A hybrid homogeneously weighted moving average control chart for process monitoring: Discussion

The sensitivity of a monitoring scheme depends on many factors including the variance of the charting statistic which is very important in the computation of the control limits. This paper discusses the computation of the variance of the recently proposed hybrid homogeneously weighted moving average (HHWMA) $\overline{X}$ scheme which was based on an incorrect assumption. The correct variance is used to evaluate the run-length characteristics of the HHWMA $\overline{X}$ scheme. It is observed that the incorrect variance has a significant impact on the sensitivity (or performance) of the HHWMA $\overline{X}$ scheme.     

On monitoring the process mean of autocorrelated observations with measurement errors using the w-of-w runs-rules scheme

Runs-rules have been widely used since the 1950s in industrial and nonindustrial process monitoring applications to improve the performance of basic and other traditional monitoring schemes. However, none of the studies on runs-rules have accounted for a process with a combined effect of measurement errors and autocorrelation. Hence, in this paper, the use of the w-of-w runs-rules to improve the performance of the Shewhart $\overline{X}$ scheme using an additive model with a constant variance and a first-order autoregressive model is proposed. To reduce the combined negative effect of measurement errors and autocorrelation, we implement a sampling strategy based on rational subgroups in which (a) multiple measurements per item are taken (instead of a standard single measurement) and (b) non-neighboring observations are gathered. Moreover, the latter sampling strategy is incorporated into the values of probability elements of a Markov chain matrix which is used to derive some closed-form expressions for the zero- and steady-state run-length distribution. The main finding of this study is that, with respect to some overall performance measures, the proposed scheme outperforms the existing Shewhart $\overline{X}$ scheme by a significant margin. A real-life example is used to illustrate the practical implementation of the proposed scheme.     

Generally weighted moving average monitoring schemes: Overview and perspectives

An overview of monitoring schemes from a class called generally weighted moving average (GWMA) is provided. A GWMA scheme is an extended version of the exponentially weighted moving average (EWMA) scheme with an additional adjustment parameter that introduces more flexibility in the GWMA model as it adjusts the kurtosis of the weighting function so that the GWMA scheme can be designed such that it has an advantage over the corresponding EWMA scheme in the detection of certain shift values efficiently. The parametric and distribution-free GWMA schemes to monitor various quality characteristics and its existing enhanced versions (ie, double GWMA, composite Shewhart-GWMA, mixed GWMA-CUSUM, and mixed CUSUM-GWMA) have better performance than their corresponding EWMA counterparts in many situations; hence, all such existing research works discussing GWMA-related schemes (ie, 66 publications in total) are documented and categorized in such a manner that it is easy to identify research gaps. Finally, a number of possible future research ideas are provided.     

Distribution-free composite Shewhart-GWMA Mann-Whitney charts for monitoring the process location

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 phase II composite Shewhart-GWMA (CSG) scheme is proposed using the MW U statistic. The performance of the proposed scheme is investigated using the average run-length (ARL) and average extra quadratic loss (AEQL) values through extensive simulations. The performance of this newly proposed monitoring scheme is found to be superior when compared to numerous memory-type MW schemes (some existing and others introduced in this paper) in many situations. An illustrative example is given to demonstrate the implementation of the CSG MW U scheme using real-life data.     

Distribution-free double-sampling precedence monitoring scheme to detect unknown shifts in the location parameter

In most applications, parametric monitoring schemes are used to monitor the majority of industrial and nonindustrial processes in order to improve the quality of the outputs or services. However, parametric monitoring schemes are known to underperform when the normality assumption is not met or when there is not enough information about the symmetry or asymmetry nature of the process underlying distribution. Hence, in this paper, a new nonparametric Phase II Shewhart-type double-sampling (DS) monitoring scheme based on the precedence statistic is proposed in order to efficiently monitor quality processes when the underlying process distribution departs from normality. The performance is investigated using the average run length (ARL), standard deviation of the run length (SDRL), expected ARL (EARL) and expected average number of observations to signal (EANOS), and the average sample sizes (ASS) metrics. The latter metrics are computed using Monte Carlo simulation and exact formulae. In general, it is shown that the new DS precedence scheme outperforms the existing basic Shewhart precedence scheme with and without supplementary runs rules in many situations. A real-life illustrative example based on a filling process of milk bottles is provided to demonstrate the application and implementation of the new DS precedence monitoring scheme.     

An application of paired quasilinearization on double‐diffusive convection flow over a cone embedded in a porous medium in the presence of nanoparticles

Mixed convection flow of a nanofluid near a vertical cone embedded in a a porous medium with Soret and Dufour effects is exercised. The bearing of a porous medium is recounted by the Darcy model. The partial differential equations, modeling the concerned problem, is nondimensionalised by implementing compatible transformations, which results in a similar form. A new paired spectral quasilinearization method is adopted to get the accurate numerical solution. Convergence and accuracy of the solution is elaborated by analyzing the norm of residual and solution errors. Alteration of velocity, temperature, nanoparticle and solute concentration profiles due to flow controlling parameters, namely, Brownian motion, thermophoresis, Soret, Dufour, Lewis number, and buoyancy ratio is outlined by reproducing the obtained numerical solution in graphs and tables. Analysis reveals that the flow profiles are greatly influenced by the physical parameters under investigation.     

MHD mixed convective radiative flow of Eyring‐Powell fluid over an oscillatory stretching sheet using bivariate spectral method on overlapping grids

The bivariate spectral quasilinearization method (BSQLM) on overlapping grids is presented and applied in the analysis of unsteady magnetohydrodynamic mixed convection flow of Eyring‐Powell fluid over an oscillatory stretching sheet embedded in a non‐Darcy porous medium with nonlinear radiative heat flux and variable thermophysical properties. The fluid properties, namely the fluid viscosity, thermal conductivity, and mass diffusivity, are assumed to vary with temperature. It is assumed that the first‐order chemical reaction with heat generation/absorption takes place in the flow. The flow domain is subject to uniform transverse magnetic field perpendicular to the stretching surface. The transformed flow equations are solved numerically using BSQLM on overlapping grids. The convergence properties and accuracy of the method are assessed. The proposed method is computationally efficient, and it gives stable and highly accurate results after few iterations and using few grid points in each subinterval. The improved accuracy rests upon the use of the overlapping grid, which produces sparse coefficient matrices that are easy to invert and have small condition numbers. The effects of physical parameters on the flow fields, local skin friction, the Nusselt number, and the Sherwood number are exhibited through graphs and tables. Amongst other findings, we found that the amplitude of the fluid flow along with flow characteristics may efficiently improve through the utilization of variable fluid viscosity. Heat and mass transportation processes enhance with the inclusion of nonlinear radiative heat flux, temperature‐dependent thermal conductivity, and mass diffusion coefficient, whereas they diminish with the increase in the local inertia coefficient. The current flow analysis can be useful in various engineering applications including paper production, polymer solution, glass blowing, extrusion of thermal system manufacturing process, and heat transportation enhancement.     

One‐sided runs‐rules schemes to monitor autocorrelated time series data using a first‐order autoregressive model with skip sampling strategies

In some industrial or health‐related processes, it makes more practical sense to monitor either an increase only or a decrease only in the quality characteristic of interest. Consequently, in this paper, we propose four one‐sided Shewhart charts supplemented with runs‐rules to monitor the mean of autocorrelated normally distributed samples using a stationary first‐order autoregressive model. To counteract the negative effect of autocorrelation, we implement a sampling strategy which involves sampling of non‐neighboring observations to form rational subgroups. The Markov chain technique is used to derive zero‐state and steady‐state closed‐form expressions of the specific shift performance metric, ie, average run‐length (ARL). Moreover, we compute the expected ARL metric which evaluates each monitoring scheme based on all specified range of possible values of the shift parameter, or more specifically, from a global point of view and thus gives a different perspective from the specific shift ARL metric. We observed that the steady‐state improved w‐of‐w and the improved 2‐of‐(H + 1) schemes yield a better overall performance than their corresponding basic counterparts for all different levels of autocorrelation. A real‐life example is provided to illustrate the implementation of the monitoring schemes proposed here.     

Assessing Secure OpenID-Based EAAA Protocol to Prevent MITM and Phishing Attacks in Web Apps

To secure web applications from Man-In-The-Middle (MITM) and phishing attacks is a challenging task nowadays. For this purpose, authentication protocol plays a vital role in web communication which securely transfers data from one party to another. This authentication works via OpenID, Kerberos, password authentication protocols, etc. However, there are still some limitations present in the reported security protocols. In this paper, the presented anticipated strategy secures both Web-based attacks by leveraging encoded emails and a novel password form pattern method. The proposed OpenID-based encrypted Email’s Authentication, Authorization, and Accounting (EAAA) protocol ensure security by relying on the email authenticity and a Special Secret Encrypted Alphanumeric String (SSEAS). This string is deployed on both the relying party and the email server, which is unique and trustworthy. The first authentication, OpenID Uniform Resource Locator (URL) identity, is performed on the identity provider side. A second authentication is carried out by the hidden Email’s server side and receives a third authentication link. This Email’s third SSEAS authentication link manages on the relying party (RP). Compared to existing cryptographic single sign-on protocols, the EAAA protocol ensures that an OpenID URL’s identity is secured from MITM and phishing attacks. This study manages two attacks such as MITM and phishing attacks and gives 339 ms response time which is higher than the already reported methods, such as Single Sign-On (SSO) and OpenID. The experimental sites were examined by 72 information technology (IT) specialists, who found that 88.89% of respondents successfully validated the user authorization provided to them via Email. The proposed EAAA protocol minimizes the higher-level risk of MITM and phishing attacks in an OpenID-based atmosphere.