Effects Of Component Failures Research Articles

Selective maintenance of multi-state series systems considering maintenance quality uncertainty and failure effects

In order to improve the lifetime and reliability of equipment operation stage, it is necessary to carry out maintenance for components. The typical selective maintenance model does not consider the maintenance quality uncertainty and the failure effects, which may make the decision-maker overestimates the reliability of completing the next task after system maintenance, resulting in incorrect maintenance decision and prone to serious consequences of failure. In this paper, the potential discrepancy between the target maintenance quality and the actual maintenance quality of the decision maker is considered. At the same time, a multi-state FMECA is proposed to measure the failure effects under different states. Finally, the selective maintenance model of the multi-state series systems is established and solved by the genetic algorithm. The results show that considering the effect of component failure and the uncertainty of maintenance quality has an influence on maintenance decision. The maintenance decision made in this way is more consistent with the engineering practice.

System reliability modeling and life cycle research considering component characteristics and correlation

The accuracy and rationality of the system life depends not only on the detailed grasp of the system operation information, but also on the structural relationship between the internal components of the system and the correlation between the characteristics of each component and the degradation of the components. This article explicitly considers the different characteristics of component failure, and adopts different random process personalized modeling for the failure modes of different components; on this basis, the failure correlation between the components that work together to realize the system function is considered, and the synergistic effect of component failure is integrated into the reliability degradation model of components. In terms of system failure criteria, starting from an economic point of view, the overall working cycle of the system is obtained by comparing the relationship between the replacement cycle of lossy parts and the remaining life of the stable parts. Finally, an example is given to show the effectiveness and practicability of the proposed method.

Effect of component failure on tour package evaluation

Effect of component failure on tour package evaluation

Dynamic Performance Evaluation of Photovoltaic Power Plant by Stochastic Hybrid Fault Tree Automaton Model

The contribution of renewable energies to the reduction of the impact of fossil fuels sources and especially energy supply in remote areas has occupied a role more and more important during last decades. The estimation of renewable power plants performances by means of deterministic models is usually limited by the innate variability of the energy resources. The accuracy of energy production forecasting results may be inadequate. An accurate feasibility analysis requires taking into account the randomness of the primary resource operations and the effect of component failures in the energy production process. This paper treats a novel approach to the estimation of energy production in a real photovoltaic power plant by means of dynamic reliability analysis based on Stochastic Hybrid Fault Tree Automaton (SHyFTA). The comparison between real data, deterministic model and SHyFTA model confirm how the latter better estimate energy production than deterministic model.

Optimisation of opportunistic maintenance of a multi-component system considering the effect of failures on quality and production schedule: A case study

For a manufacturing equipment, any unplanned breakdown during the production period results into a high production loss. To keep the manufacturing facilities in good condition, preventive maintenance is planned. However, be- cause of limited time and availability of resources, not all the system components can be or need to be repaired/replaced during a planned opportunity. Hence, the unplanned break- downs can also be considered as an opportunity to do the maintenance activities for other components to take the ad- vantage of economicdependencyin multi-component system. However, when the system is under maintenance, it is very conservative to take the decision of maintenance actions on the components because of limited available time and re- sources. For such situation, this paper consider an opportunis- tic maintenance model for a multi-component system to take maintenance decision with a constraint on available time and the system availability requirements. The maintenance deci- sions for each component involves one of the three actions namely, repair, replace or do nothing to achieve the target availability with minimum maintenance cost. The model also considers the effect of component failures on the quality of product being manufactured as well as the production sched- ule on the machine. The cost of rejections is considered in the total failure cost along with the maintenance and downtime costs. The production schedule delay factor is considered as a constraint for the maintenance decision to account for the effect on production schedule delay. The optimal solution for the model is obtained using three solution methodologies namely simulated annealing, genetic algorithm and sequence heuristics. Using a real-life example of high pressure die casting machine, the opportunistic maintenance approach is demonstrated and results are discussed.

Parameter Sizing for Fluid Power Circuits Using Taguchi Methods

This paper describes the application of Taguchi methods [1-3] to the parameter sizing stage of fluid power system design. Taguchi methods have become almost synonymous with robust design and are used to design systems that are tolerant to the effects of noise factors. Noise factors are defined as anything that causes changes in the functional characteristics or performance of the system that are not controllable. In the hydraulic circuit example used in this paper, these noise factors are assumed to be effects of component failure. The method is therefore being used to select design parameter values such that the resulting circuits exhibit some tolerance to the initial development of faults in the system, which will allow the system to continue to operate for a short period of time without catastrophic failure occurring.

Mathematical models for bridge reliability

System reliability of bridge structures is investigated. Three terms are used to describe the standard reliability: structure function, reliability network, and reliability function. A bridge structure is represented by a reliability network which makes it possible to formulate the reliability function of the system. The reliability function is used to evaluate the reliability of the system. Reliability network and the reliability function are formulated for various types of bridges. Effects of component failures on system reliability are illustrated with examples. Key words: bridges, mathematical models, redundancy, system reliability.

Transient behaviour of queueing networks

In most contemporary queueing network analysis, the assumption is made that a network is in a state of equilibrium. That is, the network's state space probabilities are assumed to be time independent. It is therefore important to be able to quantify precisely when this assumption is valid. Furthermore there are also situations in which it is desirable to model the transient behaviour of networks which occur in practice, such as computer and communication systems. For example, the immediate effects of component failure or instantaneous alteration of system status may be predicted.In this paper an iterative solution is derived to the time-dependent Kolmogorov equations of queueing networks, and is shown to be convergent. From the solution, modelling of transient situations becomes possible and the time periods during which the equilibrium assumption can and should not be made may be identified; for example in terms of a time constant which is easily computed to a first-order approximation.

Transient behaviour of queueing networks

In most contemporary queueing network analysis, the assumption is made that a network is in a state of equilibrium. That is, the network's state space probabilities are assumed to be time independent. It is therefore important to be able to quantify precisely when this assumption is valid. Furthermore there are also situations in which it is desirable to model the transient behaviour of networks which occur in practice, such as computer and communication systems. For example, the immediate effects of component failure or instantaneous alteration of system status may be predicted. In this paper an iterative solution is derived to the time-dependent Kolmogorov equations of queueing networks, and is shown to be convergent. From the solution, modelling of transient situations becomes possible and the time periods during which the equilibrium assumption can and should not be made may be identified; for example in terms of a time constant which is easily computed to a first-order approximation.