Reliability Analysis of Vertical Broaching Machine by Fault Tree Analysis (FTA) Method

Reliability Analysis by Fault Tree Analysis (FTA) method plays crucial role in design process. FTA is a graphical representation of major failure occurs in a machine, their causes of failures and potential countermeasures. This paper deals with a reliability analysis of vertical broaching machine by FTA method. Qualitative and quantitative analysis helps to identify the critical design parameters and maintenance suggestions.

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Bayes Networks and Fault Tree Analysis Application in Reliability Estimation (Case Study: Automatic Water Sprinkler System)

Bayes Networks and Fault Tree Analysis Application in Reliability Estimation (Case Study: Automatic Water Sprinkler System)

In this paper, the application of Bayes networks and fault tree analysis in reliability estimation were investigated. The lowest reliability is related to the diesel generator. However, it should be noted that the diesel generator as a stand-by component, will enter the circuit in the event of a power failure in the system to supply the power required by the pumps and the warning system. Therefore, it is recommended to develop a detailed operation and maintenance program along with periodic inspections. Furthermore, the overall reliability of the system can be increased by adding two or more operators for manual start-up and notifying the fire department in parallel. Certainly, extinguishing the fire in the shortest time and without a system failure can be effective in reducing the severity of outcomes and ultimately reducing the risk priority number and risk level. The 33% of the failures reported due to being deactivate, inoperative, and lack of effective maintenance. Also Human interference, component faults and freezing of the system account for 20 percent of the causes. Frank (2013).
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The Synthesis of Human-Error Analysis Using the Cognitive Reliability and Error Analysis Method and Fault-Tree Analysis

The Synthesis of Human-Error Analysis Using the Cognitive Reliability and Error Analysis Method and Fault-Tree Analysis

The basic goal of this work is the quantification of technical (mechanical) and human error during the continuous operation of a rectification system that causes instantaneous and continuous releases of a fluid mixture. Both types of leaks are unacceptable from the viewpoint of the economy of the process and ecological safety parameters; therefore, not only the probability of failure needs to be assessed but also the important parameters influencing the failures. A quantitative assessment of a particular failure mode also forms the basis for the mitigation of the factors leading to this failure: first the parameters leading to the most probable failure mode need to be investigated, followed by the second most probable, etc. given that the damage to life, people, and property is similar. This methodology enables one to establish which parts of the machinery are most likely to fail and therefore schedule preventive maintenance; and which areas should be addressed when training people involved in the operation of the rectification system. At the same time it should be noted that the effects of education and training are limited and that the probability of human error cannot be lowered indefinitely [11].
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Determination of Maintenance Task on Rotary Equipment Using Reliability Centered Maintenance II Method

Determination of Maintenance Task on Rotary Equipment Using Reliability Centered Maintenance II Method

After finishing step in the RCM process, it’s time for task selection. The RCM method uses a logic decision tree, in the form of a flow chart. For each step in the process, a logical question must be answered, yes or no. After ending the selection process, the RCM method will give some proposed maintenance tasks. After that, it’s up to the analyst to compare the result from the RCM task selection process with today’s maintenance, failure and operational history. From that analysis, some new solutions of proactive maintenance tasks will come out. No scheduled maintenance the no scheduled maintenance is most used when the failure is evident, and does not affect safety or the
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PROPOSAL OF CONTENT MAINTENANCE OF CNC MACHINE USING METHODS RELIABILITY CENTERED MAINTENANCE

PROPOSAL OF CONTENT MAINTENANCE OF CNC MACHINE USING METHODS RELIABILITY CENTERED MAINTENANCE

The paper presents the results of examination of the proposal content and the scope of maintenance of the machining center MCFV 1050 Basic through the RCM II - Reli- ability Centered Maintenance method. Based on the analysis of apriori and parametric reliability methods, it was decided to use the FMEA for analyze the causes and con- sequences of failure states using the software IQ-RM PRO 6. The structure, defined functions and fault functions were developed.The analyzed types of failure and types of maintenance tasks were processed in the RCM II Information and Decision Making Reports.The result is 10 proposed maintenance tasks performed in time intervals, 8 maintenance tasks performed as needed and 1 maintenance task performed after the specified performance.The end of the article discusses the suitability of the applied methods for the maintenance proposal and of the defined recommendations.
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Reliability Analysis Using Fault Tree Analysis: A Review - Volume 4 Number 3 (Jun. 2013) - IJCEA

Reliability Analysis Using Fault Tree Analysis: A Review - Volume 4 Number 3 (Jun. 2013) - IJCEA

In conventional FTA the ambiguous and imprecise events such as human errors are not handled effectively therefore to overcome this problem a hybrid approach is developed using FTA with Fuzzy logic to evaluate the probabilities of such events. Instead of directly using the failure rates, fuzzy failure rates are used for the characterization of imprecise events such as human errors [5], [23], [24]. The failure rates are defined in linguistic ranges as defined by the fuzzy set theory. It is an effective method where both linguistic and probabilistic evaluation is necessary. The method is applied on a human-robot system to illustrate the hybrid technique. This hybrid method is one of the most widely applied methods to overcome the un-adequacy of data and its applications can be observed in different areas of researches. Another example of FTA used with fuzzy logic is the undesired event caused in a spread mooring system used to hold ships and boats during (un)loading conditions [25]. Sensitivity analysis is also made by fuzzy weighted index (FWI) to estimate the impact of basic events on the top events. This method is also observed to be applied in oil and gas sector where fuzzy fault tree is applied where the probability of fire and explosion is determined qualitatively and quantitatively with minimum path set using Boolean algebra [4].
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PTA as an approach to fault tree analysis

PTA as an approach to fault tree analysis

There are several papers related to this research. A paper by Wu, Lemmon & Lin, 2017, explores PTA as an alterna- tive modelling formalism to Monte Carlo simulation and multi-state Markov chains [11]. For the research, a PTA model was created for a network communication protocol. This model was then analysed using probabilistic model checking. With the main focus on the stability condition of the protocol. Similar to this paper, it explores PTA as an alternative to other modelling formalisms. However, it does not provide a comparison between different modelling formalisms, but focuses only on a PTA model. A paper by Norman, Parker & Zou, 2017, proposes an extension of PTA, namely, partially observable probabilistic systems (POPTAs) [8]. These allow local states to be partially visible to an observer or controller. Furthermore, auto- mated techniques are presented for the verification of par- tially observable probabilistic systems. Partially observ- able Markov decision processes are (POMDPs) are used as well. In this paper POMDPs are used for discrete-time model and use POPTAs for dense time models. Exper- imental results are provided of POPTAs and POMDPs, which are analysed to compare aspects such as, the states generated and time used for each experiment. In the paper by Sproston, 2017, clock-dependent probabilistic timed automata (cdPTA) are introduced [10]. This variant on PTA uses clock bounds to determine when a transition can be made. The paper shows that the reachability prob- lem [1, 3, 6] is undecidable for cdPTA with at least three clocks. The paper by Jurdzi´ nski, Laroussinie & Spros- ton, 2007, [5] already showed that this was undecidable for PTA using one or two clocks. The papers by Norma et al., Sproston and Jurdzi´ nski et al. are relevant to this research as these papers involve the analysis of PTA with clocks, which is also done in this paper. However, no comparisons of CTMC and PTA regarding availability, reliability and verification time have been found.
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Maintenance Strategy Development (MSD) Using Reliability Centered Maintenance In A Power Plant : A Holistic Study

Maintenance Strategy Development (MSD) Using Reliability Centered Maintenance In A Power Plant : A Holistic Study

Despite this previous commonly held view, the results seemed to tell a different story. In far too many instances, PM seemed to have no beneficial effects. Indeed, in many cases, PM actually made things worse by providing more opportunity for maintenance-induced failures.

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Fault-Tree Model for Bridge Collapse Risk Analysis

Fault-Tree Model for Bridge Collapse Risk Analysis

Edwards Bridge fault-tree (Figure C-9) are single-event cut sets; therefore, each basic event is considered equally influential to the top event, bridge failure. The minimal cut [r]

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