The most common control chart used to monitor count data is based on Poisson distribution, which presents a strong restriction: The mean is equal to the variance. To deal with under‐ or overdispersion, control charts considering other count distributions as Negative Binomial (NB) distribution, hyper‐Poisson, generalized Poisson distribution (GPD), Conway–Maxwell–Poisson (COM‐Poisson), Poisson–Lindley

In the traditional industrial verification process, when the aim is the compliance to assigned specifications, it is difficult to find an affordable statistical method for the purpose. Most data tables in industrial procedures and standards deal with tolerance limits neglecting the potential needs to verify assigned specification limits. A two‐sided tolerance interval, combined with a bivariate statistical

Managing failure dependence of complex systems with hybrid uncertainty is one of the hot problems in reliability assessment. Epistemic uncertainty is attributed to complex working environment, system structure, human factors, imperfect knowledge, etc. Probability‐box has powerful characteristics for uncertainty analysis and can be effectively adopted to represent epistemic uncertainty. However, arithmetic

In actual engineering, material properties, load effects, and other factors of mechanical structures change due to long‐term use. In order to understand the operation of a mechanical structure in real time, it is crucial to obtain the dynamic trajectory of its reliability. Considering the time variability of a mechanical structure over time, uncertain random variables are introduced to express the

As an essential part in product reliability design procedure, reliability allocation can connect the reliability index between the overall product and its multiple subsystems. To obtain a reasonable reliability allocation scheme, especially for limited sample size circumstances commonly encountered in aeronautic and astronautic fields, an information fusion allocation method is constructed in the current

Since any risk in the safety‐critical systems (SCSs) might lead to a terrible disaster, the utmost quality attribute of these systems is safety. Researchers are putting their efforts to ensure the safety of such systems. This paper summarizes the state‐of‐the‐art in the area of the safety attribute of such critical systems. The in depth literature survey is performed to explore the several methods/models

Nonregular designs are a preferable alternative to regular resolution IV designs because they avoid confounding two‐factor interactions. As a result nonregular designs can estimate and identify a few active two‐factor interactions. However, due to the sometimes complex alias structure of nonregular designs, standard screening strategies can fail to identify all active effects. In this paper, we explore

A control chart is one of the statistical process techniques that is used to monitor different processes. Some processes are characterized by functions or profiles, and a profile is a functional relationship between the dependent and independent variable(s) used to monitor the quality of the process. Several research studies were conducted on linear profiling where only fixed effects are considered

In this paper, we generalize the Birnbaum‐Saunders (BS) distribution by two ways. One is based on the mixture representation of BS distribution, and a flexible weight is adopted to describe the kurtosis of the distribution. The other way is based on the transformation property of BS distribution, and we incorporate a power parameter in the transformation to describe the skewness of the distribution

Motivated by real‐world applications of satellites and wireless sensor networks, this paper models and evaluates a dynamic k‐out‐of‐n phase‐AND mission system (k/n‐PAMS). The mission task conducted by a k/n‐PAMS involves multiple consecutive phases; the mission is successful as long as the task is successful in any of the phases. Due to factors, such as scheduled maintenance, location changes in task

In many applications, the Poisson count data with varying sample sizes are monitored using statistical process control charts. Among these applications, the weighted CUSUM charts are developed to deal with the effect of the varying sample sizes. However, some of them use limited information of the sample size or the count data while assigning the weights. To gain more information of the process, the

The benefits of sequential design of experiments have long been described for both model‐based and space‐filling designs. However, in our experience, too few practitioners take advantage of the opportunity afforded by this approach to maximize the learning from their experimentation. By obtaining data sequentially, it is possible to learn from the early stages to inform subsequent data collection,

Reliability growth models are commonly used in the Department of Defense (DoD) to plan, track, and project reliability during system acquisition and testing. We describe two commonly used classes of reliability growth models for continuous failure time data and the metrics appropriate for their use. We also present two Bayesian reliability growth models that are based on the DoD models. The Bayesian

The homogeneously weighted moving average (HWMA) control chart is famous to identify small deviations in the process mean. The plotting statistic of the HWMA chart assigns equal weight among the previous samples as compared to the plotting statistic of the exponentially weighted moving average chart. We propose a new HWMA chart that uses the plotting statistic of the cumulative sum chart. The run length

We consider change‐point detection and estimation in sequences of functional observations. This setting often arises when the quality of a process is characterized by such observations, called profiles, and monitoring profiles for changes in structure can be used to ensure the stability of the process over time. We propose a nonparametric approach using a single index model (SIM), where instead of

In this paper, we proposed the Bayesian exponentially weighted moving average (EWMA) control charts for mean under the nonnormal life time distributions. We used the time between events data which follow the Exponential distribution and proposed the Bayesian EWMA control charts for Exponential distribution and transformed Exponential distributions into Inverse Rayleigh and Weibull distributions. In

This article presents the expected Bayesian (E‐Bayesian) estimation of the scale parameter, reliability and failure rate functions of two‐parameter bathtub‐shaped lifetime distribution under type‐II censoring data with. Squared error loss function and gamma distribution as a conjugate prior distribution for the unknown parameter are used to obtain the E‐Bayesian estimators. Also, three different prior

Monitoring surgical outcome quality by risk‐adjusted control charts has attracted wide attention. The hidden medical errors may cause increasing of adverse events such as infection, rehospitalization, and even death. Quickly and timely detecting abnormal changes of surgical performance helps reduce the probability of adverse events and improve health care quality. Most existing monitoring schemes focus

Observations with missing data are a typical predicament in the context of multivariate statistical process control (MSPC). When process control is performed using a T 2 control chart of the principal components (PCs), several score imputation methods have been proposed. Some of these lead to estimators with good properties. However, there are no detailed studies pertaining the performance of Phase

Lifetime data collected from reliability tests are among data that often exhibit significant heterogeneity caused by variations in manufacturing, which makes standard lifetime models inadequate. Finite mixture models provide more flexibility for modeling such data. In this paper, the Weibull‐log‐logistic mixture distributions model is introduced as a new class of flexible models for heterogeneous lifetime

System reliability optimization is a key element for a competitive and safe industrial plant. This paper addresses the multiobjective system reliability optimization in the presence of fuzzy data. A framework solution approach is proposed and based on four steps: defuzzify the data into crisp values by the ranking function procedure, the defuzzified problems are solved by the non‐sorting genetic algorithms

In practical situations, the underlying process distribution sometimes deviates from normality and their distribution is partially or completely unknown. In that instance, rather than staying with/depending on the conventional parametric control charts, we consider non‐parametric control charts due to their exceptional performance. In this paper, a new non‐parametric double homogeneously weighted moving

A mixed exponentially weighted moving average (EWMA)–progressive mean (PM) control chart (regarded as MEP) has been recently proposed in the literature for monitoring the process mean. Unfortunately, the variance of MEP statistic is incorrect. In this article, we provide the correct variance of charting statistic along with the corresponding control limits and we also evaluate the run‐length characteristics

A unified statistical process control (SPC) scheme is developed to monitor work‐process duration of repetitive processes (constant work content), semi‐repetitive (work content somewhat varies between cycles) and memoryless (no typical work content). As a basic paradigm to develop the new scheme, we monitor surgery duration (SD), known to represent durations of all three types of work processes. Recently

Hypothesis testing of C p k is an essential part for decision making on process capability. The difficulty to test the hypothesis of C p k is the complexity of the natural estimator C ̂ p k distribution even under the normal distribution. Thus, traditional methods of the hypothesis testing of C p k based on the natural estimator C ̂ p k only give the approximate test method under the normal distribution

For modern complex system, quality has become a serious and difficult problem that restricts the generation of combat effectiveness. Withal, based on domestic and foreign research and analysis, this paper puts forward a trade‐off method for complex system reliability, maintainability, supportability, testability (RMST) design, which is suitable for product design stage. First, aiming at the uncertain

Nonparametric control charts are used in process monitoring when there is insufficient information about the form of the underlying distribution. In this article, we propose a triple exponentially weighted moving average (TEWMA) control chart based on the sign statistic for monitoring the location parameter of an unknown continuous distribution. The run‐length characteristics of the proposed chart

There are differences among sampling data and representation types of uncertain interval, fuzzy and random variables, which increases the complexity of structure reliability analysis. A α, β‐Cut‐FORM is proposed to analyze structure reliability considering the mixed uncertain variables. Fuzzy variables are optimized on the interval under two cut sets (α, β) based on the theory of cut set optimization

In our recent paper “Three‐Level Designs: Evaluation and Comparison for Screening Purposes”, by the same authors, we investigated and compared the original definitive screening designs and the designs that were constructed from weighing matrices. For this purpose, we used the generalized resolution and minimum aberration criteria as well as the projection estimation capacity criterion from the literature

In this paper, we discuss the statistical analysis of a constant‐stress accelerated dependent competing failure model under progressively type‐II censoring based on a copula function. The dependence structure of lifetimes is constructed when the copula is a bivariate Clayton copula. The maximum likelihood estimations (MLEs) of the model parameters are derived. We also get the coverage probability of

Phase I is crucial for the success of the overall statistical process control (SPC) and monitoring regime. Shewhart‐type charts are recommended in this phase because of their broader shift detection ability. In this paper, a Phase I Shewhart‐type X ¯ chart is considered for the balanced random effects (also called a variance components) model. The proposed methodology takes proper account of the effects

Traditional machine tool reliability modeling methods take static parts as the research object, ignoring the characteristic that the function and performance of computer numerical control (CNC) machine tool are ultimately driven by its most basic actions, and the traditional reliability modeling methods do not fully consider the randomness of machine tool failure. In view of this, this paper gave an

When developing a product, it is important to consider product performance from a user perspective. This type of evaluation can be done through operational testing—assessing the ability of representative users to satisfactorily accomplish tasks with the product in operationally representative environments. This process can be expensive and time‐consuming, but is critical to understanding whether the

In this paper, a competing risks model based on the generalized progressive hybrid censored two‐parameter Rayleigh distributions is studied under the assumption that the lifetime distributions of failure causes are identically distributed with same location and different scale parameters. We obtain maximum likelihood estimates of unknown parameters with associated existence uniqueness. The approximate

For effective integrity management of marine renewable energy systems in the dynamic and uncertain ocean environments, understanding the failure dynamics is crucial. The cost of investment in marine/offshore renewable energy infrastructures and the associated cost due to failure and loss of energy production necessitate a predictive monitoring methodology that is dynamic and adaptive. This paper presents

The Mann‐Whitney (MW) statistic is one of the most recommended two‐sample statistical tests when the assumption of normality fails to hold due to its robustness and fascinating properties especially when small sample sizes are involved. In order to improve the sensitivity of the generally weighted moving average (GWMA) monitoring scheme toward the detection of large shifts, in this paper, a new distribution‐free

The improvement of mechanical parts inherent reliability has an impact on the reputation and performance of the company. To estimate the inherent reliability of products more conveniently and economically, a hidden quality cost‐production cost (HQC‐PC) reliability prediction model is put forward. To estimate the hidden quality cost (HQC) of products more accurately, a quadratic exponential quality

During the design phase of a control chart, the determination of its exact run length properties plays a vital role for its optimal operation. Markov chain or integral equation methods have been extensively applied in the design phase of conventional control charts. However, for distribution‐free schemes, due to the discrete nature of the statistics being used (such as the sign or the Wilcoxon signed

Control chart is a useful tool to monitor the performance of the industrial or production processes. Control charts are mostly adopted to detect unfavorable variations in process location (mean) and dispersion (standard deviation) parameters. In the literature, many control charts are designed for the monitoring of process variability under the assumption that the process mean is constant over time

Control charts are very popular quality tools used to detect and control industrial process deviations in statistical process control. The current paper presents a new triple exponentially weighted moving average (TEWMA) control chart for monitoring the process dispersion (named as S 2 ‐TEWMA chart), based on a three‐parameter logarithmic transformation of the sample variance. A performance evaluation

Monitoring of the social networks for detecting anomalous behavior could be vital for the system's survival. This anomalous behavior could raise from any changes in behavior or attributes of a particular individual or groups of individuals in the network and causes structural changes. Multivariate statistical process control charts are effective tools for this purpose while Exponential Random Graph

Effective and early fault detection and diagnosis techniques have tremendously enhanced over the years to ensure continuous operations of contemporary complex systems, control cost, and enhance safety in assets‐intensive industries, including oil and gas, process, and power generation. The objective of this work is to understand the development of different fault detection and diagnosis methods, their

The CUSUM (C) charts are well recognized as a potentially advanced process monitoring tools because of their sensitivity against small and moderate shifts. In this paper, we first improve the sensitivity of the Brownian motion–based C (BC) chart with an appropriate transformation, named new BC (NBC) chart, for monitoring moderate and large shifts in the mean of a normal process. Then, using the control

With great pleasure we introduce this Special Issue of Quality and Reliability Engineering International which is dedicated to the European Network for Business and Industrial Statistics (ENBIS). ENBIS is a forum for the development and improvement of statistical methods and their dissemination and application to the European business and industry. This Special Issue includes 16 articles mostly from

Key responses of manufacturing processes are often represented by spatially or time‐ordered data known as functional data. In practice, these are usually treated by extracting one or few representative scalar features from them to be used in the following analysis, with the risk of discarding relevant information available in the whole profile and of drawing only partial conclusions. To avoid that

Modern engineering systems have become increasingly complex and at the same time are expected to be developed faster. To shorten the product development time, organizations commonly conduct accelerated testing on a small number of units to help identify failure modes and assess reliability. Many times design changes are made to mitigate or reduce the likelihood of such failure modes. Since failure‐time

Discrete‐time Bayesian network (DTBN) is a popular tool for the reliability analysis of dynamic systems, which, however, is insufficient in analyzing the reliability of multilevel system (MLS) with warm spare (WSP) gates. Additionally, conventional DTBNs are not able to consider the situation that dormant components and primary components may fail during the same time interval. To this end, this paper

In the statistical process control, the most useful tool to monitor the manufacturing processes in the industries is the control chart. Quality practitioners always desire the charting structure that identifies sustainable changes in the monitoring processes. The sensitivity of the control chart is improved when additional correlated auxiliary information about the study variable is introduced. The

This paper proposes a novel adaptive maintenance policy for degrading systems subject to hard failure. Compared with traditional condition‐based maintenance policies, the proposed predictive maintenance policy makes maintenance decisions adaptively based on model prognostic results. The prognostic model is continuously updated based on newly inspected data. The inspection times and preventive maintenance

Competing risks model is considered with dependence causes of failure in this paper. When the latent failure times are distributed by a bivariate Gompertz model, statistical inference for the unknown model parameters is studied from classical and Bayesian approaches, respectively. Under a generalized progressive hybrid censoring, maximum likelihood estimators of the unknown parameters together with

The lead‐acid battery has been widely used in various fields. In civil aviation aircraft, it plays a vital role in the power system to maintain normal operation during the flight mission. Thus, an effective abnormal detection system for monitoring and diagnosing the status of aircraft lead‐acid battery is essential to ensure its safety and reliability. This paper aims to effectively identify aircraft

Statistical quality control is used to improve performance of processes. Since most of the processes are multivariate in nature, multivariate process capability indices (MPCIs) have been developed by many researchers depending on the context. However, it is generally difficult to understand and calculate MPCIs, compared to their univariate counterparts like C p , C p k , and so on. This paper discusses

Failure mode and effect analysis (FMEA) is a useful technique to identify and quantify potential failures. FMEA determines a potential failure mode by evaluating risk factors. In recent years, there are many works improving FMEA by allowing multiple experts to use linguistic term sets to evaluate risk factors. However, it is important to design a framework that can consider both the weight of risk

Profile monitoring is one of the methods used in statistical process control ( S P C ) to understand the functional relationship between response and explanatory variables by tracking this relationship and estimating parameters. SPC is done in two phases: In Phase I , a statistical model is created and its parameters estimated using historical data. Phase I I implements the statistical model and monitors

Advancements in information technology have made various industrial equipment increasingly sophisticated in recent years. The remaining useful life (RUL) of equipment plays a crucial important role in the industrial process. It is difficult to establish a functional RUL model as it requires the fusion of time‐series data across different scales. This paper proposes a long‐short term memory neural network

Time between events (TBE) charts are used in high‐yield processes where the rate of occurrences is very low. In the current article, we propose a triple exponentially weighted moving average control chart to monitor TBE (regarded as triple exponentially weighted moving average TEWMA‐TBE chart) modeled by a gamma distribution. One‐ and two‐sided schemes of the proposed chart are designed and compared

In this paper, we are interested in monitoring the stability of a Weibull process mean. We introduce a simplified variable sample size (SVSS) procedure, which consists of using alternately sample sizes n A and n B with n A > n B , to improve the performance of the traditional X ¯ control chart (a fixed sample size n). Operationally, the proposal is relatively simple and its adoption yields a faster

This paper proposes a parameter‐free Kullback‐Leibler information control chart for monitoring sustained shifts in the process mean of a normally distributed process in phase II. Two plotted statistics are provided. One is based on our backward empirical sequential test, the other is based on the maximum log‐likelihood ratio change point method. These two achieve similar performances for the control

Circular prediction regions are used in ballistic testing to express the uncertainty in shot accuracy. We compare two modeling approaches for estimating circular prediction regions for the miss distance of a ballistic projectile. The miss distance response variable is bivariate normal and has a mean and variance that can change with one or more experimental factors. The first approach fits a heteroskedastic