Product Reliability Assessment Research Articles

A novel random-effect Birnbaum-Saunders distribution for reliability assessment considering accelerated mechanism equivalence

ABSTRACT Birnbaum-Saunders (B-S) distribution has been widely used in reliability assessment of products. However, the basic B-S distribution fails in characterizing the variation of damage caused by different units. In this paper, a novel random-effect B-S distribution which considers the unit heterogeneity is proposed. First, the novel distribution incorporates the inverse gamma distribution into the shape parameter of B-S distribution, and statistical inferences of the novel distribution are thoroughly investigated. Then, an extension of the proposed B-S distribution is developed to handle accelerated life test (ALT) data. In order to ensure the validity of ALTs, a coefficient of variation hypothesis test method employing the necessary condition for mechanism equivalence of the proposed distribution is executed. To estimate the parameters of the novel B-S distribution with explanatory variables, a two-step algorithm combining analogue least square and expectation maximization (ALS-EM) is proposed based on the data with constant coefficients of variation. A simulation is conducted to verify the effectiveness of the proposed ALS-EM method. Finally, two actual engineering cases are utilized to show the advantages of the random-effect B-S distribution in terms of goodness-of-fit and reliability assessment precision.

Model reference sliding mode control for two-degree-of-freedom electro-hydraulic shaking table

The multi-axis electro-hydraulic shaking table (EHST) is capable of simulating complex vibration environments to assess product reliability under vibrational excitation. The random vibration control method plays a crucial role in simulating these environments. However, the unmolded disturbances and the nonlinearity of the system have a significant impact on the control accuracy of the EHST. Sliding mode control (SMC) can be used in single-input single-output electro-hydraulic servo systems (EHSS) to attenuate the influence of disturbance forces. The conventional SMC is not suitable for acceleration random vibration control of the multi-axis EHST because the coupling between the axes and the actuators and the null bias of the servo valve are not taken into account. A model reference sliding mode control (MRSMC) is presented in this paper based on the nonlinear dynamic model of the EHST. The MRSMC designed based on the backstepping method and Lyapunov theory is used to compensate for the disturbance forces and the null bias of the servo valve. Experimental acceleration random vibration responses show that the MRSMC enhances the accuracy of tracking the acceleration random signal.

Statistical inference of comparative generalized inverted exponential populations under joint adaptive progressive type-II censored samples

Design of efficient test plans to assessing product reliability rapidly, is a critical step to obtain product reliability accurately. In this paper, we are adopted the problem of statistical inference of two generalized inverted exponential populations in a competing duration. To save the balance between the optimal test time and the number of failures needing for statistical inference, joint adaptive type-II hybrid progressive censoring scheme is applied. The model parameters are estimated with classical methods (maximum likelihood and bootstrap) for point estimate and the corresponding confidence intervals. Also, Bayes estimators of model parameters are computed under importance sample technique with the corresponding Bayes credible intervals. A real data sets are analyzed for illustrating purposes. The results are compared and assessed through Monte Carlo simulation study.

Cyclic stress accelerated life test method for mechatronic products

AbstractThe reliability requirements for mechatronics continue to increase. Traditional life test methods make it difficult to obtain the data required to assess or predict the reliability of these mechatronic products within a reasonable time. Accelerated life tests can speed up the failure process of the product by using accelerated stress conditions. And then test data is obtained to predict the reliable life of the product under normal service conditions through modeling and analysis. The test efficiency of the accelerated life tests is higher than that of the life test. So, the method of accelerated life tests has become a solution for life and reliability prediction of highly reliable and long‐life mechatronic products. However, mechatronic products usually undergo cyclic stress during service. The use of cyclic stress as an accelerating stress in accelerated life tests can provide a realistic representation of service conditions and achieve higher test efficiency. Cyclic stress accelerated life test is an accurate and efficient solution for predicting the life and reliability of such mechatronic products. Current relative research is focused on constant stress, step stress and sequential stress accelerated life tests. A great challenge in engineering is modeling and analysis of cyclic stresses accelerated life tests. In this paper, we first describe the cyclic stress accelerated life test profile and its key parameters, then propose model assumptions and establish a modelling and analysis method for cyclic stress accelerated life test data, followed by an illustrative example to apply and validate the proposed method. The research results can provide technical support for the life and reliability assessment of mechatronic products under cyclic stress service conditions.

Reliability and consistency assessment of land cover products at macro and local scales in typical cities

ABSTRACT Urban areas have higher heterogeneity compared to natural areas, it is crucial to assess fine-resolution land cover products and discover how they differ in urban areas so that they can be efficiently used for various application scenarios. In this study, five typical cities in China were chosen as study areas to evaluate four commonly used 30 m land cover products: GLC_FCS30-2020, FROM-GLC30-2017, Globeland30-2020, and CLCD-2019. We analyzed the reliability of these four products using validation samples as well as by examining their area and spatial pattern consistency. Given the limitations of traditional accuracy assessments at the macro level, we added a local area evaluation to further examine the classification details in these products. The macro results indicated that four land cover products within urban areas have a similar overall accuracy, surpassing 76%, but there was a low consistency among them, ranging from 42.21% to 61.13%. The local accuracy assessment illustrated that GLC_FCS30-2020 and FROM-GLC30-2017 performed well in reflecting the intricate details of the city, however, the four products exhibited varying degrees of misclassifications and omissions. These phenomena suggest that more sophisticated algorithms are needed to consider urban particularities since fine-resolution land cover products may fail to capture complex urban details.

On Wiener Process Degradation Model for Product Reliability Assessment: A Simulation Study

This paper examines the application of the Wiener process as a degradation model. Its appropriateness as a degradation model is discussed and demonstrated with the aid of Monte Carlo simulations. In particular and for monotonically degrading systems, this paper demonstrates that the irreversible accumulation of damage can be modelled by the Wiener maximum process. First passage times of the Wiener and its maximum process are also revealed to coincide. Practical advantages of assessing system reliability from degradation data are highlighted by applying the Wiener process model to a real gallium arsenide (GaAs) laser data for telecommunication systems. The real data application results demonstrate that degradation analysis allows for conclusions about system reliability to be reached earlier without compromising estimation accuracy—a major practical advantage.

Warranty data maturity—Effect of observation time on reliability prediction and the warranty management process

AbstractWarranty data analysis is a form of life data analysis and is part of the engineering and business process of assessing product reliability and predicting the number of parts failing in the field and the associated warranty cost. However, oftentimes the prediction is started early and is based only on a few months of field data, which raises a question of data maturity. As data matures and the product is operating longer in the field the prediction changes, since the failure distribution becomes the function of the observation time. Data maturation has been known as a complicating factor in warranty data analysis affecting the accuracy of prediction, however there were very few attempts to look at how the data maturity affects the failure patterns and the probability of failure as the time in the field and consequently the observation time increases.This paper discusses the causes of data maturity, presents an analytical model to assess the maturation trends and presents several case studies based on the automotive electronics warranty data. The paper analyzes the patterns of how warranty data matures as more field data becomes available and how it affects the accuracy of prediction. It also suggests the criteria of determining the levels of data maturity.

Comparison between continuous and periodic inspections in step‐stress tests

Accelerated life test is currently the main method of assessing product reliability rapidly, and the design of efficient test plans is a critical step to ensure that accelerated life tests can assess the product reliability accurately, quickly and economically. In these tests, the samples are tested at stress levels higher than normal. Then, the product life at the normal stress level can be estimated by extrapolating the life information of samples at high stress levels to the normal level based on the stress–life relationship. In this paper, optimal k‐level step‐stress accelerated life tests are considered for the Weibull failure data under progressive Type‐I censoring. There are two strategies for performance inspection of the test unit, which include continuous inspection and periodic inspection. These two strategies generate the life data and group data, respectively. In this paper, these two inspection modes are compared and the efficiencies of these are obtained. This paper investigates the optimal design based on five optimality criteria under the constraint that the total experimental cost does not exceed a pre‐specified budget. Finally, based on the simulation study and a real data set, the advantages of using the continuous inspection relative to periodic inspection are investigated.

Diagnosis of injection-molded weld lines in ABS thermoplastic by polarized terahertz reflective imaging

We carry out a nondestructive study of injection-mold weld lines in an acrylonitrile butadiene styrene (ABS) thermoplastic electrical receptacle plate. Terahertz techniques show morphological features at the weld lines and reveal terahertz birefringence properties localized around the welds, indicating frozen-in molecular orientation and stress proximate to the welds. Surface acoustic microscopy corroborates the morphological features at the welds shown by terahertz imaging and also reveals anomalous mechanical properties at the weld lines. These results indicate that THz-based techniques provide nondestructive reliability assessment and quality control for injection-molded thermoplastic products.

Reliability Analysis of Special Vehicle Critical System Using Discrete-Time Bayesian Network

The reliability assessment of special vehicles has become very important. However, due to the special structure of special vehicles, it is difficult to collect a large amount of experimental data. The use of traditional fault tree analysis cannot accurately assess product reliability. In this paper, dynamic fault trees are used to model the critical systems of special vehicles, and discrete Bayesian networks are used to evaluate the reliability of critical systems of special vehicles, which solved the problems of difficulty in accurately describing complex systems in the process of system reliability analysis and difficulty in obtaining accurate data in the process of analysis. Finally, through the combination of expert experience and the evaluation of the calculation results, the rationality of the method used in this paper in the reliability evaluation of special vehicles is verified.

Evaluation of statistical methods for assessing reliability from degradation data : A simulation study

This paper deals with the evaluation of statistical methods for assessing product reliability from degradation data. The evaluation is based on a simulation study. Benefits of assessing reliability from degradation data over censored failure time data are demonstrated using data from the first simulation run. Bias, precision and coverage probability calculated from the 105 simulated samples are the performance measures used in the evaluation. Analysis of a real gallium arsenide (GaAs) laser data set for telecommunication systems emphasizes the practical advantages of assessing reliability from degradation data.

A Bayesian-reliability based multi-objective optimization for tolerance design of mechanical assemblies

Tolerances significantly affect the assemblability of components, the product's performance, and manufacturing cost in mechanical assemblies. Despite the importance of product reliability assessment, the reliability-based tolerance design of mechanical assemblies has not been previously considered in the literature. In this paper, a novel method based on Bayesian modeling is proposed for the tolerance-reliability analysis and allocation of complex assemblies where the explicit assembly functions are difficult or impossible to extract. To reach this aim, a Bayesian model is developed for tolerance-reliability analysis. Then, a multi-objective optimization formulation is proposed for obtaining the optimum tolerances of components to minimize cost and maximize product performance. Subsequently, Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed for solving multi-objective optimization. Then, the enhanced TOPSIS is used to find the best optimum tolerances from the optimum Pareto solutions. Using the importance vector concept, a sensitivity analysis approach is used to determine the effects of design variables on the product reliability level and improve assembly reliability to the desired level. Finally, to exhibit the applicability of the proposed method, a transmission planetary gear system is considered, and the obtained results are compared and discussed for verification.

Designing a Shape–Performance Integrated Digital Twin Based on Multiple Models and Dynamic Data: A Boom Crane Example

Abstract The digital twin, a concept that aims to establish a real-time mapping between physical space and virtual space, can be used for real-time analysis, reliability assessment, predictive maintenance, and design optimization of products. This article presents an enabling technology named shape–performance integrated digital twin (SPI-DT) and takes a boom crane as an example to illustrate how to design the SPI-DT step by step for the structural analysis of complex heavy equipment. The SPI-DT contains different types of models, such as an analytical model, a numerical model, and an artificial intelligence (AI) model. In addition, it leverages multisource dynamic data obtained by placing different sensors at multiple measurement positions. In the SPI-DT, the AI model plays a central role, invoking the numerical model and sensor data as the input to predict the structural performance of key components of heavy equipment, while the analytical model analyzes the structure of noncritical components with sensor data as input. This significantly improves the computational efficiency of the digital twin used for the structural analysis of complex heavy equipment, making the digital twin computationally affordable, and thus can be used for the safety assessment and damage protection of the equipment in the operation, as well as the design optimization of next-generation products. Moreover, to visually demonstrate the models and data in the SPI-DT, a three-dimensional application used to display and record the shape and performance information in real time during the operation of the boom crane is developed.

Reliability assessment and lifetime prediction of degradation processes considering recoverable shock damages

Many products degrade over time and their degradation processes could be affected by instantaneous shocks during field usage. Instantaneous shocks can cause incremental increases to the degradation signals through shock damages, and can also increase the degradation rates of products. In practice, some kinds of products can recover fully or partially from shock damages in a certain period of time. In this article, a degradation model for soft failure is proposed considering continuous degradation processes with recoverable shock damages for reliability assessment and lifetime prediction of products. The random component of the degradation processes is characterized by a Wiener process and the effect of instantaneous shocks on the degradation process is expressed by an exponential function with a residual effect for either partial or full recovery. The impact of shocks affecting the degradation rate is established to be proportional to the shock size. The resulting model includes some existing models as its special cases and can easily be extended to cases where the degradation process follows other random processes with independent increments. Numerical examples are presented to illustrate the applications of the proposed model. Sensitivity analysis and validation of the two-stage parameter estimation approach are conducted based on the simulation.

Effects of silicone lens aging on degradation kinetics of light-emitting diode package in various accelerated testing

Silicone is commonly used in light-emitting diode (LED) package as lens and/or encapsulation owing to its high light transmittance, large refractive index, and good thermal stability. However, the effect of silicone lens aging on the lumen decay and color shift of LED package is a considerable concern for package level reliability. This study empirically investigates the effects of silicone lens aging on lumen decay and color shift of LED package under three accelerated tests, namely, the constant stress-accelerated degradation test, step-up stress-accelerated degradation test, and step-down stress-accelerated degradation test (SDSADT). Results reveal that silicone lens aging substantially contributed to lumen decay and color shift of LEDs and considerably influenced the degradation kinetics of LED package. The color coordinates of LED package covered with aged silicone specimen in three testing methods exhibit a steady yellowing shift law at the same 45-degree direction. Silicone lens aging primarily reduces its transmittance to blue light as accumulated thermal oxidation and hydrolysis reaction, and its effect on the blue peak intensity of LED is independent of the stress-loaded order of step stress-accelerated degradation testing (SSADT). In addition, the effect law of silicone lens aging on LED lumen and color shift could be presented with the exponential and power function models, respectively. Lumen decay and color shift are mostly independent of the historical stress and loaded order in SSADT. The SDSADT testing manner more effectively distinguishes the color shift effect of thermal stress level compared with other accelerated tests. These findings are assumed to benefit the design and reliability assessment of LED products.

Reliability assessment of high-Quality new products with data scarcity

This study concerns the reliability assessment in high-quality new product development in which there is scarcity of data resulting from few or zero failures or the unavailability of failure time information. In such circumstances, traditional reliability assessment methods tend to be inadequate and ineffective. This paper describes a pragmatic approach adopted to address this practical issue. A Bayesian method using reparameterization of the Weibull distribution is proposed, which elicits priors in a meaningful way from technical experts and based on historical data. Unlike existing procedures found in the literature, the method here is developed from the perspective of availability of failure time data. Through a case study from the hard disk drive industry, it is demonstrated that the proposed method can provide an effective and practical solution to the challenging real-life problem. Furthermore, it is shown that failure time information has a significant effect on the inference about the Weibull shape parameter.

An Extended Building-In Reliability Methodology on Evaluating SRAM Reliability by Wafer-Level Reliability Systems

Advancement in integrated circuit (IC) brings a series of challenges on product reliability. In order to meet these challenges and fulfill customers’ requirements, we introduced the methodology of building-in reliability (BIR) into whole stages during IC manufacturing. The wafer-level reliability (WLR) is an essential element of the BIR system. Significant amount of costs, resources, and times are saved from the early detections on reliability deficiencies at design and development stages. After successful mass production, hidden reliability risks can also be timely identified before shipment. Currently, the process reliability has been successfully evaluated by WLR platform. However, the product reliability, which covers much wider reliability factors, has not been effectively covered by WLR. Currently, we still rely on the conventional package-level reliability (PLR) tests to assess product reliability. In this paper, we report how the classical static random access memory (SRAM) is transplanted into the WLR system, which serves as an efficient platform to detect reliability weakness. In our extended BIR methodology, by reasonable test structure and pattern designs, proper electric parameters selections, test methods optimizations, we can thoughtfully consider inherent failure mechanisms and process fluctuations in order to build quantitative reliability models, which are essential to our proposed system. The quantitative reliability model was not seen in the similar WLR approaches and this may explain why these previous proposals failed. Finally, we report the obtained robust correlations between single-bit cell wear-out and package-level SRAM degradations, which is further validated by conventional HTOL tests. Our approaches provide opportunities not only on early detecting reliability weakness, but also on reliability assurance after product deliveries. These two contributions are essential and especially crucial for advanced technology developments.

RETRACTED: A Review on Modeling and Analysis of Accelerated Degradation Data for Reliability Assessment

Abstract Accelerated degradation testing (ADT) has been recognized as an essential and effective approach for the reliability assessment of high reliability long-lifetime products, and can provide various health management strategies to ensure the safe and economical operation of deteriorating products. Studies on how to best assess such reliability have recently gained popularity owing to the rapid advances in accelerated degradation data monitoring techniques. However, because of its complicated relationship with observable degradation information, there have been no systematic reviews focused particularly on reliability assessment based on accelerated degradation data. As such, this paper reviews recent developments in the modeling and analysis of accelerated degradation data for reliability assessment. After a brief introduction of the fundamentals of ADT, this paper concentrates on a review of the reliability modeling and statistical analysis of ADT technology from four aspects, namely performance degradation modeling, acceleration modeling, identification of the consistency in failure mechanism and the model parameter estimation. We systematically review the models and approaches reported in the latest literature, and finally highlight future research challenges and possible development trends.

Reliability assessment for products with two performance characteristics based on marginal stochastic processes and copulas

Many highly reliable products (systems) usually have multiple dependent degradation processes because of their complex structure. Therefore, it is important to investigate the multivariate degradation models along with the reliability assessment in the stochastic modeling. This article proposes a framework for bivariate degradation modeling based on hybrid stochastic processes for products with two performance characteristics (PCs), the dependence of which is captured by copula functions. Considering heterogeneities among product units, different random effects are introduced in marginal stochastic processes. Then two classes of reliability functions based on joint posterior distributions are derived. In addition, a simulation study indicates that the holistic Bayesian parameter estimation method is better than the two-step Bayesian parameter estimation method. Finally, this article concludes with a case application to demonstrate the effectiveness of the proposed model.

Application of diffusion-non-monoton distribution to model the radio-electronic equipment operation process

The emergence of reliability as an applied mathematical discipline is associated with the 50-60 years of the last century, when large and complex technical systems began to be created in various branches of technology. In this regard, an acute reliability problem arose, that is, ensuring the functioning and operability of these complex and expensive systems. The whole variety of reliability studies is aimed at solving the following three problems: assessment and prediction of product reliability at the design stages (a priori methods); experimental evaluation of reliability indicators, that is, confirmation of the projected level of reliability according to the results of tests or operation (posterior methods); taking measures to achieve and ensure a given level of reliability by optimizing the maintenance strategy, redundancy, spare parts, etc. (optimization problems) The traditional has developed a certain division in the areas of theory and practice of reliability of machines (mechanical objects, technical systems containing mechanical components) and equipment (electronic products, technical devices containing electronic and radio elements). The main tasks of reliability of machines and equipment - the establishment of patterns of failure and the assessment of quantitative indicators of reliability - can be solved in two different ways. To date, the direction based on the use of only probabilistic concepts (purely probabilistic theory) has received the greatest development in the theory and practice of reliability. The second way to establish quantitative indicators of reliability, in contrast to a purely probabilistic approach, is based on the study of mechano-physico-chemical properties and some physical parameters of products characterizing the technical condition of the latter using probabilistic methods. The methodology for establishing quantitative reliability indicators based on the study of certain physical parameters characterizing the technical condition of products consists in identifying the kinetic laws of degradation processes (building mathematical models of degradation processes) and determining the analytical relationship between these laws and reliability indicators. The article discusses the use of diffusion-nonmonotonic distribution for modeling the process of operation of electronic equipment. Particular attention is paid to the determination of point estimates of distribution parameters based on the results of operational observations.