Reliability Analysis Of Equipment Research Articles

Bayesian network approach for reliability analysis of mining trucks

Having a safe and efficient system for mineral transportation is a top priority for all mining operations. Trucks are the most widely used material transportation systems that are applied in both surface and underground mines. Any truck failure disrupts the mineral transportation process and consequently decreases the overall output. Therefore, the reliability analysis of such equipment plays a critical role in increasing the efficiency and productivity of a mining operation. This paper proposes a novel method for analyzing the reliability of a fleet of mining trucks based on the Bayesian Network modeling. Considering the reliability block diagram, the fault tree of trucks was developed according to the logical relationship between the units. Then, a dynamic Bayesian network was constructed according to the conditional probability analysis. Moreover, the relative contributions of each truck’s component to the occurrence of the fleet failure were studied by using critical analysis. The results of this paper show that the successful operation of the fleet of trucks is most sensitive to truck no. 5, which has the highest reliability level in all time intervals. The reliability of the fleet of trucks reaches 0.881 at 20 h, and the fuel injection system of the truck’s engine is the main leading cause of the trucks failure. A proper preventive maintenance strategy should be paid more attention to improve the reliability and availability of the engine system.

Reliability analysis of a plastic processing equipment: a case study supported by statistical software

The extrusion process of plastic transformation involves a series of variables and components which must be associated with the concept of reliability to achieve an expected performance in operational and quality terms. This paper describes the reliability framework of an extruder of a packaging company located in Brazil through the following mathematical representations: probability density function f(t), reliability curve R(t) and function rate of failure h(t). Through a statistical software the set of representations was able to develop the reliability framework of the machine, which can be used to support a FMEA analysis. Besides that, it was evidenced that in the current operating conditions of the machine, approximately 50% of the failure observations happen on the hour 100 of operating time. The main outcome is that it is recommended a systematic preventive maintenance based on 100h cycles. It is expected that this work may act as a guide for future implementation of improvement activities.

Discrete-Time Bayesian Networks Applied to Flexible Coping Strategies of Nuclear Power Plant Systems

The Fukushima Daiichi accident prompted the nuclear community to find a new solution to reduce the risk in nuclear power plants (NPPs) due to beyond-design-basis external events (BDBEEs). An implementation guide for diverse and flexible coping strategies (FLEX) has been presented by the Nuclear Energy Institute to manage the challenges of BDBEEs and enhance reactor safety. Due to the uniqueness of the FLEX systems, these systems can potentially carry dependencies among components not commonly modeled in NPPs. In this study, we investigate the effectiveness and applicability of both Bayesian networks (BNs) and discrete-time Bayesian networks in the reliability analysis of FLEX equipment. The study compares BNs with two other reliability assessment methods: fault tree and Markov chain. These methods are also shown to be capable of mapping into BNs to perform a reliability analysis of FLEX systems. A neutral dependency algorithm is used to simplify the conditional probability tables and reduce the complexity of the BNs. The results indicate that BNs are not only a powerful method for modeling FLEX strategies but are also effective techniques for inclusion of the dynamics of FLEX equipment in probabilistic risk analysis.

Reliability modeling and analysis of high voltage power equipment: a case study of Ajaokuta Steel Company Limited (ASCL)

Reliability modeling and analysis of high voltage power equipment: a case study of Ajaokuta Steel Company Limited (ASCL)

Random Vibration Fatigue Life Analysis of Airborne Electrical Control Box

To study the influence of random vibration on the fatigue life of airborne equipment, an aircraft electrical control box was selected as the research object. First, finite element software was used to model the dynamics of the airborne electrical control box to investigate its mode frequencies. The accuracy of finite element simulations was verified by performing mode experiments. Second, the mode superposition method was used to analyze the flight direction (X axis), side direction (Y axis), and altitude direction (Z axis) random vibration responses of the electrical control box. The analysis results were combined with the Miner linear cumulative damage criterion and the Gaussian-distribution Steinberg method to estimate the fatigue life of the electrical control box in the three directions. Finally, the calculation results were verified by performing the random vibration durability test on the electrical control box. The finite element mode analysis results show good agreement with the vibration experiment results, and the maximum error is 13.4%, indicating that the finite element model established in this paper is acceptable. The fatigue life of the electrical control box in the three axes meets the user requirements, and random vibration along the side direction (Y axis) has the greatest impact on the fatigue life, which is consistent with the results of the actual experimental data. The research method can be extended to predict the fatigue life of other airborne equipment and thus has practical significance for structural design and reliability analysis of airborne equipment.

F2G: A hybrid fault-function graphical model for reliability analysis of complex equipment with coupled faults

Reliability analysis plays a crucial role in revealing the failure causes and determining the improvement measures for reliability growth. However, reliability analysis of complex equipment with coupled faults still corresponds to a challenging task, due to unclear coupling mechanism and unsuitable analysis model. A down-top, deductive modeling method, named as fault-function graph (F2G), is proposed. First, the meta models are defined to normalize all the atomic faults, coupling relations and coupling forms in modeling. Next, an initial fault model is constructed based on typical fault-relations and coupling forms. Furthermore, the functional hierarchy of fault determined by IDEF0 is appended. Lastly, the rigorous modeling rules and computing processes are explained based on an actual case. As a graphical modeling method, it handles the coupling faults by integrating the system functional and fault information. Exploiting the advantages of conventional models, the coupling relations are quantified, and the false relations are detected based on functional constraints. Therefore, the proposed method can be used flexibly in the reliability modeling of coupled faults. Moreover, it provides a foundation for the comprehensive and dynamic reliability analysis and the failure mechanism mining of complex equipment, and it can be used in other engineering applications as well.

Reliability Analysis of Electric Automation Control Equipment in Hydropower Plant

Reliability Analysis of Electric Automation Control Equipment in Hydropower Plant

Reliability Analysis of Magnetic Resonance Imaging Equipment Based on Non-homogeneous Poisson Process

In order to evaluate the quality of different brands of magnetic resonance imaging system, optimize the quality of equipment repair and maintenance, and ensure the quality and safety of the equipment in clinical use. Meanwhile build the reliability evaluation model of magnetic resonance imaging equipment based on the large failure data collected by magnetic resonance repair system. In this paper, using the fault data of a certain brand of magnetic resonance in the past two years, applying the statistical judgment criterion, selecting the appropriate statistical distribution model, and finally fitting the equipment reliability evaluation model based on the non-homogeneous Poisson process, and then obtaining the magnetic resonance imaging equipment. Reliability evaluation indicators such as cumulative fault strength function, magnetic resonance imaging equipment fault density function, and mean time between failures. According to the calculated reliability index, on the one hand, it can evaluate the system reliability quality of a certain brand of magnetic resonance imaging equipment, and then evaluate the quality of different brands of magnetic resonance imaging equipment, on the other hand, it can help hospital equipment managers to carry out operational optimization, maintenance strategy development and safety management of magnetic resonance imaging equipment.

OKBM Afrikantov Experience in Developing Methods and Computer Codes for Reliability Analysis and Probabilistic Safety Analysis of Nuclear Installations

The history of the development and adoption of reliability analysis of equipment and systems as well as probabilistic safety analysis in the practice of design and operation of nuclear installations is presented. The basic characteristics of the developed software systems for performing probabilistic safety analysis of installations during the design process, risk monitoring during operation of NPP, reliability monitoring of ship installations, and nuclear power plants operating as intended as well as information about their adoption in operating facilities are presented. It is shown that digital technologies are being actively adopted in the analysis and monitoring of safety.

An Overview of the Reliability Analysis Methods of Tunneling Equipment

The absolute prevention of damage occurrence is not possible, thus reducing the probability of failure in a system and its impact is very important regarding the operation of a whole system. A failure in a system or in its subsystems makes negative results such as the stop in the production process, rising labor costs, and increasing the cost of maintenance. Reliability, in recent years, is mentioned as one of the most significant aspects of the quality of goods and services. In the past, reliability concerned sensitive and complex industries such as military, nuclear, and aerospace where the lack of their reliability could cause irreparable damage to the entire system. However, today it has become a universal concern. Tunneling equipment has grown in size and complexity and therefore, lack of reliability may cause massive costs to this equipment. Therefore, reliability determination in order to identify the components and subsystems with low reliability is essential. The aim of this study is to review the methods of tunneling equipment reliability analysis including statistical analysis, failure mode and effects analysis, Markov and fault tree methods. In addition, previous available research on the reliability analysis of tunneling equipment is presented.

Reliability Analysis of Dragline Using Equivalent Aging Model

Traditional models for reliability analysis of mining equipment are developed from time to failure data. However, inclusion of operational data and environmental stressors in reliability analysis makes models realistic and can predict the reliability as well as availability of equipment more precisely. It also allows us to understand the aging process of the equipment. The aging of equipment can be comprehended with the concept of the equivalent age that describes how much the equipment wear-out within a particular duration when it works under a specific environmental condition. Thus, equivalent age differs from its physical age. This study has used last 12-year operational data of a dragline deployed in a large opencast coal mine. Collected data have been grouped into four maintenance strategies. It is revealed from the results that production stress and maintenance strategy significantly affect the equivalent age of the dragline. Moreover, the effect of maintenance has been incorporated intrinsically in the equivalent age model to represent a gradual effect of a particular maintenance strategy on dragline aging. This research has studied the effect of a set of maintenance strategies and production stress on the reliability of a dragline using the concept of equivalent age. This concept will help the maintenance engineers in preparing a suitable maintenance plan for the draglines or any heavy earth moving machines in advance.

Reliability analysis of power equipment of traction rolling stock within the Eastern region

AnnotationOne of the most loaded structures, and at the same time, the weakest elements of the power equipment of traction rolling stock, is isolation. The analysis of the operation of power equipment of electric locomotives from the negative impact of climatic factors on it has been made. It was revealed that to ensure reliable and safe operation, a system of maintenance and repair of rolling stock is necessary, taking into account the zonal conditions of operational features. The necessity of creating adaptive systems to maintain optimal values for temperature and humidity conditions for the insulation structures of electric locomotives is shown.

FPGA-Based Stochastic Activity Networks for Online Reliability Monitoring

Stochastic activity network (SAN) is a flexible formalism that permits performing reliability and prognostics analysis of complex degrading systems. However, their use for the analysis of high-reliability equipment including fast evolving and degrading mechanisms requires long simulation times and large hardware resources. This paper presents, a field programmable gate array (FPGA)-based architecture that permits performing online Monte Carlo simulations of SAN models of high reliability systems. The synthesis is automated and the result preserves the structure of the models, permitting model inspection, and validation. The architecture runs without the aid of a central processing unit (CPU) and the simulation results are directly recorded into CPU-accessible random access memory (RAM). The design is validated on reliability monitors for an overheating detector and for degrading underground cables. The resource usage and simulation time are compared to the performance of software solutions that are run on parallel processors and large computer resources. Obtained results confirm that the proposed FPGA architecture can be employed for the accelerated runtime reliability analysis of equipment.

Reliability analysis of equipment for zero-failure of type-I censoring test with replacement

Reliability analysis of equipment for zero-failure of type-I censoring test with replacement

Reliability Analysis and Failure Prediction of Construction Equipment with Time Series Models

Reliability Analysis and Failure Prediction of Construction Equipment with Time Series Models

Reliability Analysis of Intermittently Operated Military Equipment

Reliability Analysis of Intermittently Operated Military Equipment

Reliability Test and Analysis of Electrical Automation Control Equipment

For a long time, reliability plays an extremely important role in electrical automation control equipment. To improve electrical automation control equipment’s reliability, the job should be promoted to a strategic height so as to assume and effectively control the factors affecting the reliability of the equipment, thus ensure the accuracy of reliability test. This paper, based on this, first is to implement the reliability influence factors analysis, and then introduces the main testing methods. By contrast, it finally comes to the conclusion that this article can provide certain reference for the research of related topics.

Reliability Test and Analysis of Electrical Automation Control Equipment

Improve the reliability of electrical automation control equipment is hot issues manufacturer and user have been focused on, therefore, the relevant measures must be taken to strengthen the reliability of the electrical automation control equipment. This paper discusses on the reliability test method and the status quo of electrical automation control equipment, and further discusses the measures to improve the reliability of the electrical automation control equipment and the choice of control equipment reliability test method of.

Reliability analysis of underground mining equipment using genetic algorithms

Purpose– While increased mechanization and automation make considerable contributions to mine productivity, unexpected equipment failures and imperfect planned or routine maintenance prohibit the maximum possible utilization of sophisticated mining equipment and require significant amount of extra capital investment. Traditional preventive/planned maintenance is usually scheduled at a fixed interval based on maintenance personnel's experience and it can result in decreasing reliability. This paper deals with reliability analysis and prediction for mining machinery. A software tool called GenRel is discussed with its theoretical background, applied algorithms and its current improvements. In GenRel, it is assumed that failures of mining equipment caused by an array of factors (e.g. age of equipment, operating environment) follow the biological evolution theory. GenRel then simulates the failure occurrences during a time period of interest based on Genetic Algorithms (GAs) combined with a number of statistical procedures. The paper also discusses a case study of two mine hoists. The purpose of this paper is to investigate whether or not GenRel can be applied for reliability analysis of mine hoists in real life.Design/methodology/approach– Statistical testing methods are applied to examine the similarity between the predicted data set with the real-life data set in the same time period. The data employed in this case study is compiled from two mine hoists from the Sudbury area in Ontario, Canada. Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation.Findings– The case studies shown in this paper demonstrate successful applications of a GAs-based software, GenRel, to analyze and predict dynamic reliability characteristics of two hoist systems. Two separate case studies in Mine A and Mine B at a time interval of three months both present acceptable prediction results at a given level of confidence, 5 percent.Practical implications– Potential applications of the reliability assessment results yielded from GenRel include reliability-centered maintenance planning and production simulation.Originality/value– Compared to conventional mathematical models, GAs offer several key advantages. To the best of the authors’ knowledge, there has not been a wide application of GAs in hoist reliability assessment and prediction. In addition, the authors bring discrete distribution functions to the software tool (GenRel) for the first time and significantly improve computing efficiency. The results of the case studies demonstrate successful application of GenRel in assessing and predicting hoist reliability, and this may lead to better preventative maintenance management in the industry.

The Gears System Reliability Analysis with Correlation among the Components of Gear Box in Self-Propelled Gun

Against the accurately solving of system reliability was inadequate, the Copula function was applied in system reliability analysis of weapon equipment, the paper established system reliability model which obtained the second shift single driving, and obtained the common relationship between travel and system reliability degree, it tested that Copula function was better to solve correlation problem in the system reliability model .It provided a method for system reliability analysis and reliability susceptive analysis.