Constant Failure Rate Research Articles

Intuitionistic Fuzzy Approach for Reliability Assessment of NSP System Under Constant Failure Rates

Intuitionistic Fuzzy Approach for Reliability Assessment of NSP System Under Constant Failure Rates

A novel probabilistic model: Simulation and modeling the time duration in musical education and engineering

Statistical analysis of the time-to-event scenarios commonly involves the use of the exponential and Rayleigh distributions. However, the exponential distribution is constrained by its constant failure rate, while the Rayleigh distribution exhibits a growing (or increasing) failure rate. The linear failure rate distribution provides a broader perspective by encompassing both of these distributions, including the possibility of a non-increasing hazard function. In this paper, a new distribution is introduced, which could be considered as one of the major modifications to the linear failure rate distribution, known as the weighted linear failure rate distribution. The model proposed illustrates both monotonic and a known non-monotonic failure rate. This paper extensively explores the characteristics of the proposed distribution. It presents the maximum likelihood estimates for the unknown parameters and includes a simulation study. The analysis focuses on three real data sets obtained from the fields of musical education and engineering. By employing three decisive tools, it is observed that the current distribution provides a superior fit in comparison to several other widely recognized distributions.

An analytical method for reliability evaluation of power distribution system with time-varying failure rates

Reliability evaluation is crucial in assessing the power supply capacity and guiding the planning and operation of the distribution system. Traditional analytical reliability evaluation usually assumes a constant failure rate for components, implying that the life distribution follows an exponential distribution. However, in reality, the failure rate of components varies over time due to external disturbances and aging. As a result, traditional analytical reliability evaluation methods are no longer applicable. To address this issue, this paper presents an analytical method for evaluating the reliability of the distribution system with time-varying failure rates. The method considers short-term and long-term time-varying failure rates using density evolution and non-homogeneous Poisson process techniques, respectively. Both steady-state and instantaneous indices are calculated to reflect the level of system reliability. Finally, the proposed method is applied to the IEEE RBTS Bus 6 test system, demonstrating its correctness and efficiency.

The component outage model for power systems using availability approximations

The traditional outage models with constant failure rates do not truly reflect the environmental and operating conditions nor the effect of repair operations on power systems. This paper proposes two useful approximations for the availability function based only on the first three of the lifetime distribution. We compare the availability function of a power transformer using the numerical inverse of the transformed availability function. It also suggests methods to verify the effectiveness of the approaches. Finally, it outlines the proposed approximations to validate the efficacy of the approximations.

PROBABILISTIC ANALYSIS OF A THREE-UNIT SERIES-PARALLEL SYSTEM WITH COMMON-CAUSE, HUMAN ERROR AND ENVIRONMENTAL STATE FAILURES

This paper presents a mathematical model for performing reliability and availability analyses of Series- Parallel system with constant human error and common-cause failure rates. The method of Integro-differential equation was used to develop equations for the model to obtain the general expression. The Laplace transform technique was used to obtain the system reliability with constant human error failure rate of the system

Assessment of the FIDES Guide 2022 electrical, electronic, and electromechanical reliability prediction methodology

The FIDES Guide is a reliability prediction handbook published by a group of European defense and aerospace manufacturers under the supervision of the French Ministry of Defense. This paper evaluates the suitability of FIDES for predicting reliability. The evaluation is based on the fitness of the model used in FIDES for calculating the failure rate and the accuracy of its reliability predictions. The assessment makes use of the questionnaire in the IEEE Standard 1413, “IEEE Standard Framework for Reliability Prediction of Hardware.” The foundation of FIDES on the erroneous assumption of a constant failure rate for electronics, its omission of critical attributes (e.g., materials and geometry of components), and the subjectivity of certain inputs to the model make it inadequate for producing an accurate prediction.

Flexible Extension of the Lomax Distribution for Asymmetric Data under Different Failure Rate Profiles: Characteristics with Applications for Failure Modeling and Service Times for Aircraft Windshields

A novel four-parameter lifetime Lomax model is presented and investigated within the scope of this paper. The failure rate of the innovative model can be “monotonically decreasing failure rate,” “monotonically increasing failure rate,” or “constant failure rate,” and the density of the model can be “asymmetric right skewed,” “symmetric,” “asymmetric left skewed,” or “uniform density”. The new density is expressed as a blend of the Lomax densities that have been multiplied by an exponent. New bivariate Lomax types were created for our research. The maximum likelihood technique was utilized. We performed simulated experiments for the purpose of evaluating the finite sample behavior of maximum likelihood estimators, using “biases” and “mean squared errors” as our primary metrics of analysis. The novel distribution was evaluated based on a number of pertinent Lomax models, including Lomax extensions that were generated on the basis of odd log-logistic, Kumaraswamy, beta, gamma, and Topp–Leone families, among others. The newly developed extension demonstrated its relevance by predicting the service and failure times of datasets pertaining to aircraft windshields.

Evaluation of customer orientated indices and reliability study of electrical feeder system

Aim. Reliability evaluation of a system or component or element is very important in order to predict its availability and other relevant indices. Reliability is the parameter which tells about the availability of the system under proper working conditions for a given period of time. The study of different reliability indices are very important considering the complex and uncertain nature of the power system. Methods. The study uses classical methods of the reliability theory in respect to a system with a constant failure rate consisting of series-connected elements. Conclusions. The paper reviews literature dedicated to the reliability estimation of power supply systems. In particular, the paper examined studies that employed the Markov cut-set approach, the conditional probability approach, distribution systems simulation, probabilistic models, the Monte Carlo method, reliability network equivalent, state transition sampling, inspection repair-based availability optimisation of distribution systems, bootstrapping, fault tree analysis, Bayes networks, peak-valley partition model, demand response model, etc. The authors defined the problem and analysed input data. They showed that, in physical terms, the system configuration will be a series reliability network. Given the above, the system fails even if one component fails, and survives if all of the components survive. It is noted that, when considering the reliability of series systems, the three basic parameters are average failure rate, average annual outage time and average repair time. As the customer orientated indices associated with the research of operational reliability the system average interruption frequency index (SAIFI), the system average interruption duration index (SAIDI) and the customer average interruption duration index (CAIDI) were used. Using the example of an eight-node radial distribution system, reliability was estimated for each distribution section, as well, as at each load point. For the examined distribution sections and load points, three basic reliability parameters were also obtained, i.e., the average failure rate, average outage time and average annual outage time. For a radial distribution system, important customer-oriented indices were estimated, i.e., system average interruption frequency index, system average interruption duration index and customer average interruption duration index. The resultant data allow characterizing reliability and other associated indices, which is relevant for power distribution systems.

Stress-strength reliability under partially accelerated life testing using Weibull model

The reliability of a system is the probability that its strength exceeds its stress. This reliability is called as the stress-strength reliability. The inferences of the stress-strength reliability R=P(X>Y), when: (1) the strength (X) and stress (Y) are independent random variables follow one-parameter exponential distributions; and (2) the strength variable is subjected to the step-stress partially accelerated life test (SSPALT) are discussed recently. Exponential distribution has limitation to describe the strength and stress due to its constant failure rate. In this paper, we consider the estimate of R, when: (1) X and Y are independent random variables that follow two-parameter Weibull distributions; and (2) the strength variable X is subjected to the SSPALT. The maximum likelihood estimator of R and its asymptotic distribution are not obtained analytically and therefore the asymptotic confidence interval of R is discussed. A real data set is analyzed using the proposed model for illustrative and comparison purposes. Based on the numerical results, we would conclude that the exponential distribution is rejected to fit the strength and stress, at any significant level that is greater than or equal to 2.58%, against the Weibull model.

Effect of Switch-over Devices on Availability of a Steam Generating System in a Thermal Power Plant

Purpose: Suggests a method to compute availability of the main part i.e. Steam- generation part of a Thermal Power Plant by taking into consideration the repair/ failure rates of switch-over devices. This part contains gas classifier, crushing mills and boilers as its subsystems. Design/ Methodology/ Approach:. Assuming constant failure and repair rates, transition diagram of the system is drawn and problem is formulated using Markov Method. The governing difference equations are solved recursively for a steady state. Findings: System is analyzed for long run availability followed by illustration, table and graph. Originality / Value: It will help in increasing overall performance of Thermal Power Plant.

Resilience of wave energy farms using metocean dependent failure rates and repair operations

Emerging offshore renewable energy technologies are expected to become an important part of the future energy system, and reliability for these new technologies in different metocean scenarios must be guaranteed. This poses a challenge in extreme weather scenarios like storms, in particular for less mature technologies such as wave energy. Not only the offshore survivability must be controlled; the restoration after disruptive events and failures should be addressed and optimized. Offshore operations are costly and cannot be carried out if the weather is too harsh, and the resulting downtime after failures may be financially devastating for projects. In this paper, the resilience of large wave energy systems is studied with respect to wave conditions, metocean dependent failure rates, and weather windows available for offshore repair operations. A metocean- and time-dependent failure rate is derived based on a Weibull distribution, which is a novelty of the paper. The performance of the farm is assessed using the varying failure rates and metocean data at different offshore sites. Critical metocean thresholds for different offshore vessels are considered, and the resilience is quantified using relevant measures such as unavailability and expected energy not supplied. The resilience analysis is coupled to an economic assessment of the wave farm and different repair strategies. Our results show that the commonly used assumption of constant failure rates is seen to overestimate the annual energy production than when a more realistic varying failure rate is used. Two offshore sites are compared, and the availability is found to be higher at the calmer site. Most of the evaluated repair strategies cannot be considered to be economically justified, when compared to the cost of the energy not supplied.

Non-Parametric Hypothesis Testing for Unknown Aged Class of Life Distribution Using Real Medical Data

Over the last few decades, the statisticians and reliability analysts have looked at putting exponentiality to the test using the Laplace transform technique. The non-parametric statistical test used in this study, which is based on this technique, evaluates various treatment modalities by looking at failure behavior in the survival data that were gathered. Following use of the suggested strategy, patient survival times are recorded. In this investigation, it was presupposed that the Laplace transform order of (UBAC2) attribute or the constant failure rate would determine how the observed data behave (exponential scenario). If the survival data are exponential, the recommended treatment approach is ineffective. If the survival data are UBAC2L, the technique in use produces a better or a higher expected total present value than an older one governed by an exponential survival function (discussed in the Applications section). The efficiency and critical values of the test are calculated and compared to those of other tests in order to ensure that the suggested statistical test is applied correctly.

Process modeling for decomposition unit of a UFP for reliability indices subject to fail-back mode and degradation

PurposeEnsuring safe operation of a urea fertilizer plant (UFP) is a vital aspect for its functioning and production. Clearly the safe operation of such systems can only be archived with proper and effective maintenance scheduling and through controlling its failures as well as repairs of the components. Also for this, the concern plant management must have the information regarding the failures that affects the system's performance most/least. The objective of this study is to analyze mathematically the factors that are responsible for the failure/degradation of the decomposition unit of UFP.Design/methodology/approachThe considered system has been modeled by the aid of Markov's birth–death process with two types of failures for its components: variable (which are very similar in practical situations) and constant. The mathematical model is solved by the help of Laplace transform and supplementary variable technique.FindingsIn the present paper, the availability, reliability and mean time to failure (MTTF) are computed for the decomposition unit of the UFP. The critical components that affect the reliability and MTTF of the decomposition unit are identified through sensitivity analysis.Originality/valueIn this paper, a mathematical model based on the working of the decomposition unit of a UFP has been developed by considering two types of failure, namely, variable failures rates and constant failure rates (which has not been done in the literature for the decomposition unit). Conclusions in this paper are good references for the improvement of the same.

Reliability assessment of a NSP system under constant triangular fuzzy failure rates

Reliability assessment of a NSP system under constant triangular fuzzy failure rates

Analysis of Steady State Availability of a Series– Parallel Repairable System with Hot Standbys, Three Units and Vacation

Abstract: In this paper we analyze the steady state availability of a series-parallel repairable system. In this system, the first unit is master control unit and other two are slave units and one single repairman who operates single vacation. Under that assumption each unit has arbitrary repair time distribution & a constant failure rate. Also, it is noted that to calculate the availability of the system it is required to obtain the explicit expression and for obtaining steady-state probabilities it is necessary to use “the supplementary variable” method as well as “Markov process theory”.

Improved Modeling of Maintenance for Future Vertical Lift

The Future Vertical Lift (FVL) Cross Functional Team (CFT) required analysis on the sustainment performance of FVL aircraft operating in Multi-Domain Operations (MDO). A study from last year forecasted the sustainment performance of FVL’s Future Attack Reconnaissance Aircraft (FARA) based upon historical performance of the enduring AH-64 Apache infused with emerging technologies. This study improved last year’s model by refining key assumptions. First, a Forward Maintenance Team in MDO conducted limited maintenance that was constrained by an austere environment. Second, the assumption of constant component failure rates was updated with increasing hazard rates to reflect fatigue in mechanical systems like the transmission and rotors. Third, technological risk was captured by accounting for the uncertainty associated with infused technologies based on the Technology Readiness Level. Finally, the historical failure rates of the enduring fleet of AH-64, UH-60, and CH-47 aircraft guided reliability forecasts for FARA increments over its life cycle.

Reliability prediction for aircraft fleet operators: A Bayesian network model that combines supplier estimates, maintenance data and expert judgement

Reliability prediction is crucial for aircraft maintenance and spare part inventory decisions. These predictions are made based on operational data collected by fleet operators or design life estimates provided by aircraft suppliers. Purely data-driven predictions have limited use especially when the fleet is young, hence the data is scarce. In this case, design life estimates are used for predicting reliability often by assuming a constant failure rate. This strong assumption is not necessarily valid for all components. This paper proposes a Bayesian Network (BN) modelling framework that systematically combines design life estimates, operational data, and expert judgement for reliability prediction of aircraft subsystems. The proposed BN adjusts the design life estimates based on expert judgement regarding supplier and manufacturing quality and revises it based on operational data. We used the BN to predict the reliability of a large aircraft fleet by using failure and maintenance data provided by a large fleet operator. We compared the predictive performance of the BN to using only data-driven approaches and to using only design life estimates provided by the aircraft supplier. The BN model provides consistently accurate reliability predictions compared to design-life estimates and purely data-driven approaches especially when the available data is scarce.

Modular battery energy storage system design factors analysis to improve battery-pack reliability

Traditional battery energy storage systems (BESS) are based on the series/parallel connections of big amounts of cells. However, as the cell to cell imbalances tend to rise over time, the cycle life of the battery-pack is shorter than the life of individual cells. New design proposals focused on modular systems could help to overcome this problem, increasing the access to each cell measurements and management. During the design of a modular battery system many factors influence the lifespan calculation. This work is centred on carrying out a factor importance analysis to identify the most relevant variables and their interactions. The analysis models used to calculate the reliability of the batteries are the state of health (SoH) and the Multi-State System (MSS) analysis with the Universal Generating Function (UGF), while electronic devices reliability is approximated using constant failure rate achieved with FIDES guide. Thus, it is determined numerically that module redundancy, cell capacity, module voltage and their interactions are the most determinant design characteristics.

철도차량의 좌우측절단자료를 이용한 2단계 상태기반 점검주기 연구

Purpose: This paper introduces two-phase condition-based maintenance by analyzing left-truncated and right-censored field data, with characteristics managed by the existing maintenance schedule.BRMethods: The failure rate was initially observed as a constant failure rate (CFR) and, after a certain point, as an increasing failure rate (IFR). Therefore, a two-phase condition-based maintenance policy with each stage maintenance cycle was proposed. In addition, a maintenance model was developed to determine the optimal maintenance schedule in terms of economic feasibility.BRResults: The optimal maintenance schedule was derived by minimizing the total cost, including the inspection cost, failure cost, and improvement factor. Further, changes in the optimal maintenance schedule were examined based on the ratios of the inspection cost, failure cost, and improvement factor.BRConclusion: Designing a maintenance policy to evaluate the system conditions and mutual adequacy between the cost and improvement effect in terms of light and medium maintenance is essential.

Statistical Modeling of Some Cancerous Diseases Using the Laplace Transform Approach of Basic Life Testing Issues.

The purpose of the nonparametric statistical test used in this study is to compare different treatment options by looking at failure behavior in recorded survival data. Patients' survival times are documented after using the proposed approach. The observed data's behavior was assumed to be based on used better than aged in the moment generating function order (UBAmgf) characteristic or a constant failure rate in this study (exponential scenario). Suppose that the survival data is UBAmgf, then the treatment or the machine or system in use produces a better or a higher expected total present value than an older machine governed by an exponential survival function; if the data is exponential, the suggested treatment strategy is ineffective (the recommended treatment approach has neither positive or negative effects on the patients). To guarantee that the suggested statistical test is used correctly, the efficiency and critical values are calculated and compared to those of other tests, and the technique is then applied to medical data.