Mean Time To Failure Research Articles

Improving Heat Transfer from Peltier Devices Used in an Atmospheric Water Generation

Present Atmospheric Water Generation (AWG) systems are useful for providing water in areas with limited water supplies. Many industrial AWG systems use VCR (vapor-compression refrigeration) to achieve a large amount of cooling to extract liquid water out of the air. These systems require large amounts of energy to operate, usually in the form of diesel or AC-powered generators. The systems also have many moving parts that require maintenance and use refrigerants that can leak and cause problems with the environment. An alternative AWG solution is to use DC-powered Peltier devices (thermoelectric coolers) to reduce the temperature of condensation plates to extract water from the air. This solution eliminates the issues with traditional industrial AWG systems since the Peltier devices are solid-state, have very long mean-time between failure (MTBF) performance, and can be powered by solar panels that eliminate the need to burn hydrocarbon-based fuels or have access to a reliable power grid. Also eliminated is the need to use chlorofluorocarbon (CFC) or hydrochlorofluorocarbons (HCFC) refrigerants that have been shown to deplete the ozone layer. This paper will present methods to improve the efficiency of the thermoelectric coolers by more efficiently extracting heat from the hot side of the device. This efficiency will be quantified by evaluating the coefficient of performance (COP) of the thermoelectric cooler under the various operating conditions. Different combinations of conductive heat transfer using aluminium heatsinks, convection heat transfer using forced airflow, and phase change heat transfer using copper heat pipes filled with distilled water will be investigated and evaluated.

Analysis of Relay Node Failure in Heterogeneous Wireless Sensor Networks

Introduction: Fault tolerance is an important issue for assuring data reliability, energy saving and prolonging the lifetime of wireless sensor networks. Since, sensor node, relay node, etc. are prone to failure, there is a need an effective fault tolerance mechanism. Methods: Relay nodes are used as cluster heads and the concept of two disjoint paths is employed for proving fault tolerance against link failure. To evaluate the fault tolerance level, mean time to failure and subsequently, failure rate are calculated, that reflect the reliability of the network. Results: The results show that as the area size of the network increases, the average fault tolerance level of the network becomes constant. Furthermore, when the mean time to failure of the network decreases, then the failure rate increases. It means the overall reliability of the network with a smaller network size is more than the larger network size. Discussion: This paper presents a detailed analysis of relay nodes failure under distinct network configurations in heterogeneous wireless sensor networks. Conclusion: This analysis helps the network designers to decide the quantity of deployment of relay nodes with respect to fault tolerance level. It may also help to prevent relay nodes failure by taking appropriate actions so as to increase the fault tolerance level of the network as well as network reliability.

Stochastic Diffusion Modeling of Degradation Data

Accelerated degradation tests (ADTs) can provide timely relia bility information of product. Hence ADTs have been widely used to assess the lifetime distribution of highly reliable products. In order to properly predict the lifetime distribution, modeling the product’s degradation path plays a key role in a degradation analysis. In this paper, we use a stochastic diffusion process to describe the product’s degradation path and a recursive formula for the product’s lifetime distribution can be obtained by using the first passage time (FPT) of its degradation path. In addition, two approxi mate formulas for the product’s mean-time-to-failure (MTTF) and median life (B50) are given. Finally, we extend the proposed method to the case of ADT and a real LED data is used to illustrate the proposed procedure. The results demonstrate that the proposed method has a good performance for the LED lifetime prediction.

Research on Reliability of Grid Connected Photovoltaic Renewable Generation System

Renewable energy sources are increasingly being implemented in power systems to curb global warming and improve generation adequacy. These renewable sources include Hydro, wind, tidal, and solar power systems. Since Pakistan experiences decent solar irradiation throughout the year, the most viable renewable energy option is photovoltaic generation. Before solar systems are implemented, the proposed design is first simulated using design software such as MATLAB-Simulink to correct and adjust parameters to attain the DC voltage and current through the irradiation and environment temperature. Reliability studies and analysis are performed on the simulated systems to ascertain the success and long life before the system components’ failure. In this thesis, the grid-connected PV system’s reliability model established based on the reliability block diagram method using the MIL-HDBK-217F handbook. The handbook provides the methodology of calculating failure rates of specific physical electronics operations. The mean time to failure (MTTF) and Mean time to repair (MTTR) of the system is calculated from the overall system reliability. Photovoltaic power output varies greatly, and it is dependent on solar irradiation and temperature, resulting in intermittent and variable energy production. All of these considerations have a significant effect on the entire system adequacy of the power generation system. This study uses a probabilistic analytical methodology to develop comprehensive reliability models of grid-connected Photovoltaic generation systems.

Effect of Preventive Maintenance on Machine Reliability in a Beverage Packaging Plant

This paper investigates the effect of preventive maintenance on the reliabilities of devices in a bottling plant. Six months of real-time maintenance data were analyzed quantitatively. Based on the breakdown events obtained for each machine, mean time between failure (MTBF), mean time to repair (MTTR), and failure rate (λ) values for individual equipment are calculated. The bottle packer, empty bottle inspector (EBI), and palletizer are identified as the plant's critical machines. A breakdown analysis (BDA) is then performed on the bottle packer and from the failure mode of all the reoccurring problems affecting this machine as a result of ineffective PM. An autonomous maintenance (AM) team is set up as part of establishing an effective PM program to improve the reliabilities of the critical machines that were continually falling. A significant reduction in machine breakdowns is observed after two months of rolling out the AM program. As a result, the reliability of bottle packer increased from 55.30% to 70.80%, while EBI and palletizer increased from 89.20% and 87.20% to 92% and 90.50%, respectively.

Enhancing Reliability and Availability through Redundancy in Vehicular Clouds

The past eight years have seen the emergence of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vehicular clouds</i> as a topic of research in its own right. Vehicular clouds were inspired by the insight that present-day vehicles feature an impressive array of on-board compute, storage and sensing capabilities. These on-board capabilities are a vast untapped resource that, at the moment, is wasted. One of the defining ways in which vehicular clouds differ from conventional clouds is resource volatility. As vehicles enter and leave the cloud, new compute resources become available while others depart, creating a volatile environment where the tasks of enhancing reliability and availability become very challenging. It is intuitively clear that the longer and more predictable the vehicle residency times in the cloud are, the easier it is to ensure reliability and system availability. In this work we look at vehicular clouds with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">short and unpredictable</i> vehicular residency times. We propose to enhance the reliability and availability of these types of vehicular clouds through a family of redundancy-based job assignment strategies that attempt to mitigate the effect of resource volatility. We offer a theoretical prediction of the Mean Time To Failure (MTTF) of these strategies. We also show how to fine-tune the granularity of the redundancy in order to meet QoS requirements specified in terms of a minimum MTTF for a given user job. Extensive simulations, using vehicle residency data derived from shopping mall statistics, have confirmed the accuracy of our analytical predictions.

Semi-automated Estimation of Reliability Measures from MaintenanceWork Order Records

Determining mean-time-between-failure (MTBF) estimation for in-service assets is an essential process. Statistical distributions of end-of-life values are used to assess asset reliability performance and the effectiveness of maintenance strategy. However, identifying the end-of-life event for each instance of functional failure is an arduous, manual process dependent on structured and unstructured fields in the maintenance management system and rules used by individual reliability engineers. We emulate the process of end-of-life event detection using a natural language processing pipeline followed by statistical parameter estimation to produce MTBF values for in-service assets from maintenance work order data. Using this pipeline we test how alternate mappings of words in unstructured text and the use, or not, of structured data can impact the identification of end-of-life events. We demonstrate the pipeline on data sets from two industrial users with 14,508 and 89,259 maintenance work orders, respectively. We find that resulting MTBF estimates can vary from, for example, 97 to 226 days for a single asset depending on the mappings and rules used. The main contributions of this paper are a) a demonstration of the impact of undocumented decisions made by reliability engineers in identifying end-of-life events on MTBF estimates, and b) an end to end pipeline for MTBF estimation from raw maintenance work order texts. In addition, we provide open-source code for the pipeline that can be used by asset owning organisations to semi-automate the MTBF estimation process in a manner that is fast and scalable, and ensures the rules used for end of life determination are documented and hence the process is transparent and repeatable.

A goodness of fit test for mean time to failure function in age replacement

Mean time to failure (MTTF) function plays an important role in connection with age replacement policy. In this paper, a goodness of fit test is proposed for MTTF function utilizing a weighted integral as a measure of deviation. The test statistic is shown to be asymptotically normal and the consistency of the test is also established. The proposed test is compared with some parametric tests of exponentiality in the sense of Pitman Asymptotic Relative Efficiency (PARE). The performance of the test is assessed by means of a simulation study. Finally, the test is applied to a real-life data set for illustrative purposes and the results are shown to be in accordance with those obtained by applying the one-sample Kolmogorov-Smirnov test.

Implementasi RCM pada mesin diesel Deutz 20 kVA

The aspect that most influences the functioning of this telecommunications service is the aspect of maintaining the equipment or assets supporting the telecommunications service. For this reason, companies must periodically measure the performance of their maintenance so that telecommunications services continue to function properly. From the data, the frequency of damage to the diesel generator engine from 2017 to 2020 is very high. In the period 2017 to 2020 there were a total of 90 times the damage, and the biggest contributor to the damage was in the 20kVA Deutz diesel engine. The purpose of this research is to know how the maintenance conditions are and to know the level of effectiveness and to know the right recommendations to increase the effectiveness of the diesel generator engine. The research method used is RCM (Reliability Centered maintanance) which is a technique used to develop scheduled preventive maintenance. Research results obtained, the component whose frequency is often damaged in the Deutz generator diesel engine is the Alternator. This selection is based on the highest number of damage frequencies and the longest downtime for approximately 3 years. Calculation of the Alternator's Mean Time to Failure (MTTF) value is 25305 hours, which means that the Alternator component will experience damage again after operating for 25305 hours. While the Mean Time to Repair (MTTR) value of the Alternator is 22.54 hours, which means that the average time to repair the Alternator component is 22.54 hours. From the calculation of the Reliability Value, the alternator is said to still have a good function because the average value interval is still in the range 0 1), the appropriate types of maintenance for the Alternator component are Preventive and Time Based Maintenance. Keywords : Reliability Centered Maintenance, Critical Components, Maintenance .

Unbalanced currents effect on the thermal characteristic and reliability of parallel connected power switches

In many industrial applications, parallel connection of power semiconductor switches is widely used to achieve higher power levels and fault-tolerant operation. But there is a current imbalance between parallel connected switches in practical applications. In this research, the impact of unbalanced currents on the junction temperature and the reliability of parallel connected switches are quantified and analyzed. Markov based reliability model is developed for quantitative assessment of reliability for parallel switches under different current sharing. The Mean Time to Failure (MTTF) is calculated for different conditions to be used as reliability metric for comparison of various conditions. A sensitivity analysis is also presented to show the effect of parameter variation on the junction temperatures of devices and reliability of the system. At last, a downscaled setup has been built up and tested. Experimental results verify the theoretical analysis and confirm procedure. Also, junction temperatures of power semiconductor devices are measured using thermal camera.

On classes of life distributions based on the mean time to failure function

AbstractThe performance and effectiveness of an age replacement policy can be assessed by its mean time to failure (MTTF) function. We develop shock model theory in different scenarios for classes of life distributions based on the MTTF function where the probabilities $\bar{P}_k$ of surviving the first k shocks are assumed to have discrete DMTTF, IMTTF and IDMTTF properties. The cumulative damage model of A-Hameed and Proschan [1] is studied in this context and analogous results are established. Weak convergence and moment convergence issues within the IDMTTF class of life distributions are explored. The preservation of the IDMTTF property under some basic reliability operations is also investigated. Finally we show that the intersection of IDMRL and IDMTTF classes contains the BFR family and establish results outlining the positions of various non-monotonic ageing classes in the hierarchy.

Performance Analysis of Tyre Manufacturing System in the SMEs Using RAMD Approach

In the recent trends, production plants in the automobile industries all over the world are facing a lot of challenges to achieve better productivity and customer satisfaction due to increasing the passenger’s necessity and demand for transportation. In this direction, the belt, tyre, and tube manufacturing plants act as vital roles in the day-to-day life of the automobile industries. Tyre production plant comprises five major units, namely, raw material selection, preparation, tyre components, finishing, and inspection. The main purpose of this research is to implement the new method to predict the most critical subsystems in the tyre manufacturing system of the rubber industry. As mathematically, any one maintenance parameter among reliability, availability, maintainability, and dependability (RAMD) parameters is evaluated to identify the critical subsystems and their effect on the effectiveness of the tyre production system. In this research, the effect of variation in maintenance indices, RAMD, is measured to identify the critical subsystem of the tyre production system based on the mathematical modeling Markov birth-death approach (MBDA), and the equations of the subsystems are derived by using the Chapman–Kolmogorov method. Besides, it also calculates the performance of certain maintenance parameters concerning time such as mean time between failures (MTBF), mean time to repair (MTTR), and dependability ratio for each subsystem of the tyre production system. Finally, RAMD analysis of the tyre production systems has been executed for predicting the most critical subsystem by changing the rates of failure and repair of individual subsystems with the utilization of MATLAB software. RAMD analysis reveals that the subsystem bias cutting is most critical with the minimum availability of 0.8387, dependability 5.19, dependability ratio 0.8701, and maximum MTTR 38.46 hours of the subsystem. In this implementation of the proposed method, a real-time case study of the industrial repairable system of tyre manufacturing system has been taken for evaluating RAMD indices of the production plant of rubber industry cited in the southern region of Tamil Nadu, India.

Operation strategy optimization for on-orbit satellite subsystems considering multiple active switching

To improve the reliability of satellites, there are many standby configurations in the key subsystems. Concerning the on-orbit operation of standby systems, the standby units usually switch to the operating state after the active units fail. However, a periodic switching strategy differing from this common strategy is employed for the gyroscope warm standby system of satellite in engineering. For this problem, a multiple active switching policy for standby units is considered, and the on-orbit operation strategy optimization problem is studied. First, the multiple active switching process of the gyroscope warm standby system and the virtual age theory are described. Second, under the imperfect and non-periodic multiple active switching strategy, the reliability function and mean time to failure (MTTF) of the warm standby system are derived based on the binary decision diagram (BDD) with units following arbitrary lifetime distributions. Furthermore, an operation optimization model is proposed by maximizing the MTTF of the warm standby system to obtain the optimal switching numbers and corresponding time points. Finally, a numerical example of the gyroscope warm standby system under the Weibull distribution is presented to show the application of the model, and a sensitivity analysis is carried out to identify the useful conclusions.

A Quasi-Normal Distribution and its Application in Parameter Estimation on Heavily Censored Data

Parameter estimation on heavily censored data is a challenging issue. This paper addresses this issue using a two-step single-parameter maximum likelihood method to estimate mean time to failure (MTTF) and Weibull shape parameter (WSP). The first step fits the data to three one-parameter auxiliary models, which are special cases of a two-parameter quasi-normal distribution with nonnegative support, to obtain three estimates of the MTTF. The second step estimates the WSP through fixing each of the MTTF estimates. The best estimates are selected from three pairs of estimates based on appropriate rules. A simple numerical method is also proposed to construct the confidence intervals of the estimated MTTF and WSP. The auxiliary models are derived, the model selection rules are specified, and a numerical experiment is carried out to illustrate the accuracy of the proposed method.

Resilience-Driven Quantitative Analysis of Vehicle Platooning Service

Vehicle platooning can be applied to cooperative downloading and uploading (CDU) services through the cooperation between lead vehicle and non-lead vehicles. CDU service can be completed cooperatively by containers constructed in vehicles of the vehicle platooning system. Containers in vehicles may suffer from potential attacks which can lead to resource degradation and further cause the decrease in the dependability and security of CDU service. Failover technique can be deployed in an in-vehicle system and then performs protective operation for mitigating the impact of resources degradation and guaranteeing service resilience. This paper aims to quantitatively analyze the availability, reliability and security of CDU service in the vehicle platooning system deploying failover technique. We construct an analytical model to describe the interaction between resources degradation and rejuvenation behaviors of the vehicle platooning system. Then we derive the formulas of availability, Mean Time to Failure (MTTF) for evaluating reliability and Mean Security Capacity to Failure (MSCF) for evaluating security. Simulation and analytical experiments are applied to demonstrate the approximate accuracy of our model and investigate the impact of system parameters on metrics, respectively, which helps service providers make decisions on how to organize vehicles to perform CDU service and how to set system parameter values for maximizing their benefits.

Reliability Analysis on Water Pumps in Water Supply System in Johor

The utilization of water pumps in supplying water facilities to consumer should be given priority in terms of operating performance and availability. In light of that, reliability assessments on water pumps were carried out through Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR) and availability. Then, the water pumps’ brands were compared using Mean Cumulative Function (MCF) plot and suggestion strategies through Failure Modes, Effects and Criticality Analysis (FMECA) approach were conducted. There were two types of old and new water pumps which are raw water pump (RWP) and treated water pump (TWP). The name of the brand of old and new RWP and TWP are Brand A, Brand C, and Brand B. Throughout the study, the finding shows that old RWP and new TWP are the most reliable water pumps based on the computation. Besides, Brand A and Brand C were the best brands among others water pumps’ brand by comparing the performance using the MCF plot. Lastly, the suitable strategies suggested to be focused on predictive maintenance, preventive maintenance and corrective maintenance in handling the maintenance.

A Study on Statistical Methods for Prediction of Service Life of Fire Trucks

The current methods of calculating the economic productivity of fire pumpers reduce the value of the vehicle based on its lifetime use. However, it is reasonable to base the service time of a fire pumper on its original function. In this study, we proposed the use of the functional approach to determine the productivity of fire pumpers as opposed to the use of the economic approach. The Korea Fire Institute is a professional institution that inspected 342 fire pumpers in 2019. In all, 102 pumpers were found to be malfunctioning. The number was modified to 100 cases considering the production date and results of statistical analysis. Next, we determined a mean time to failure (MTTF) of 7.65 years based on the service time data using Weibull distribution; this MTTF is 2.35 years shorter than the current mean service time of the pumpers, so this study selected a reasonable service time of 8 years for a pumper.

Mathematical Modeling and Time Dependent Availability Analysis of Poly - Ethylene Terephthalate Bottle Hot Drink Filling System: A Case Study

The current research aims to analyze the Time Dependent System Availability (TDSA) and identify the most sensitive component/unit of Poly Ethylene Terephthalate (PET) Bottle Hot Drink Filling System of a beverage Industry with Markovian approach. TDSA and Mean time between failures (MTBF) is computed for system concerned. The industrial system chosen includes five components namely Blow Moulding Machine, Filling Machine, Cooling Machine, Labeling Machine and Coding Machine. Transition diagram of the system has been developed and respective Chapman-Kolmogorov equations are originated. The derived equations are further simplified by an advance and receptive method acknowledged as adjustive step size control Runge-Kutta method. On basis of TDSA analysis most sensitive unit/component has been identified and maintenance priorities to other units/components have been assigned.

Reliability analysis of exponentiated Poisson‐exponential constant stress accelerated life test model

AbstractAccelerated life testing is an efficient tool frequently adopted for obtaining failure time data of test units in a lesser time period as compared to normal use conditions. We assume that the lifetime data of a product at constant level of stress follows an exponentiated Poisson‐exponential distribution and the shape parameter of the model has a log‐linear relationship with the stress level. Model parameters, the reliability function (RF), and the mean time to failure (MTTF) function under use conditions are estimated based on eight frequentist methods of estimation, namely, method of maximum likelihood, method of least square and weighted least square, method of maximum product of spacing, method of minimum spacing absolute‐log distance, method of Cramér‐von‐Mises, method of Anderson–Darling, and Right‐tail Anderson–Darling. The performance of the different estimation methods is evaluated in terms of their mean relative estimate and mean squared error using small and large sample sizes through a Monte Carlo simulation study. Finally, two accelerated life test data sets are considered and bootstrap confidence intervals for the unknown parameters, predicted shape parameter, predicted RF, and the MTTF at different stress levels, are obtained.

RAMI analysis of the Collective Thomson Scattering system front-end – Part2 – reliability block diagram analysis

ITER is an experimental tokamak nuclear fusion reactor with the goal of achieving afusion energy gain factor of 10. Nuclear fusion presents an extreme environment for materials during operations while requiring continuous uninterrupted operation.The Reliability Block Diagram (RBD) is a graphic methodology for system reliability modelling which is constructed from the reliability-wise relations between different subsystems/components and their respective reliability and maintenance data. In this paper, we construct andanalyse the RBD for the Collective Thomson Scattering (CTS) front-end both in terms of fulfilling its functions and its effects in the ITER tokamak operations. Our RDB analysis results were then used to propose mitigation actions which include design changes and operational procedures to deal with the identified failure modes.Our initial results indicate that the system's mean availability at the end of its lifecycle of 20 years is no greater than 82.55% which was due to low Mean Time Between Failures (MTBF) of a critical system component – theSplit Biased Waveguide (SBWG) – aswell as several thermally loaded components. After mitigation actions, which aimed at controlling the system's exposure to heat loads, the MTBFs increased and the resulting mean availability achieved values over 97%, in conformity with design specifications. Furthermore, considering the CTS failure modes with impact on ITER operations, the expected value for the mean availability is of 99.995%. Therefore, we concluded that these failure modes did not require mitigation actions.In this article, we cover the second half of the RAMI analysis of the CTS diagnostic, the RBD analysis.