On Effective Dual Use of Auxiliary Information in Variability Control Charts

During the last decade, variance control charts based on different sampling schemes have attracted research interest in the field of statistical process control. These charts used extra (auxiliary) information either for ranking of units or estimation rather than using it for both. The effectiveness of a control chart can be increased by utilizing the auxiliary information for dual purposes. This article is focused on developing a generalized structure of variance control charts based on dual use of auxiliary information under different sampling strategies and runs rules. The generalized structure mainly depends on three auxiliary information‐based estimators with dual use of auxiliary information, three bivariate process distributions, and variety of sampling schemes. The performance of the proposed control charts is investigated by assessing the power curve. We have observed that the proposals of the study perform better than its complement. An application example is also provided for practitioners' concerns to monitor the stability of physicochemical parameter of groundwater. Copyright © 2015 John Wiley & Sons, Ltd.     

Combined Application of Shewhart and Cumulative Sum R Chart for Monitoring Process Dispersion

This study analyzes the performance of combined applications of the Shewhart and cumulative sum (CUSUM) range R chart and proposes modifications based on well‐structured sampling techniques, the extreme variations of ranked set sampling, for efficient monitoring of changes in the process dispersion. In this combined scheme, the Shewhart feature enables quick detection of large shifts from the target standard deviation while the CUSUM feature takes care of small to moderate shifts from the target value. We evaluate the numerical performance of the proposed scheme in terms of the average run length, standard deviation of run length, the average ratio average run length, and average extra quadratic loss. The results show that the combined scheme can detect changes in the process that were small or large enough to escape detection by the lone Shewhart R chart or CUSUM R chart, respectively. We present a comparison of the proposed schemes with several dispersion charts for monitoring changes in process variability. The practical application of the proposed scheme is demonstrated using real industrial data. Copyright © 2014 John Wiley & Sons, Ltd.     

On Modified Successive Sampling Based Control Charting Schemes

The presence of variation cannot be avoided in different kinds of manufacturing and non‐manufacturing processes. A better understanding of the causes of variability in any process is necessary to improve the process. Control chart is a very frequently used tool for checking whether the process parameters are stable or not. The current study devises a sampling technique, named as modified successive sampling scheme, that is not only cost‐effective but also efficient as compared with the simple random sampling scheme. A number of Shewhart‐type control charts are proposed based on the said sampling scheme, and average run length is used as a performance indicator. Based on the average run length values, all the proposed charts are compared with existing Shewhart control chart for both positive and negative shifts in the process. Finally, the new proposals are applied to a real dataset where the variable of interest is an inner diameter of automobile engine piston rings made of steel. Copyright © 2015 John Wiley & Sons, Ltd.     

Magneto-electric characteristics in (Mn,Cu) co-doped BiFeO<Subscript>3</Subscript> multiferroic nanoparticles

Multiferroic nanoparticles having general formula BiFe_0.99-xMn_xCu_0.01O₃ (x = 0, 0.01, 0.02, 0.03 & 0.04) were prepared by a chemically derived method to explore the magneto-electric characteristics of this new class of materials. X-ray diffraction confirmed that all the samples had rhombohedraly distorted cubic perovskite 3D lattice. Lattice constant was increased with increasing concentration of Mn. Micrographs obtained from a field emission scanning electron microscope revealed a fine distribution of well-shaped particles while the particle size was increased with increased contents of Mn. Enhanced hopping mechanism induced by substitution of Mn at the lattice sites of Fe resulted in an increased AC conductivity. Ferroelectricity was observed to increase with increased Mn, attributed mainly to the leakage current due to free charge carriers instigated by multiple oxidation states of Fe and Mn. It has been observed that antiferromagnetic bismuth ferrite begins to show ferromagnetic behavior due to the collapse of antiferromagnetic spin structure with increased Mn contents.     

On designing a progressive mean chart for efficient monitoring of process location

Variation is an important phenomenon of the output of every manufacturing and production process. To deal with the natural and special cause variations in the process, quality practitioners mostly apply control charts. There have been regular advancements over time in the design structures of these charts such as runs rules, fast initial response, sampling mechanisms among many others. In this article, auxiliary-information-based progressive mean (AIB-PM) control chart has been proposed, in which study variable is found correlated with another auxiliary variable. The development of the proposed AIB-PM structure utilises both the study and auxiliary variables. It is based on the regression estimator to introduce an unbiased and efficient estimate of the location parameter of the study variable. The performance assessment is carried out using average run length as a metric under zero-state and steady-state modes. The proposed AIB-PM chart is compared with some existing competitors and found that it performs uniformly superior than the existing competitors at small and persistent shifts in the process mean. An illustrative example using a real data set is presented to show the implementation of the proposed method.     

On developing an exponentially weighted moving average chart under progressive setup: An efficient approach to manufacturing processes

The exponentially weighted moving average (EWMA) control chart is a memory chart that is widely used in process monitoring to spot small and persistent disturbances in the process parameter(s). This chart requires normality of the quality characteristic(s) of interest and a smaller choice of smoothing parameter. Any deviations from these conditions affect its performance in terms of efficiency and robustness. For the said two concerns, this study develops a new mixed EWMA chart under progressive setup (mixed EWMA–progressive mean [MEP] chart). The proposed MEP chart combines the advantages of robustness (under nonnormal scenarios) and high sensitivity to small and persistent shifts in the process mean. The performance of the proposed MEP control chart is evaluated in terms of average run length and some other characteristics of run length distribution. The assessment of the proposed chart is made under standard normal, student's t, gamma, Laplace, logistic, exponential, contaminated normal and lognormal distributions. The performance of the proposed MEP chart is also compared with some existing competitors including the classical EWMA, the classical cumulative sum (CUSUM), the homogenously weighted moving average, the mixed EWMA–CUSUM, the mixed CUSUM–EWMA and the double EWMA charts. The analysis reveals that the proposal of this study offers a superior design structure relative to its competing counterparts. An application from substrates manufacturing process (in which flow width of the resist is the key quality characteristic) is also provided in the study.     

Effect of filler size and shape on local nanoindentation modulus of resin-composites

The aim of this study was to determine the Young’s moduli (E) of a series of model dental resin-composites using nanoindentation, and to examine how E was influenced by differences in filler-size and shape. Materials with different filler-sizes and shapes but constant filler volume-fraction were investigated. Disc specimens, mounted in polystyrene resin were mechanically polished and tested with a nanoindenter. One-way ANOVA and Bonferroni test were used for the statistical analysis. Regression analysis was used to investigate the correlation between E and filler-size. E ranged from 9.31 to 12.54 GPa for spherical fillers and from 14.09 to 17.03 GPa for irregular fillers. Statistically significant differences were found among the groups. Strong quadratic correlations were observed between E and filler-size for unimodal materials with spherical and irregular fillers, but were not statistically significant. Filler-size and shape seemed to be fine-tuning factors for E.     

High performance corrosion protective DGEBA/polypyrrole composite coatings

Conducting polymers (CP) have been envisaged as nontoxic substitutes for chromates in corrosion protective coatings owing to their environmental stability, excellent corrosion resistant performances and good adhesion to metal substrate. Recent advancements in the field of corrosion protective coatings have therefore headed towards the utilization of conducting polymers as “smart corrosion inhibitors” in the formulation of eco-friendly anti-corrosive coatings. With the aim to develop a facile method for the synthesis of anti corrosive coating material having superior corrosion protective properties, the present work reports the corrosion studies of polypyrrole/DGEBA composite coatings on mild steel (MS). The coatings were characterized by physicochemical as well as physicomechanical studies while the corrosion protective performance was evaluated by chemical resistance in different corrosive media, corrosion rate and open circuit potential (OCP) measurements. The morphologies of corroded, coated, uncorroded and uncoated samples were investigated by SEM studies. The composite coatings were found to show far superior anti corrosive performance than PANI/epoxy coatings in acid, alkaline as well as saline environments.     

A hybrid defocused region segmentation approach using image matting

Multidimensional Systems and Signal Processing - In this paper, a hybrid defocused region segmentation using image matting is proposed. The technique incorporates three sharpness metrics which are...     

A chipless RFID tag for smart temporal applications

A compact, robust, chipless radio frequency identification (RFID) tag is proposed. Resonant elements patterned in a concentric fashion encode data in the spectral domain employing frequency shift encoding. The proposed tag encodes 28.25 data bits over a miniscule physical footprint of 25 × 25 mm². The formulated scheme is demonstrated to be viable for encoding of temporal variables. The electromagnetic performance of the presented design is investigated for different laminates: Rogers RT/duroid® 5880 and Taconic TLX‐0. Multiple tag prototypes employing a variety of substrates are realized and evaluated for in‐laboratory performance. The proposed design is compared with existing work reported in literature. Code density of 4.52 bits/cm² has been successfully achieved. The tag design operates from 3.07 to 10.6 GHz and is readily realizable on flexible laminates. Smart retail, intelligent packaging, adaptive ticketing, and similar time‐related applications can be materialized using the proposed tag.