Application Of Reliability Engineering Research Articles

ENSURING THE FUTURE OF RENEWABLE ENERGY: A CRITICAL REVIEW OF RELIABILITY ENGINEERING APPLICATIONS IN RENEWABLE ENERGY SYSTEMS

As the global shift toward sustainable energy intensifies, the reliability and robustness of renewable energy systems become paramount. This research article offers a comprehensive examination of the pivotal role that reliability engineering plays in optimizing the efficiency, longevity, and dependability of these renewable systems. Delving into varied energy domains, from solar and wind to geothermal and bioenergy, the study elucidates the challenges and breakthroughs in ensuring consistent energy outputs amidst the inherent uncertainties of renewable sources. The study exploration also highlights the innovative intersection of emerging technologies, such as artificial intelligence and predictive maintenance, in augmenting the reliability of these green energy systems. Through real-world case studies, the research paper provides insights into the tangible benefits and lessons drawn from effective reliability engineering applications. Conclusively, the paper posits actionable recommendations for both policymakers and engineers, emphasizing the indispensable nature of reliability engineering in shaping a resilient renewable energy future. This study serves as a seminal reference for stakeholders aiming to enhance the sustainability and dependability of the next generation of renewable energy systems.

A two‐parameter parsimonious bathtub model for the analysis of system failure times with illustrations to reliability data

AbstractIn this study, a two‐parameter, upper‐bounded probability distribution called the tau distribution is introduced and its applications in reliability engineering are presented. Each of the parameters of the tau distribution has a clear semantic meaning. Namely, one of them determines the upper bound of the distribution, while the value of the other parameter influences the shape of the cumulative distribution function. A remarkable property of this new probability distribution is that its probability density function, survival function, hazard rate function (HRF), and quantile function can all be expressed in terms of its cumulative distribution function. The HRF of the proposed probability distribution can exhibit an increasing trend and various bathtub shapes with or without a low and long‐flat phase (useful time phase), which makes this new distribution suitable for modeling a wide range of real‐world problems. The constraint maximum likelihood estimation, percentile estimation, approximate Bayesian computation, and approximate quantile estimation computation are proposed to calculate the unknown parameters of the model. The suitability of the estimation methods is verified with the aid of simulation and real‐world data results. The modeling capability of the tau distribution was compared with that of some well‐known two‐ and three‐parameter probability distributions using two data sets known from the literature of reliability engineering: time between failures data of a machining center, and time to failure of data acquisition system cards. Based on empirical results, the new distribution may be viewed as a viable competitor to the Weibull, Gamma, Chen, and modified Weibull distributions.

A new failure times model for one and two failure modes system: A Bayesian study with Hamiltonian Monte Carlo simulation

This paper presents an additive Gompertz-Weibull (AGW) distribution, a four-parameter hybrid probability distribution, and its applications in reliability engineering. The failure rate (FR) function of the proposed model demonstrates an increasing trend and a variety of bathtub shapes with or without a low and yet long-stable segment, making it appropriate for modelling a wide variety of real-world problems. Some relationships between the AGW’s FR and its mean residual life functions are examined. For parameter estimation, maximum likelihood and Bayesian inferences are considered. For posterior simulations, we use Hamiltonian Monte Carlo to evaluate the Bayes estimators of the AGW parameters. We evaluate the performance of the proposed AGW model to that of other recent bathtub distributions constructed following the same approach on three failure time datasets. The first two datasets represent device failure times, while the third represents early cable-joint failure times, all with bathtub FR. For comparison, five parametric and nonparametric evaluation criteria and the fitted FR and mean residual life curves were employed. The results indicated that the AGW model would be the best choice for describing failure times, especially when the bathtub-shaped FR of the presented dataset exhibits its three segments.

A New Modified Exponent Power Alpha Family of Distributions with Applications in Reliability Engineering

Probability distributions perform a very significant role in the field of applied sciences, particularly in the field of reliability engineering. Engineering data sets are either negatively or positively skewed and/or symmetrical. Therefore, a flexible distribution is required that can handle such data sets. In this paper, we propose a new family of lifetime distributions to model the aforementioned data sets. This proposed family is known as a “New Modified Exponent Power Alpha Family of distributions” or in short NMEPA. The proposed family is obtained by applying the well-known T-X approach together with the exponential distribution. A three-parameter-specific sub-model of the proposed method termed a “new Modified Exponent Power Alpha Weibull distribution” (NMEPA-Wei for short), is discussed in detail. The various mathematical properties including hazard rate function, ordinary moments, moment generating function, and order statistics are also discussed. In addition, we adopted the method of maximum likelihood estimation (MLE) for estimating the unknown model parameters. A brief Monte Carlo simulation study is conducted to evaluate the performance of the MLE based on bias and mean square errors. A comprehensive study is also provided to assess the proposed family of distributions by analyzing two real-life data sets from reliability engineering. The analytical goodness of fit measures of the proposed distribution are compared with well-known distributions including (i) APT-Wei (alpha power transformed Weibull), (ii) Ex-Wei (exponentiated-Weibull), (iii) classical two-parameter Weibull, (iv) Mod-Wei (modified Weibull), and (v) Kumar-Wei (Kumaraswamy–Weibull) distributions. The proposed class of distributions is expected to produce many more new distributions for fitting monotonic and non-monotonic data in the field of reliability analysis and survival analysis.

An Overview of Structural Design, Analysis and Common Monitoring Technologies for Floating Platform and Flexible Cable and Riser

Offshore oil and gas development plays an important part in the global energy sector. Offshore platforms and flexible pipes are the key equipments in the whole offshore oil and gas development system. Because of the randomness and uncertainty of wave and current loads in the ocean environment, the structural design and mechanical analysis of the marine equipment can be highly complicated. Therefore, this paper reviews the recent works of the theoretical model, numerical simulation, and experimental test in three research areas: hydrodynamic analysis of offshore platforms, structural mechanics analysis of flexible pipe and cable, and monitoring technology of offshore floating structures under marine loads. By analyzing their main research methods and key technical difficulties, this paper provides theoretical basis and technical support for the reliability engineering application of offshore platforms and flexible pipelines. Also, China is relatively backward in the design of marine floating platform, the design, analysis and testing of flexible pipeline and cable, as well as the marine equipment prototype monitoring technology research. Calling for breakthroughs at the earliest possible stage in the above fields, prime research should be focused on and strategic planning should be made to deal with “key areas and stranglehold problems”. It is of great significance for the development of China’s deep-sea energy and resource development of independent technology and on time to achieve the “carbon peak” national strategic objectives.

Reliability engineering applications in electronic, software, nuclear and aerospace industries: A 20 year review (2000–2020)

A review on reliability engineering applications in 4 industrial domains namely electronic, software, nuclear and aerospace from the 2000′s to the present day is compiled. The progress in industrial maintenance activities and Human Reliability Analysis (HRA) linked to these domains are explored. Then, the mathematical aspect of reliability evaluation, in particular multi-state system (MSS), which characterizes the system complexity in these domains are presented. Trends progression are obtained through literature of respective areas as well as available technical information and industrial circulations. Through this review, trend similarities between the mentioned domains and the challenges in reliability science implementation are uncovered. The methods employed in respective industry are explained, with each strength and weakness analysed, together with application examples. This work reveals the role of Prognostic and Health Management (PHM), HRA and analytical methodologies such as MSS and Probabilistic Risk Assessment (PRA) in managing reliability of complex industrial systems. Finally, it stresses on the importance of synergy between these frameworks to ensure a complete reliability assessment in the industry.

New generalized-X family: Modeling the reliability engineering applications.

As is already known, statistical models are very important for modeling data in applied fields, particularly in engineering, medicine, and many other disciplines. In this paper, we propose a new family to introduce new distributions suitable for modeling reliability engineering data. We called our proposed family a new generalized-X family of distributions. For the practical illustration, we introduced a new special sub-model, called the new generalized-Weibull distribution, to describe the new family’s significance. For the proposed family, we introduced some mathematical reliability properties. The maximum likelihood estimators for the parameters of the new generalized-X distributions are derived. For assessing the performance of these estimators, a comprehensive Monte Carlo simulation study is carried out. To assess the efficiency of the proposed model, the new generalized-Weibull model is applied to the coating machine failure time data. Finally, Bayesian analysis and performance of Gibbs sampling for the coating machine failure time data are also carried out. Furthermore, the measures such as Gelman-Rubin, Geweke and Raftery-Lewis are used to track algorithm convergence.

Optimal preventive maintenance for repairable weighted k-out-of-n systems

Weighted k-out-of-n systems form an important class of redundant systems with a wide range of applications in reliability engineering. In this paper, we introduce novel optimal preventive maintenance models for the class of weighted k-out-of-n systems based on average cost and availability criteria. Depending on the average number of failed components, we set up a cost (availability) function corresponding to the time that the total weights of the working components become less than a predetermined threshold m, or the age of the system reaches TPM. The form of the cost (and availability) function relies on the mixture representation of the system reliability based on the notion of the signature of the system. Some examples of weighted k-out-of-n systems are presented to demonstrate the proposed models numerically and graphically.

Reliability Analysis of Randomly Weighted k-out-of-n Systems with Heterogeneous Components

The k-out-of-n systems with components having random weights have wide applications in reliability engineering. In this paper, we implement the study on reliability analysis of k-out-of-n systems with heterogeneous components and random weights. Firstly, for a randomly weighted k-out-of-n system with dependent components chosen from two different classes of ordered components, we carry out stochastic comparisons of different random selection strategies with respective to the usual stochastic order, the increasing convex [concave] order, and the expectation order. Secondly, we investigate the performance levels of randomly weighted k-out-of-n systems with components chosen via independent Bernoulli trials under different selection probabilities. Thirdly, we consider the assembly of a randomly weighted k-out-of-n system through drawing n subsystems from m groups with each group consisting of independent and identically distributed components. The effects of selecting strategies and sampling probabilities on the systems total capacities are studied according to the above mentioned stochastic orders when the subsystems possess parallel or series structure. These results can be conducive to assembling randomly weighted k-out-of-n systems in practical scenarios. Numerical examples are provided to illustrate the findings as well.

Introduction to formal concept analysis and its applications in reliability engineering

Formal Analysis of Concepts (FCA) is a method of data analysis that helps to study the relationship between a set of objects and a set of attributes (the formal context). FCA not only allows detecting data groups (concepts) and their graphical visualization, but also extracting rules that could reveal the underlying structure of the analyzed context. The main idea of this paper is to present the fundamentals of FCA and how it can be used in reliability engineering problems. To this aim, examples in reliability engineering, from both the literature and authors’ experience, have been selected for analysis. Comments on the new insights provided by FCA are also highlighted. Finally, the results from the examples selected show that other reliability areas could benefit from using an FCA-based approach.

Reliability engineering application to pipeline design

PurposeThe purpose of this paper is to investigate the application of reliability engineering to oil and gas (O&G) pipeline systems with the aim of identifying means through which reliability engineering can be used to improve pipeline integrity, specifically with regard to man-made incidents (e.g. material/weld/equipment failure, corrosion, incorrect operation and excavation damages).Design/methodology/approachA literature review was carried out on the application of reliability tools to O&G pipeline systems and four case studies are presented as examples of how reliability engineering can help to improve pipeline integrity. The scope of the paper is narrowed to four stages of the pipeline life cycle; the decommissioning stage is not part of this research. A survey was also carried out using a questionnaire to check the level of application of reliability tools in the O&G industry.FindingsData from survey and literature show that a reliability-centred approach can be applied and will improve pipeline reliability where applied; however, there are several hindrances to the effective application of reliability tools, the current methods are time based and focus mainly on design against failure rather than design for reliability.Research limitations/implicationsThe tools identified do not cover the decommissioning of the pipeline system. Research validation sample size can be broadened to include more pipeline stakeholders/professionals. Pipeline integrity management systems are proprietary information and permission is required from stakeholders to do a detailed practical study.Originality/valueThis paper proposes the minimum applied reliability tools for application during the design, operation and maintenance phases targeted at the O&G industry. Critically, this paper provides a case for an integrated approach to applying reliability and maintenance tools that are required to reduce pipeline failure incidents in the O&G industry.

Imprecise reliability assessment for heavy numerical control machine tools against small sample size problem

Small sample size problem is one of the main problems that heavy numerical control (NC) machine tools encounter in their reliability assessment. In order to deal with the small sample size problem, many indirect reliability data such as reliability data of similar products, expert opinion, and engineers’ experience are used in reliability assessment. However, the existing mathematical theories cannot simultaneously process the above reliability data of multiple types, and thus imprecise probability theory is introduced. Imprecise probability theory can simultaneously process multiple reliability data by quantifying multiple uncertainties (stochastic uncertainty, fuzzy uncertainty, epistemic uncertainty, etc.) together. Although imprecise probability theory has so many advantages, the existing natural extension models are complex and the computation result is imprecise. Therefore, they need some improvement for the better application of reliability engineering. This paper proposes an improved imprecise reliability assessment method by introducing empirical probability distributions to natural extension model, and the improved natural extension model is applied to the reliability assessment of heavy NC machine tool spindle to illustrate its effectiveness.

Comprehensive Database for Concrete Creep and Shrinkage: Analysis and Recommendations for Testing and Recording

The first large worldwide database of creep and shrinkage tests was assembled at Northwestern University (NU) in 1978. It was expanded as the RILEM database in 1992 and further in 2008. A major expansion, completely restructured and verified, named the NU Database, is now presented. The number of the test curves of creep and drying shrinkage is more than doubled and over 400 test curves of autogenous shrinkage are added. The database covers longer measurement periods and encompasses the effects of admixtures in modern concrete mixtures. The database contains roughly 1400 creep and 1800 shrinkage curves, of which approximately 800 creep and 1050 shrinkage curves contain admixtures. Their analysis shows significant influence of admixtures on the creep and shrinkage behavior. The mixture proportions, testing conditions, and specimen geometries are documented in greater detail, and information on the admixture contents and aggregate types is included. The new database makes it possible to calibrate and verify improved creep and shrinkage prediction models. Additionally, the statistics of the mixture parameters, strength distributions, and scatter of the compliance curves have been extracted for applications in reliability engineering and probabilistic performance assessment. Data analysis brings to light various recommendations for testing and recording, and suggests corrections of various oversights distorting the reported data. These recommendations would make future test data more useful, consistent, complete, and reliable. The NU database is now available for free download at www. civil.northwestern.edu/people/bazant/ as well as at www.baunat.boku.ac.at/creep.html.

Tensile properties and fracture reliability of a glass-coated Co-based amorphous microwire

Co68.15Fe4.35Si12.25B15.25 (at%) amorphous microwires with a smooth surface and a circular cross-section were fabricated by the glass-coated melt spinning method. Their mechanical properties were evaluated through tensile tests of the glass-coated amorphous microwires, and their fracture reliability was estimated using two- and three-parameter Weibull analysis. X-ray diffraction and transmission electron microscopy results showed that these glass-coated Co-based microwires were mostly amorphous. The coated Co-based microwires exhibit a tensile strength of 1145 to 2457 MPa, with a mean value of 1727 MPa and a variance of 445 MPa. Weibull statistical analysis showed that the tensile two-parameter Weibull modulus of the amorphous microwires is 4.16 and the three-parameter Weibull modulus is 1.61 with a threshold value as high as 942 MPa. These results indicate that the fabricated microwires exhibit good tensile properties and fracture reliability, and thus appear to be good candidates for electronics reliability engineering applications.

Bayesian Credible Limits of Failure Rate and its Applications in Reliability Engineering

This paper for product obeys exponential distribution, in the case of data with only one failure, one-sided Bayesian upper credible limit, two-sided Bayesian lower and upper credible limits of failure rate are proposed, moreover, the one-sided Bayesian lower credible limit, two-sided Bayesian lower and upper credible limits of the reliability are also provided. Finally, calculation performed on practical problems, show that the provided method is feasible and easy to perform in engineering.

Analysis of Constant-Stress Accelerated-Life-Test Data of Electric Appliances

In the field of electric appliances’ reliability, the constant-stress accelerated-life-test is commonly used to test the reliability of electric appliances. A new analysis method based on constructed data is introduced to analyze the constant-stress accelerated-life-test data of electric appliances under Weibull distribution. The correlation between shape parameter and characteristic life is took into account and the estimated value of characteristic life is modified, which increase the model fitting optimization and improve the analysis precision. Moreover, the method avoids table lookup and is easy to be realized by computer software in the application of reliability engineering for electric appliances.

E-Bayesian Estimation Method and its Applications in Reliability Engineering

Evaluation method of reliability of industrial products needs to be improved effectively with the advance of science and technology. This paper introduces a new method, named E-Bayesian estimation method, to estimate failure probability in reliability engineering. The definition of E-Bayesian estimation of the failure probability is provided, moreover, the formulas of E-Bayesian estimation and hierarchical Bayesian estimation of the failure probability were provided, and properties of the E-Bayesian estimation, i.e. relations between E-Bayesian estimation and hierarchical Bayesian estimation, are also provided. Finally, calculation on practical problems shows that the provided method is feasible and easy to perform.

Application of Reliability Engineering on the Maintenance of Ship Structural Integrity(Application of Reliability Engineering to Structures)

Application of Reliability Engineering on the Maintenance of Ship Structural Integrity(Application of Reliability Engineering to Structures)

A Seismic Design for Over-Track Station Buildings(Application of Reliability Engineering to Structures)

A Seismic Design for Over-Track Station Buildings(Application of Reliability Engineering to Structures)

HTV Structure Design and Verification(Application of Reliability Engineering to Structures)

HTV Structure Design and Verification(Application of Reliability Engineering to Structures)