Risk-Based X-bar chart with variable sample size and sampling interval

Flexibility is increasingly important in production management, and adaptive control charts (i.e., control charts with variable sample size and/or variable sampling interval) have significant importance in the field of statistical process control. The value of the variable chart parameters depends on the detected process parameters. The process parameters need to be estimated based on observed values; however, these values are distorted by measurement uncertainty. Therefore, the performance of the method is strongly influenced by the precision of the measurement. This paper proposes a risk-based concept for the design of an X-bar chart with variable sample size and sampling interval. The optimal set of the parameters (control line, sample size and sampling interval) is determined using genetic algorithms and the Nelder-Mead direct search algorithm to minimize the risks arising from measurement uncertainty

A Quality Systems Economic-Risk Design Theoretical Framework

Quality systems, including control charts theory and sampling plans, have become essential tools to develop business processes. Since 1928, research has been conducted in developing the economic-risk designs for specific types of control charts or sampling plans. However, there has been no theoretical or applied research attempts to combine these related theories into a synthesized theoretical framework of quality systems economic-risk design. This research proposes to develop a theoretical framework of quality systems economic-risk design from qualitative research synthesis of the economic-risk design of sampling plan models and control charts models. This theoretical framework will be useful in guiding future research into economic risk quality systems design theory and application

Economic Design of X-bar Control Chart Using Gravitational Search Algorithm

Control chart is a major and one of most widely used statistical process control (SPC) tools. It is used to statistically monitor the process through sampling inspection. Control chart tells us when to allow the process to continue or avoid unnecessary adjustments with machine and when to take the corrective action. On to same problem either on the material side or from the operator side it is quite possible that either targeted value X-bar has changed or process dispersion has changed. These changes must be reflected on the control chart so that the corrective action can be taken. The use of control chart requires selection of three parameters namely sample size n, sampling interval h, and width of control limits k for the chart. Duncan developed a loss cost function for X-bar control chart with single assignable cause. The function has to be optimized using metaheuristic optimization technique. In the present project, the economic design of the X-bar control chart using Gravitational Search Algorithm (GSA) has been developed MATLAB software to determine the three parameters i.e. n , h and k such that the expected total cost per hour is minimized. The results obtained are found to be better than that reported in literature

Economic Design of X-bar Control Chart Using Gravitational Search Algorithm

Control chart is a major and one of most widely used statistical process control (SPC) tools. It is used to statistically monitor the process through sampling inspection. Control chart tells us when to allow the process to continue or avoid unnecessary adjustments with machine and when to take the corrective action. On to same problem either on the material side or from the operator side it is quite possible that either targeted value X-bar has changed or process dispersion has changed. These changes must be reflected on the control chart so that the corrective action can be taken. The use of control chart requires selection of three parameters namely sample size n, sampling interval h, and width of control limits k for the chart. Duncan developed a loss cost function for X-bar control chart with single assignable cause. The function has to be optimized using metaheuristic optimization technique. In the present project, the economic design of the X-bar control chart using Gravitational Search Algorithm (GSA) has been developed MATLAB software to determine the three parameters i.e. n , h and k such that the expected total cost per hour is minimized. The results obtained are found to be better than that reported in literature

Molecular epidemiology of waterborne zoonoses in the North Island of New Zealand : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science (Epidemiology and Public Health) at Institute of Veterinary, Animal and Biomedical Sciences (IVABS), Massey University, Palmerston North, New Zealand

Campylobacter, Cryptosporidium and Giardia species are three important waterborne zoonotic pathogens of global public health concern. This PhD opens with an interpretive overview of the literature on Campylobacter, Cryptosporidium and Giardia spp. in ruminants and their presence in surface water (Chapter 1), followed by five epidemiological studies of Campylobacter, Cryptosporidium and Giardia spp. in cattle, sheep and aquatic environment in New Zealand (Chapters 2-6). The second chapter investigated four years of retrospective data on Campylobacter spp. (n=507) to infer the source, population structure and zoonotic potential of Campylobacter jejuni from six high-use recreational rivers in the Wanganui- Manawatu region of New Zealand through the generalised additive model, generalised linear/logistic regression model, and minimum spanning trees. This study highlights the ubiquitous presence of Campylobacter spp. in both low and high river flows, and during winter months. It also shows the presence of C. jejuni in 21% of samples containing highly diverse strains, the majority of which were associated with wild birds only. These wild birds-associated C. jejuni have not been detected in human, suggesting they may not be infectious to human. However, the presence of some poultry and ruminant-associated strains that are potentially zoonotic suggested the possibility of waterborne transmission of C. jejuni to the public. Good biosecurity measures and water treatment plants may be helpful in reducing the risk of waterborne Campylobacter transmission In the third study, a repeated cross-sectional study was conducted every month for four months to investigate the source of drinking source-water contamination. A total of 499 ruminant faecal samples and 24 river/stream water samples were collected from two rural town water catchments (Dannevirke and Shannon) in the Manawatu- Wanganui region of New Zealand, and molecular analysis of those samples was performed to determine the occurrence of Campylobacter, Cryptosporidium, and Giardia spp. and their zoonotic potential. The major pathogens found in faecal samples were Campylobacter (n=225 from 7/8 farms), followed by Giardia (n=151 from 8/8 farms), whereas Giardia cysts were found in many water samples (n=18), followed by Campylobacter (n=4). On the contrary, Cryptosporidium oocysts were only detected in a few faecal (n=18) and water (n=3) samples. Cryptosporidium and Giardia spp. were detected in a higher number of faecal samples from young animals (≤ 3 months) than juvenile and adult animals, whereas Campylobacter spp. were highly isolated in the faecal samples from juvenile and adult ruminants. PCRsequencing of the detected pathogens indicated the presence of potentially zoonotic C. jejuni and C. coli, Cryptosporidium parvum (gp60 allelic types IIA18G3R1 and IIA19G4R1) and Giardia duodenalis (assemblages AII, BII, BIII, and BIV) in cattle and sheep. In addition, potentially zoonotic C. jejuni and Giardia duodenalis assemblages AII, BI, BII, and BIV were also determined in water samples. These findings indicate that these three pathogens of public health significance are present in ruminant faecal samples of farms and in water, and may represent a possible source of human infection in New Zealand. In the fourth study, PCR-sequencing of Cryptosporidium spp. isolates obtained from the faeces of 6-week- old dairy calves (n=15) in the third study were investigated at multiple loci (18S SSU rDNA, HSP70, Actin and gp60) to determine the presence of mixed Cryptosporidium spp. infections. Cryptosporidium parvum (15/15), C. bovis (3/15) and C. andersoni (1/15), and two new genetic variants were determined along with molecular evidence of mixed infections in five specimens. Three main Cryptosporidium species of cattle, C. parvum, C. bovis and C. andersoni, were detected together in one specimen. Genetic evidence of the presence of C. Anderson and two new Cryptosporidium genetic variants are provided here for the first time in New Zealand. These findings provided additional evidence that describes Cryptosporidium parasites as genetically heterogeneous populations and highlighted the need for iterative genotyping at multiple loci to explore the genetic makeup of the isolates. The C. jejuni and C. coli isolates (n=96) obtained from cattle, sheep and water in the third study were subtyped to determine their genetic diversity and zoonotic potential using a modified, novel multi-locus sequence typing method (“massMLST”; Chapter 5). Primers were developed and optimised, PCR-based target-MLST alleles’ amplification were performed, followed by next generation sequencing on an Illumina MiSeq machine. A bioinformatics pipeline of the sequencing data was developed to define C. jejuni and C. coli multi-locus sequence types. This study demonstrated the utility and potential of this novel typing method, massMLST, as a strain typing method. In addition to identifying the possible C. jejuni/coli clonal complexes or sequence types of 68/96 isolates from ruminant faeces and water samples, this study reported three new C. jejuni strains in cattle in New Zealand, along with many strains, such as CC-61, CC-828 and CC-21, that have also been found in humans, indicating the public health significance of these isolates circulating on the farms in the two water catchment areas. Automation of the massMLST method and may allow a cost-effective high-resolution typing method in the near future for multilocus sequence typing of large collections of Campylobacter strains. In the final study (Chapter 6), a pilot metagenomic study was carried out to obtain a snapshot of the microbial ecology of surface water used in the two rural towns of New Zealand for drinking purposes, and to identify the zoonotic pathogens related to waterborne diseases. Fresh samples collected in 2011 and 2012, samples from the same time that were frozen, and samples that were kept in the preservative RNAlater were sequenced using whole-genome shotgun sequencing on an Illumina MiSeq machine. Proteobacteria was detected in all the samples characterised, although there were differences in the genus and species between the samples. The microbial diversity reported varied between the grab and stomacher methods, between samples collected in the year 2011 and 2012, and among the fresh, frozen and RNAlater preserved samples. This study also determined the presence of DNA of potentially zoonotic pathogens such as Cryptosporidium, Campylobacter and Mycobacterium spp. in water. Use of metagenomics could potentially be used to monitor the ecology of drinking water sources so that effective water treatment plans can be formulated, and for reducing the risk of waterborne zoonosis. As a whole, this PhD project provides new data on G. duodenalis assemblages in cattle, sheep and surface water, new information on mixed Cryptosporidium infections in calves, a novel “massMLST” method to subtype Campylobacter species, and shows the utility of shotgun metagenomic sequencing for drinking water monitoring. Results indicate that ruminants (cattle and sheep) in New Zealand shed potentially zoonotic pathogens in the environment and may contribute to the contamination of surface water. A better understanding of waterborne zoonotic transmission would help in devising appropriate control strategies, which could reduce the shedding of Campylobacter, Cryptosporidium, and Giardia spp. in the environment and thereby reduce waterborne transmission

One-sided Downward Control Chart for Monitoring the Multivariate Coefficient of Variation with VSSI Strategy

In recent years, control charts monitoring the coefficient of variation (CV), denoted as the ratio of the variance to the mean, is attracting significant attention due to its ability to monitor processes in which the process mean and process variance are not independent of each other. However, very few studies have been done on charts to monitor downward process shifts, which is important since downward process shifts show process improvement. In view of the importance of today's competitive manufacturing environment, this paper proposes a one-sided chart to monitor the downward multivariate CV (MCV) with variable sample size and sampling interval (VSSI), i.e. the VSSID MCV chart. This paper monitors the MCV as most industrial processes simultaneously monitor at least two or more quality characteristics, while the VSSI feature is incorporated, as it is shown that this feature brings about a significant improvement of the chart. A Markov chain approach was adopted for designing a performance measure of the proposed chart. The numerical comparison revealed that the proposed chart outperformed existing MCV charts. The implementation of the VSSID MCV chart is illustrated with an example

Frequency of higher risk sexual behaviors for men who have sex with men

Safer sexual behaviors have been widely promoted for many years as an effective means of preventing the transmission of HIV. However, creating an initial change in an individual\u27s behavior does not guarantee that an individual will maintain that behavior change. This meta-analysis looked at one population---men who have sex with men---and fit a random effects model to the data for the available studies on the frequency of higher risk sexual behaviors. It is clear the prevention programs need to be developed that focus on maintenance of changes to safer sexual behaviors. By identifying the important predictors of the frequency of higher risk sexual behaviors, this meta-analysis provides suggestions on what may be important to include in targeted prevention programs

The statistical optimal design of Shewhart control charts with supplementary stopping rules

Monitoring production processes to assure product quality has been a major problem in industrial engineering and quality control. These processes are subject to shifts to out-of-control states resulting in the production of nonconforming items. In general, desirable control schemes are those that require a small number of samples (small run length) for the detection and correction of these shifts in the process meanwhile providing a large in-control average run length (A.R.L.);In this study, a method for designing control schemes for X-bar charts is presented and discussed. This method can be used in conjunction with economical-design methods for these charts or as an alternative to these methods when estimates of cost parameters are not available. Our method is based exclusively on the average run length properties of the different control schemes and it seeks the minimization of the out-of-control A.R.L. (by the appropriate selection of the control limits) for a given in-control A.R.L;A Markov-chain based method is presented for obtaining the exact A.R.L. properties of Shewhart control charts with supplementary stopping rules. Computer code is given for obtaining the transient states and the transition probabilities of the Markov chain representation of several control schemes. Computer programs and algorithms (based on penalty-function methods and inverse parabolic interpolation) to find the optimal control limits for various control schemes are given, as well. For practitioners, tables and nomographs, giving the control-limit combinations that minimize the out-of-control A.R.L. for different values of the in-control A.R.L. and for several control schemes, are provided. An optimal control scheme is compared to a commonly used scheme and their performance, under different out-of-control situations, is evaluated using Monte Carlo simulation techniques

Joint economic design of EWMA control charts for mean and variance

Cataloged from PDF version of article.Control charts with exponentially weighted moving average (EWMA) statistics (mean and variance) are used to jointly monitor the mean and variance of a process. An EWMA cost minimization model is presented to design the joint control scheme based on pure economic or both economic and statistical performance criteria. The pure economic model is extended to the economic-statistical design by adding constraints associated with in-control and out-of-control average run lengths. The quality related production costs are calculated using Taguchi's quadratic loss function. The optimal values of smoothing constants, sampling interval, sample size, and control chart limits are determined by using a numerical search method. The average run length of the control scheme is computed by using the Markov chain approach. Computational study indicates that optimal sample sizes decrease as the magnitudes of shifts in mean and/or variance increase, and higher values of quality loss coefficient lead to shorter sampling intervals. The sensitivity analysis results regarding the effects of various inputs on the chart parameters provide useful guidelines for designing an EWMA-based process control scheme when there exists an assignable cause generating concurrent changes in process mean and variance. (C) 2006 Elsevier B.V. All rights reserved