Identifying time of a monotonic change in the fraction nonconforming of a high-quality process

When a signal is detected by control charts, a search begins to identify and eliminate the sources of this signal. Knowing when a process has changed is very helpful for this purpose. The unknown special point that the process changed for the first time is referred to as change point. In this paper, we propose a maximum-likelihood estimator for the behavior model of the process fraction nonconforming in a high-quality process monitored with a cumulative count of conforming (CCC) control chart. We estimate the time of change without requiring the prior knowledge of the change type rather than we assume the type of change present belongs to a family of monotonic changes. Then, we compare the performance of the proposed change point estimator relative to estimators for the process fraction nonconforming change point derived under a single step and a linear trend change assumption. We do this for a number of monotonic change types following a signal from a CCC control chart. Finally, the application of the proposed change point estimator is shown through a real case.     

Nigella sativa L. improves lipid profile and prevents atherosclerosis: Evidence from an experimental study on hypercholesterolemic rabbits

The effects of Nigella sativa (NS) on lipid profile, C-reactive protein, oxidized LDL, antioxidant capacity, Apo A and Apo B and fatty streak formation in hypercholesterolemic male rabbits were examined. Fifteen rabbits were distributed into three groups of five each [normal diet, hypercholesterolemic diet (1% cholesterol) and hypercholesterolemic diet (1% cholesterol) supplemented with 5% NS]. They received rabbit laboratory chow diet for a period of 8 weeks. At the start and end of the study, fasting blood was taken from all animals. NS significantly decreased fatty streak formation as well as total cholesterol (TC) and low-density lipoprotein (LDL) in hypercholesterolemic male rabbits. NS showed positive effects on other factors (triacylglycerol, high-density lipoprotein, C-reactive protein, oxidized LDL, antioxidant capacity, Apo A and Apo B), but these were insignificant. Based on favorable efficiency of NS on TC and LDL reduction and its anti-atherogenic cardioprotective properties, it is suggested using this plant with fat-rich diets simultaneously may reduce their adverse health effects.     

Modeling the Solubility of Carbon Dioxide and 1,1,1,2-Tetrafluoroethane in Ionic Liquids Using the van der Waals and Generic Redlich–Kwong Equations of State

Theoretical Foundations of Chemical Engineering - In this study, we have examined the modeling of gas solubility in twenty room temperature ionic liquids based on the van der Waals and generic...     

Location-aware hazardous litter management for smart emergency governance in urban eco-cyber-physical systems

Multimedia Tools and Applications - Smart city management is facing a new challenge from littered face masks during COVID-19 pandemic. Addressing the issues of detection and collection of this...     

Sustainable approach toward synthesis of green functional carbonaceous 3-D micro/nanostructures from biomass

This study proposes a novel technique to synthesize functional carbonaceous three-dimensional (3-D) micro/nanocompounds from agricultural by-products using femtosecond laser irradiation. Biowastes of rice husk and wheat straw are value-engineered to carbonaceous structures in a single-step process under ambient conditions. Our results demonstrate that by controlling the laser fluence, structures with a variety of different morphologies from nanostructures to microstructures can be achieved. Also, the results indicate that altering the laser processing parameters influences the chemical composition of the synthesized structures. This sustainable approach presents an important step towards synthesizing 3-D micro/nanofibrous compounds from biowaste materials. These structures, as-synthesized or as nanocomposite fillers, can have practical uses in electronic, sensing, biological, and environmental applications.     

A comparative study on the free volume theories for diffusivity through polymeric membrane in pervaporation process

In this work, free volume theories are coupled with a thermodynamic model and generalized Fick's law to develop a mass transfer model based on solution‐diffusion mechanism for pervaporation process with a hydrophobic polymeric membrane. The Wesselingh, Fujita and Vrentas‐Duda's theories are used to calculate concentration‐dependent diffusion coefficient of permeants inside polydimethylsiloxane membrane. The sorption and pervaporation experiments on aqueous ethanol solutions are performed to validate the sorption and pervaporation models. The results reveal that the proposed models are able to predict influences of feed concentration and temperature as well as permeate‐side pressure on partial fluxes through the membrane. The comparative investigation indicated that Wesselingh's free volume theory underestimated the diffusion coefficients inside the membrane and the accuracy of the model used this theory is very low for prediction of the permeation flux. Generally, Fujita and Vrentas‐Duda's theories are found to be much more accurate especially for dilute aqueous feed solutions. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40581.     

Phase‐I monitoring of log‐linear model‐based processes (a case study in health care: Kidney patients)

Processes with multiple correlated categorical quality characteristics are called multivariate categorical processes. These processes are usually shown by contingency tables and are characterized by log‐linear models. In this paper, two monitoring approaches including likelihood ratio test (LRT) and F test are developed to monitor multivariate categorical processes based on the contingency table in Phase I. In addition, a change point estimator for multivariate categorical processes is developed in Phase I. The performances of the two proposed approaches are evaluated in terms of probability of signal, while the performance of the proposed change point estimator is evaluated in terms of accuracy and precision criteria through simulation experiments. Meanwhile, we compare the performance of the two proposed control charts with an existing control chart called “?2LRT” control chart for multivariate categorical processes. In the end, a typical application of the proposed methods is illustrated in a real‐world health care system.     

Monitoring Bernoulli processes considering measurement errors and learning effect

This paper presents the effect of measurement errors and learning on monitoring processes with individual Bernoulli observations. A cumulative sum control chart is considered to evaluate the possible impacts of measurement errors and learning. We propose a time‐dependent learning effect model along with measurement errors and incorporate them into the Bernoulli CUSUM control chart statistic. The performance of the Bernoulli CUSUM control chart is then merely assessed by comparing the average number of observations to signal (ANOS) under two proposed conditions with the condition of no possible errors. Thus, the ANOS values are obtained under different proportions of non‐conforming items, once considering errors due to measurement by inspectors, and once considering both errors and learning effect together. The experimental results show that the efficiency of the control chart to detect assignable causes deteriorates in the presence of measurement errors and enhances when learning affects operators' performance. The proposed approach has a potential to be used in monitoring high‐quality Bernoulli processes as well as disease diagnosis, and other health care applications with Bernoulli observations.     

Sum of Squares Control Charts for Monitoring of Multivariate Multiple Linear Regression Profiles in Phase II

In this paper, we propose four control charts for simultaneous monitoring of mean vector and covariance matrix in multivariate multiple linear regression profiles in Phase II. The proposed control charts include sum of squares exponential weighted moving average (SS‐EWMA) and sum of squares cumulative sum (SS‐CUSUM) for monitoring regression parameters and corresponding covariance matrix and SS‐EWMARe and SS‐CUSUMRe control charts for monitoring mean vector and covariance matrix of residual. Proposed methods are able to identify the out‐of‐control parameter responsible for shift. The performance of the proposed control charts is compared with existing method through Monte‐Carlo simulations. Moreover, the diagnostic performance of the proposed control charts is evaluated through simulation studies. The results show better performance of the proposed control charts rather than competing control chart. Finally, the applicability of the proposed control charts is illustrated using a real case of calibration application in the automotive industry. Copyright © 2016 John Wiley & Sons, Ltd.