Tesi sul tema "Statistical Process control chart"
Segui questo link per vedere altri tipi di pubblicazioni sul tema: Statistical Process control chart.
Cita una fonte nei formati APA, MLA, Chicago, Harvard e in molti altri stili
Vedi i top-50 saggi (tesi di laurea o di dottorato) per l'attività di ricerca sul tema "Statistical Process control chart".
Accanto a ogni fonte nell'elenco di riferimenti c'è un pulsante "Aggiungi alla bibliografia". Premilo e genereremo automaticamente la citazione bibliografica dell'opera scelta nello stile citazionale di cui hai bisogno: APA, MLA, Harvard, Chicago, Vancouver ecc.
Puoi anche scaricare il testo completo della pubblicazione scientifica nel formato .pdf e leggere online l'abstract (il sommario) dell'opera se è presente nei metadati.
Vedi le tesi di molte aree scientifiche e compila una bibliografia corretta.
1
SIMOES, BRUNO FRANCISCO TEIXEIRA. "EWMA CHART WITH ADAPTIVE SMOOTHING CONSTANT FOR STATISTICAL PROCESS CONTROL". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=8189@1.
Abstract (sommario):
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOREste trabalho propõe um gráfico de controle EWMA para observações individuais ou médias amostrais, com a constante de amortecimento variando entre dois valores de acordo com o valor mais recente da estatística EWMA, para obter detecção mais rápida de alterações pequenas a moderadas na média do processo, e sem a complexidade operacional apresentada por outros esquemas adaptativos, pois o tamanho da amostra e o intervalo de amostragem são mantidos fixos. Já existe um outro trabalho propondo a variação da constante de amortecimento dos gráficos EWMA, mas com base em outro critério: Capizzi e Masarotto (2003). O esquema EWMA adaptativo foi combinado com limites de Shewhart para os valores individuais (ou médias amostrais), para acelerar a detecção de grandes deslocamentos da média do processo, também sem aumento da complexidade operacional. Os NMA1´s - números esperados de amostras até um sinal verdadeiro - foram calculados por um método de aproximação numérica usando um modelo matemático por cadeias de Markov, e comparados com os do esquema EWMA tradicional (com parâmetros fixos) e com os do esquema adaptativo de Capizzi e Masarotto (2003). O esquema proposto tende a fornecer NMA1´s menores para alterações na média acima de 1,0 desvio-padrão, e o esquema de Capizzi e Masarotto (2003) tende a fornecer NMA1´s menores para pequenas alterações. Ambos os esquemas possuem melhor desempenho que o gráfico EWMA com parâmetros fixos. Uma vantagem que pode se tornar decisiva para a adoção do esquema proposto é a simplicidade dos cálculos requeridos para o monitoramento.
This work proposes an EWMA process control chart for individual observations or subgroup averages, in which the smoothing constant varies between two values according to the most recent value of the EWMA statistic, in order to achieve faster detection of small to moderate shifts in the process mean, and without the operational complexities presented by other adaptive schemes, since its sample size and sampling interval do not vary. There is one other work proposing the adaptive variation of the smoothing constant of EWMA charts, but based on a different criterion: Capizzi and Masarotto (2003). The adaptive EWMA scheme was combined with Shewhart limits for the individual values (or subgroup averages), to enhance its sensitivity to large shifts, again with no extra operational burden. The out-of-control average run lengths (ARL1´s) were calculated through a numerical approximation method based on a Markov chain model. The ARL1´s were compared of the proposed scheme, of the traditional (fixed parameter) EWMA chart and of Capizzi and Masarottos´s adaptive EWMA scheme. The proposed scheme generally provides the shortest ARL1´s for shifts in the mean above one standard deviation, and Capizzi and Masarotto´s scheme tends to outperform it for smaller shifts. Both schemes perform better than the fixed parameter EWMA. An advantage that can become decisive for the adoption of the proposed scheme is the simplicity of the calculations required for the monitoring.
2
Sundholm, Per. "Statistical Process Control for the Sawmill Industry". Thesis, Umeå universitet, Institutionen för fysik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-112046.
Abstract (sommario):
In the sawmill industry, it can be very profitable to monitor the dimensions of sawn boards so that operators quickly can detect errors and take cor-rective action. In this master’s thesis project, Statistical Process Control (SPC) methods have been implemented to achieve this. SPC is a set of statistical methods whose purpose is to minimize the variations in an in-dustrial process. In particular, the SPC method used here is the control chart, which with an upper and lower control limit quantifies the bounds of natural variation. To find the most suitable control chart, five control charts monitoring the process mean, and two monitoring process variability were tested with help of both a simulation study and an empirical evaluation. The result of the evaluation was that the ”Average Moving Range” chart was regarded the most suitable for changes in process mean, and the Range chart was regarded as the best at detecting changes in process variability. Both charts are constructed for individual boards and not subgroups of boards (as is more common) due to compatibility reasons with the existing measurement practice. The two methods were deemed to be quite able to detect process changes, but some results indicate that the methods might work better for double arbour saw lines than single arbour ones.Det kan vara mycket lönsamt för sågverk att övervaka mått på plankor så att personal snabbt kan hitta och åtgärda fel som uppstår i processen. I det syftet har det här masterarbetet gått ut på att implementera statistisk processkontroll (SPC) för råmåttkontroll på sågverk. SPC är en mängd olika statistiska metoder vars syfte är att minimera spridningen i en tillverkningsprocess. Den metod som är i speciellt focus i det här arbetet är det så kallade styrdiagrammet som med en övre och undre gräns kvantifierar hur stor den naturligt förekommande spridningen är. För att finna det mest lämpade styrdiagrammet utvärderades fem styrdiagram som övervakar processens medelvärde och två styrdiagram som övervakar processens spridning. Denna utvärdering bestod både av en simuleringsstudie och tester gjorda för empiriskt data. Utvärderingen resulterade i att det så kallade ”Average Moving Range” diagrammet rekommenderades för övervakning av medelvärde och ett räckviddsstyrdiagram rekommenderades för spridningen. Båda styrdiagrammen konstruerades för enskilda plankor och inte för stickprov av flera plankor (vilket är vanligare) på grund av kompatibelitetsskäl med gängse mätmetodik. De båda metoderna ansågs vara ganska bra på att upptäcka processförändringar men vissa resultat tyder på att metoderna kanske fungerar bättre för sågverk med mötande klingor än enaxliga sågverk.
3
Ouyang, Jintao. "Cumulative quantity control chart and maintenance strategies for industrial processes". Thesis, Click to view the E-thesis via HKUTO, 2004. http://sunzi.lib.hku.hk/hkuto/record/B31121184.
4
el, homani Abdellatif. "NOVEL APPROACHES FOR STATISTICAL PROCESS CONTROL CHARTS PATTERN RECOGNITION". OpenSIUC, 2010. https://opensiuc.lib.siu.edu/dissertations/152.
Abstract (sommario):
Fast and accurate recognition of the Statistical Control Chart Patterns (SPCCP) is significant for supervising manufacturing processes to accomplish better control and to make high value products. SPCCP can display eight kinds of patterns: normal, stratification, systematic, increasing trend, decreasing trend, up shift, down shift and cyclic. With the exception of the natural pattern, all other patterns indicate that the supervised manufacturing process is not performing properly and actions need to be taken to correct the problems. This research proposes new approaches, neural networks and neural-fuzzy systems, to the (SPCCP) recognition. This dissertation also investigates the use of features extracted from statistical analysis for simple patterns, and wavelet analysis for concurrent patterns as the components of the input vectors. Results based on simulated data show that the proposed approaches perform better than conventional approaches. Our work concluded that the extracted features improve the performance of the proposed recognizer systems.
5
Kirbas, Serkan. "An Assessment And Analysis Tool For Statistical Process Control Of Software Processes". Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608196/index.pdf.
Abstract (sommario):
Statistical process control (SPC) which includes very powerful techniques used in other mature engineering disciplines for providing process control is not used by many software organizations. In software engineering domain, SPC is currently utilized only by organizations which have high maturity levels according to the process improvement models like CMM, ISO/IEC 15504 and CMMI. Guidelines and software tools to implement SPC techniques should be developed for effective use and dissemination of SPC especially for low maturity organizations.
In this thesis, a software tool (SPC-AAT) which we developed to assess the suitability of software processes and metrics for SPC and use of SPC tools is presented. With SPC-AAT, we aim to ease and enhance application of SPC especially for emergent and low maturity organizations. Control charts, histograms, bar charts and pareto charts are the supported SPC tools for this purpose. We also explained the validation of the tool over two processes of a software organization in three case studies.
6
Chin, Chang-Ho. "Optimal filter design approaches to statistical process control for autocorrelated processes". Texas A&M University, 2004. http://hdl.handle.net/1969.1/2776.
Abstract (sommario):
Statistical Process Control (SPC), and in particular control charting, is widely used to achieve and maintain control of various processes in manufacturing. A control chart is a graphical display that plots quality characteristics versus the sample number or the time line. Interest in effective implementation of control charts for autocorrelated processes has increased in recent years. However, because of the complexities involved, few systematic design approaches have thus far been developed.
Many control charting methods can be viewed as the charting of the output of a linear filter applied to the process data. In this dissertation, we generalize the concept of linear filters for control charts and propose new control charting schemes, the general linear filter (GLF) and the 2nd-order linear filter, based on the generalization. In addition, their optimal design methodologies are developed, where the filter parameters are optimally selected to minimize the out-of-control Average Run Length (ARL) while constraining the in-control ARL to some desired value. The optimal linear filters are compared with other methods in terms of ARL performance, and a number of their interesting characteristics are discussed for various types of mean shifts (step, spike, sinusoidal) and various ARMA process models (i.i.d., AR(1), ARMA(1,1)).
Also, in this work, a new discretization approach for substantially reducing the computational time and memory use for the Markov chain method of calculating the ARL is proposed. Finally, a gradient-based optimization strategy for searching optimal linear filters is illustrated.
7
Wilson, Sara R. "Control Charts with Missing Observations". Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/37623.
Abstract (sommario):
Traditional control charts for process monitoring are based on taking samples from the process at regular time intervals. However, it is often possible in practice for observations, and even entire samples, to be missing. This dissertation investigates missing observations in Exponentially Weighted Moving Average (EWMA) and Multivariate EWMA (MEWMA) control charts. The standardized sample mean is used since this adjusts the sample mean for the fact that part of the sample may be missing. It also allows for constant control limits even though the sample size varies randomly. When complete samples are missing, the weights between samples should also be adjusted.
In the univariate case, three approaches for adjusting the weights of the EWMA control statistic are investigated: (1) ignoring missing samples; (2) adding the weights from previous consecutive missing samples to the current sample; and (3) increasing the weights of non-missing samples in proportion, so that the weights sum to one. Integral equation and Markov chain methods are developed to find and compare the statistical properties of these charts. The EI chart, which adjusts the weights by ignoring the missing samples, has the best overall performance.
The multivariate case in which information on some of the variables is missing is also examined using MEWMA charts. Two methods for adjusting the weights of the MEWMA control statistic are investigated and compared using simulation: (1) ignoring all the data at a sampling point if the data for at least one variable is missing; and (2) using the previous EWMA value for any variable for which all the data are missing. Both of these methods are examined when the in-control covariance matrix is adjusted at each sampling point to account for missing observations, and when it is not adjusted. The MS control chart, which uses the previous value of the EWMA statistic for a variable if all of the data for that variable is missing at a sampling point, provides the best overall performance. The in-control covariance matrix needs to be adjusted at each sampling point, unless the variables are independent or only weakly correlated.Ph. D.
8
Park, Yongro. "A statistical process control approach for network intrusion detection". Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/6835.
Abstract (sommario):
Intrusion detection systems (IDS) have a vital role in protecting computer networks and information systems. In this thesis we applied an SPC monitoring concept to a certain type of traffic data in order to detect a network intrusion.
We developed a general SPC intrusion detection approach and described it and the source and the preparation of data used in this thesis. We extracted sample data sets that represent various situations, calculated event intensities for each situation, and stored these sample data sets in the data repository for use in future research.
A regular batch mean chart was used to remove the sample datas inherent 60-second cycles. However, this proved too slow in detecting a signal because the regular batch mean chart only monitored the statistic at the end of the batch. To gain faster results, a modified batch mean (MBM) chart was developed that met this goal. Subsequently, we developed the Modified Batch Mean Shewhart chart, the Modified Batch Mean Cusum chart, and the Modified Batch Mean EWMA chart and analyzed the performances of each one on simulated data. The simulation studies showed that the MBM charts perform especially well with large signals ?the type of signal typically associated with a DOS intrusion.
The MBM Charts can be applied two ways: by using actual control limits or by using robust control limits. The actual control limits must be determined by simulation, but the robust control limits require nothing more than the use of the recommended limits. The robust MBM Shewhart chart was developed based on choosing appropriate values based on batch size. The robust MBM Cusum chart and robust MBM EWMA chart were developed on choosing appropriate values of charting parameters.
9
Liu, Qingyun. "Statistical Process Control for the Fairness of Network Resource Distribution". FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/518.
Abstract (sommario):
The purpose of this research is to develop a statistical method to monitor the fairness of network resource distribution. The newly developed fairness score function allows users to have the same or different priority levels. Especially, this function possesses all the necessary properties required as a quality characteristic for the purpose of statistical process control.
The main objective is to find the critical values for the statistical test. Monte Carlo simulation is used to find the critical values. When the users have the same priority level, a table of the critical values is given for different sample sizes and different significance levels. When the users have different priority levels, it is difficult to generate a similar table since the users’ priority levels vary. Therefore, the critical values are computed for given priority levels. In both cases, an example is given to demonstrate the approach developed in this study.
10
Šváchová, Mariana. "Určování způsobilosti a stability vybraného technického procesu". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417798.
Abstract (sommario):
This diploma thesis deals with the evaluation of the capability of a specific production process. The theoretical part of the work contains a description of statistical process control, types of control charts and evaluation of process capability. The practical part is focused on evaluating the capability of a specific process. The method of dataset collection is described at first, then this data are analyzed and the capability of this process is evaluated.
11
Yang, Hualong, e 阳华龙. "Statistical process control charts with known and estimatedparameters". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50900018.
Abstract (sommario):
Monitoring and detection of abrupt changes for multivariate processes are becoming increasingly important in modern manufacturing environments. Typical equipment may have multiple key variables to be measured continuously. Hotelling's 〖T 〗^2and CUSUM charts were widely applied to solve the problem of monitoring the mean vector of multivariate quality measurements. Besides, a new multivariate cumulative sum chart (MCUSUM) is introduced where the target shift mean is assumed to be a weighted sum of principal directions of the population covariance matrix. In practical problems, estimated parameters are needed and the properties of control charts differ from the case where the parameters are known in advance. In particular, it has been observed that the average run length (ARL), a performance indicator of the control charts, is larger when the estimated parameters are used. As a first contribution we provide a general and formal proof of the phenomenon. Also, to design an efficient 〖T 〗^2 or CUSUM chart with estimated parameters, a method to calculate or approximate the ARL function is necessarily needed. A commonly used approach consists in tabulating reference values using extensive Monte-Carlo simulation. By a different approach in thesis, an analytical approximation for the ARL function in univariate case is provided, especially in-control ARL function, which can help to directly set up control limits for different sample sizes of Phase I procedure instead of conducting complex simulation.published_or_final_version
Statistics and Actuarial Science
Master
Master of Philosophy
12
Zhong, Xin. "Efficient Sampling Plans for Control Charts When Monitoring an Autocorrelated Process". Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/26337.
Abstract (sommario):
This dissertation investigates the effects of autocorrelation on the performances of various sampling plans for control charts in detecting special causes that may produce sustained or transient shifts in the process mean and/or variance. Observations from the process are modeled as a first-order autoregressive process plus a random error. Combinations of two Shewhart control charts and combinations of two exponentially weighted moving average (EWMA) control charts based on both the original observations and on the process residuals are considered. Three types of sampling plans are investigated: samples of n = 1, samples of n > 1 observations taken together at one sampling point, or samples of n > 1 observations taken at different times. In comparing these sampling plans it is assumed that the sampling rate in terms of the number of observations per unit time is fixed, so taking samples of n = 1 allows more frequent plotting. The best overall performance of sampling plans for control charts in detecting both sustained and transient shifts in the process is obtained by taking samples of n = 1 and using an EWMA chart combination with a observations chart for mean and a residuals chart for variance. The Shewhart chart combination with the best overall performance, though inferior to the EWMA chart combination, is based on samples of n > 1 taken at different times and with a observations chart for mean and a residuals chart for variance.Ph. D.
13
Ronnestrand, Clinton. "Using control charts to determine if a process is in statistical process control". Online version, 2009. http://www.uwstout.edu/lib/thesis/2009/2009ronnestrandc.pdf.
14
Harvey, Martha M. (Martha Mattern). "The Fixed v. Variable Sampling Interval Shewhart X-Bar Control Chart in the Presence of Positively Autocorrelated Data". Thesis, University of North Texas, 1993. https://digital.library.unt.edu/ark:/67531/metadc278763/.
Abstract (sommario):
This study uses simulation to examine differences between fixed sampling interval (FSI) and variable sampling interval (VSI) Shewhart X-bar control charts for processes that produce positively autocorrelated data. The influence of sample size (1 and 5), autocorrelation parameter, shift in process mean, and length of time between samples is investigated by comparing average time (ATS) and average number of samples (ANSS) to produce an out of control signal for FSI and VSI Shewhart X-bar charts. These comparisons are conducted in two ways: control chart limits pre-set at ±3σ_x / √n and limits computed from the sampling process. Proper interpretation of the Shewhart X-bar chart requires the assumption that observations are statistically independent; however, process data are often autocorrelated over time. Results of this study indicate that increasing the time between samples decreases the effect of positive autocorrelation between samples. Thus, with sufficient time between samples the assumption of independence is essentially not violated. Samples of size 5 produce a faster signal than samples of size 1 with both the FSI and VSI Shewhart X-bar chart when positive autocorrelation is present. However, samples of size 5 require the same time when the data are independent, indicating that this effect is a result of autocorrelation. This research determined that the VSI Shewhart X-bar chart signals increasingly faster than the corresponding FSI chart as the shift in the process mean increases. If the process is likely to exhibit a large shift in the mean, then the VSI technique is recommended. But the faster signaling time of the VSI chart is undesirable when the process is operating on target. However, if the control limits are estimated from process samples, results show that when the process is in control the ARL for the FSI and the ANSS for the VSI are approximately the same, and exceed the expected value when the limits are fixed.
15
Sargut, Kamil Umut. "Application Of Statistical Process Control To Software Development Processes Via Control Charts". Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1270081/index.pdf.
Abstract (sommario):
The application of Statistical Process Control (SPC) to software processes has
been a challenging issue for software engineers and researchers. Although SPC is
suggested for providing process control and achieving higher process maturity
levels, there are very few resources that describe success stories, implementation
details, and implemented guidelines for applying SPC to specific metrics.
In this thesis the findings of a case study that is performed for investigating the
applicability of SPC to software metrics in an emergent CMM Level 3 software
organization are presented. As being one of the basic and most sophisticated tools
of SPC, control charts are used for the analysis. The difficulties in application of
Statistical Process Control to a CMM Level 3 organization are observed by using
the existing data of defect density, rework percentage, productivity and review
performance metrics and relevant suggestions are provided for dealing with them.
Finally the analysis results are summarized and a guideline is prepared for
software companies who want to utilize control charts by using their existing
metric data.
16
Lanhede, Daniel. "Non-parametric Statistical Process Control : Evaluation and Implementation of Methods for Statistical Process Control at GE Healthcare, Umeå". Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-104512.
Abstract (sommario):
Statistical process control (SPC) is a toolbox to detect changes in the output of a process distribution. It can serve as a valuable resource to maintain high quality in a manufacturing process. This report is based on the work on evaluating and implementing methods for SPC in the process of chromatography instrument manufacturing at GE Healthcare, Umeå. To handle low volume and non-normally distributed process output data, non-parametric methods are considered. Eight control charts, three for for Phase I analysis, and five for Phase II analysis, are evaluated in this study. The usability of the charts are assessed based on ease of interpretation and the performance to detect distributional changes. The later is evaluated with simulations. The result of the project is the implementation of the RS/P-chart, suggested by Capizzi et al (2013), for Phase I analysis. Of the considered Phase I methods (and simulation scenarios), the RS/P-chart has the highest overall probability, of detecting a variety of distributional changes. Further, the RS/P-chart is easily interpreted, facilitating the analysis. For Phase II analysis, the use of two control charts, one based on the Mann-Whitney U statistic, suggested by Chakraborti et al (2008), and one on the Mood test statistic for dispersion, suggested by Ghute et al (2014), have been implemented. These are chosen mainly based on the ease of interpretation. To reduce the detection time for changes in the process distribution, the change-point chart based on the Cramer Von Mises statistic, suggested by Ross et al (2012), could be used instead. Using single observations, instead of larger samples, this chart is updated more frequently. However, this efficiently increases the false alarm rate and the chart is also considered much more difficult to interpret for the SPC practitioner.Statistisk processkontroll (SPC) är en samling verktyg för att upptäcka förändringar, i fördelningen, hos utfallen i en process. Det kan fungera som en värdefull resurs för att upprätthålla en hög kvalitet i en tillverkningsprocess. Denna rapport är baserad på arbetet med att utvärdera och implementera metoder för SPC i en monteringsprocess av kromatografiinstrument på GE Healthcare, Umeå. Åtta styrdiagram, tre för för fas I analys, och fem för fas II analys, studeras i denna rapport. Användbarheten hos styrdiagrammen bedöms efter hur enkla de är att tolka och förmågan att upptäcka fördelningsförändringar. Den senare utvärderas med simuleringar. Resultatet av projektet är införandet av RS/P-metod, utvecklad av Capizzi et al (2013), för analysen i fas I. Av de utvärderade metoderna, (och simuleringsscenarier), har RS/P-diagrammet den högsta övergripande sannolikheten, för att upptäcka en mängd olika fördelningsförändringar. Vidare är metodens grafiska diagram lätt att tolka, vilket underlättar analysen. För fas II analys, har två styrdiagram, ett baserat på Mann-Whitney's U teststatistika, som föreslagits av Chakraborti et al (2008), och ett på Mood's teststatistika för spridning, som föreslagits av Ghute et al (2014), implementerats. Styrkan i dessa styrdiagram ligger främst i dess enkla tolkning. För snabbare identifiering av processförändringar kan styrdiagrammet baserat på Cramer von Mises teststatistika, som föreslagits av Ross et al (2012), användas. Baserat på enskilda observationer, istället för stickprov, har styrdiagrammet en högre uppdateringsfrekvens. Detta leder dock till ett ökat antal falska larm och styrdiagrammet anses dessutom vara avsevärt mycket svårare att tolka för SPC-utövaren.
17
Szmek, Tomáš. "Stabilita procesu výroby železničních podkladnic". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2011. http://www.nusl.cz/ntk/nusl-229776.
Abstract (sommario):
The master’s thesis is focused on process monitoring using statistical process control SPC tools. It is designed as a guide for the implementation and use of control charts in the manufacturing process of the base plates, which would ultimately be conducive to improving and stabilizing the process. The theoretical parts are the basic attitudes and practices methodology of SPC, especially classical Shewhart control charts. The next section describes the current status in Strojírny Třinec, a.s. and the manufacturing process of the base plates. Followed by application of control charts for a given quality features and analysis using statistical software. Based on the evaluation are findings and recommendations for long-term monitoring of the defined quality features.
18
Love, Nicole S. (Nicole Sharlene). "Statistical process control charts for the computer-aided fabrication environment". Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/35437.
19
Huang, Wandi. "GLR Control Charts for Monitoring a Proportion". Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/40405.
Abstract (sommario):
The generalized likelihood ratio (GLR) control charts are studied for monitoring a process proportion of defective or nonconforming items. The type of process change considered is an abrupt sustained increase in the process proportion, which implies deterioration of the process quality. The objective is to effectively detect a wide range of shift sizes.
For the first part of this research, we assume samples are collected using rational subgrouping with sample size n>1, and the binomial GLR statistic is constructed based on a moving window of past sample statistics that follow a binomial distribution. Steady state performance is evaluated for the binomial GLR chart and the other widely used binomial charts. We find that in terms of the overall performance, the binomial GLR chart is at least as good as the other charts. In addition, since it has only two charting parameters that both can be easily obtained based on the approach we propose, less effort is required to design the binomial GLR chart for practical applications.
The second part of this research develops a Bernoulli GLR chart to monitor processes based on the continuous inspection, in which case samples of size n=1 are observed. A constant upper bound is imposed on the estimate of the process shift, preventing the corresponding Bernoulli GLR statistic from being undefined. Performance comparisons between the Bernoulli GLR chart and the other charts show that the Bernoulli GLR chart has better overall performance than its competitors, especially for detecting small shifts.Ph. D.
20
Ryan, Anne Garrett. "Surveillance of Poisson and Multinomial Processes". Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/26549.
Abstract (sommario):
As time passes, change occurs. With this change comes the need for surveillance. One may be a technician on an assembly line and in need of a surveillance technique to monitor the number of defective components produced. On the other hand, one may be an administrator of a hospital in need of surveillance measures to monitor the number of patient falls in the hospital or to monitor surgical outcomes to detect changes in surgical failure rates. A natural choice for on-going surveillance is the control chart; however, the chart must be constructed in a way that accommodates the situation at hand. Two scenarios involving attribute control charting are investigated here. The first scenario involves Poisson count data where the area of opportunity changes. A modified exponentially weighted moving average (EWMA) chart is proposed to accommodate the varying sample sizes. The performance of this method is compared with the performance for several competing control chart techniques and recommendations are made regarding the best preforming control chart method. This research is a result of joint work with Dr. William H. Woodall (Department of Statistics, Virginia Tech). The second scenario involves monitoring a process where items are classified into more than two categories and the results for these classifications are readily available. A multinomial cumulative sum (CUSUM) chart is proposed to monitor these types of situations. The multinomial CUSUM chart is evaluated through comparisons of performance with competing control chart methods. This research is a result of joint work with Mr. Lee J. Wells (Grado Department of Industrial and Systems Engineering, Virginia Tech) and Dr. William H. Woodall (Department of Statistics, Virginia Tech).Ph. D.
21
Urbieta, Pablo Cezar. "Gráficos CUSUM e EWMA para monitorar dados de contagem com distribuição binominal negativa". Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3136/tde-30092016-143355/.
Abstract (sommario):
Gráficos de controle têm sido amplamente utilizados na manufatura para melhoria de processos. Diversas abordagens tem sido propostas para melhorar o desempenho dos gráficos existentes na literatura. Além disso, o uso de gráficos de controle tem se estendido para outras áreas, tais como, economia, finanças, medicina, etc. O objetivo deste trabalho é comparar o gráfico CUSUM com o gráfico EWMA para monitoramento do número diário de internações hospitalares. Para tanto, utilizou-se uma série histórica de internações devido a doenças respiratórias para a população acima de 65 anos. Um modelo linear foi ajustado considerando que o número de internações segue uma distribuição Binomial Negativa. São simulados diversos cenários de mudança no número médio de internações e utilizando diferentes estatísticas baseadas em transformações, é feita uma comparação entre estes gráficos. Verifica-se que o gráfico EWMA com limite de controle assintótico possui desempenho muito similar ao gráfico CUSUM. Já o EWMA implementado com limite de controle exato apresenta melhor desempenho em relação ao gráfico CUSUM quando se atribui pesos menores aos dados atuais.Control charts have been widely used for process improvement in manufacturing. In literature several approaches have been proposed to improve the current charts performance. In addition, the use of control charts has been extended to other areas such as economics, finance, medicine, and others. The objective of this study is to compare CUSUM control chart with EWMA control chart for monitoring daily number of hospital admissions. Using a historical hospitalizations series due to respiratory diseases for people over 65 years old, a Negative Binomial regression model is fitted. Several scenarios are simulated using different shifts in the mean and using different statistics based on transformations, in order to compare these charts. It is shown that EWMA control chart with asymptotic control limit has similar performance as CUSUM control chart. However, using smaller values for new observations the EWMA control chart with exact control limit has better performance than CUSUM control chart.
22
Gremyr, Andreas. "Tracking Change : Usefulness of Statistical Process Control in Improving Psychiatric Care". Thesis, Hälsohögskolan, Högskolan i Jönköping, The Jönköping Academy for Improvement of Health and Welfare, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-30242.
Abstract (sommario):
Healthcare is facing great challenges and psychiatric care is no exception. Extensive attempts to improve quality are made. It is essential to use methods that enable learning from experience, to improve performance. The core feature of Statistical Process Control (SPC), the control charts, are in use in various settings to enable learning and to support quality improvement work, but its use in psychiatric settings are scarce. This master´s thesis explores the usefulness of control charts, in quality improvement work. This was done in a case study at a department of psychosis by addressing two questions related to: a) control chart’s contribution to knowledge on if, when, where and how changes occur, and 2) how usefulness of control charts is perceived at the department. Control charts were applied to important variables and development officer’s and manager’s thoughts on usefulness were analysed using pattern matching. The use of charts shows shifts and differences between wards related to ongoing improvement projects. There is a readiness to start using control charts. The perceived usefulness matches the benefits and challenges identified in literature. Control charts as a tool supporting continuous improvement work in a psychiatric context, has a great potential still awaiting its use.
23
Zhu, Haipei. "Implementation of statistical process control in a high volume machining center : importance of control charts". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101530.
Abstract (sommario):
Thesis: M. Eng. in Manufacturing, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2015.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 83-84).
This thesis focuses on application of statistical process control (SPC) and control charts in a high volume machining center at Waters Corporation. The company has a need of a real time inspection and control methodology so that new hires as well as experienced operators can produce machined parts with high quality and low scrap rates. This thesis project was conducted by Zhu, Zhang and Udayshankar as a team, developing and applying multiple components of SPC at Waters. Zhang's thesis focuses on Gage Repeatability & Reproducibility and Udayshankar's thesis focuses on standard operating procedures (SOPs). An SPC methodology flow chart is designed specifically for the company based on theoretical review of SPC methods and baseline data collection. Initially, the column machining process was out of control due to existing assignable causes such as tool breakage and tool wear. After an SOP is designed and operators trained to follow the SOP, the process was brought back into statistical control. A sampling plan is determined and individual control charts are used to achieve real time inspection in the long term. As a result, scrap rate was reduced from 8% to 4% and potential savings in the column area is higher than $200,000. The SPC methodology will be scaled up to the entire machining center in the near future, which will have a potential annual savings of $600,000. At the end of this thesis project, recommendations are made to Waters Corporation to help it maintain its status as a world class manufacturer. Major recommendations are to implement a database system for quality control, root cause analysis, training program and continuous process improvements.
by Haipei Zhu.
M. Eng. in Manufacturing
24
Hudečková, Eva. "Statistické řízení procesů". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2014. http://www.nusl.cz/ntk/nusl-231244.
Abstract (sommario):
The master´s thesis deals with the problem of statistical process control. The theoretical part describes the basic quality tools and new quality tools, as a tool for collecting, recording, classifying, and analyzing data. The knowledge gained from the theoretical part are used to describe processes in the company Heat Transfer Systems s.r.o., analyze sticking points, control plans updating and to statistical process control in the organization.
25
Buriánková, Alena. "Analýza zmetkovitosti ve výrobním procesu". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-402585.
Abstract (sommario):
The master’s thesis is focused on the reduction of rejection rate in production of plastic bowls with the use of statistic methods. The theoretical part of this thesis describes among others Statistical Process Control, Process capability and types regulatory diagrams. The basis for the practical part is data collection over a certain period of production, from which the percentage of the rejection rate is evaluated. Experiments and corrective actions are designed to improve the process and thereby reduce scrap.
26
Nam, Kyungdoo T. "A Heuristic Procedure for Specifying Parameters in Neural Network Models for Shewhart X-bar Control Chart Applications". Thesis, University of North Texas, 1993. https://digital.library.unt.edu/ark:/67531/metadc278815/.
Abstract (sommario):
This study develops a heuristic procedure for specifying parameters for a neural network configuration (learning rate, momentum, and the number of neurons in a single hidden layer) in Shewhart X-bar control chart applications. Also, this study examines the replicability of the neural network solution when the neural network is retrained several times with different initial weights.
27
Edwards, Christopher Lance. "IMPROVEMENT OF STATISTICAL PROCESS CONTROL AT ST. JUDE MEDICAL'S CARDIAC MANUFACTURING FACILITY". DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/771.
Abstract (sommario):
Sig sigma is a methodology where companies strive to reproduce results ending up having a 99.9996% chance their product will be void of defects. In order for companies to reach six sigma, statistical process control (SPC) needs to be introduced. SPC has many different tools associated with it, control charts being one of them. Control charts play a vital role in managing how a process is behaving. Control charts allow users to identify special causes, or shifts, and can therefore change the process to keep producing good products, free of defects.
There are many factories and manufacturing facilities having implemented some sort of statistical process control. St. Jude Medical implemented control charts to monitor different tools on the manufacturing line. How the data is entered and stored poses a difficult situation for the person monitoring the processes. The program used to keep the control charts is not user friendly and difficult to use. Another program can be produced to provide a greater level of efficiency.
The goals of this project are to stress how important control charts are in the manufacturing world, what problems are currently seen for operators and supervisors, and how a new and improved program can help fix the current situation. This paper goes into the reasons for the change as well has what has been improved.
28
Wang, Ning. "GLR Control Charts for Monitoring Correlated Binary Processes". Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/52981.
Abstract (sommario):
When monitoring a binary process proportion p, it is usually assumed that the binary observations are independent. However, it is very common that the observations are correlated with p being the correlation between two successive observations.
The first part of this research investigates the problem of monitoring p when the binary observations follow a first-order two-state Markov chain model with p remaining unchanged. A Markov Binary GLR (MBGLR) chart with an upper bound on the estimate of p is proposed to monitor a continuous stream of autocorrelated binary observations treating each observation as a sample of size n=1. The MBGLR chart with a large upper bound has good overall performance over a wide range of shifts. The MBGLR chart is optimized using the extra number of defectives (END) over a range of upper bounds for the MLE of p. The numerical results show that the optimized MBGLR chart has a smaller END than the optimized Markov binary CUSUM.
The second part of this research develops a CUSUM-pp chart and a GLR-pp chart to monitor p and p simultaneously. The CUSUM-pp with two tuning parameters is designed to detect shifts in p and p when the shifted values are known. We apply two CUSUM-pp charts as a chart combination to detect increases in p and increases or decreases in p. The GLR-pp chart with an upper bound on the estimate of p, and an upper bound and a lower bound on the estimate of p works well when the shifts are unknown. We find that the GLR-pp chart has better overall performance.
The last part of this research investigates the problem of monitoring p with p remains at the target value when the correlated binary observations are aggregated into samples with n>1. We assume that samples are independent and there is correlation between the observations in a sample. We proposed some GLR and CUSUM charts to monitor p and the performance of the charts are compared. The simulation results show MBNGLR has overall better performance than the other charts.Ph. D.
29
Szarka, John Louis III. "Surveillance of Negative Binomial and Bernoulli Processes". Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/26617.
Abstract (sommario):
The evaluation of discrete processes are performed for industrial and healthcare processes. Count data may be used to measure the number of defective items in industrial applications or the incidence of a certain disease at a health facility. Another classification of a discrete random variable is for binary data, where information on an item can be classified as conforming or nonconforming in a manufacturing context, or a patient's status of having a disease in health-related applications.
The first phase of this research uses discrete count data modeled from the Poisson and negative binomial distributions in a healthcare setting. Syndromic counts are currently monitored by the BioSense program within the Centers for Disease Control and Prevention (CDC) to provide real-time biosurveillance. The Early Aberration Reporting System (EARS) uses recent baseline information comparatively with a current day's syndromic count to determine if outbreaks may be present. An adaptive threshold method is proposed based on fitting baseline data to a parametric distribution, then calculating an upper-tailed p-value. These statistics are then converted to an approximately standard normal random variable. Monitoring is examined for independent and identically distributed data as well as data following several seasonal patterns. An exponentially weighted moving average (EWMA) chart is also used for these methods. The effectiveness of these methods in detecting simulated outbreaks in several sensitivity analyses is evaluated.
The second phase of research explored in this dissertation considers information that can be classified as a binary event. In industry, it is desirable to have the probability of a nonconforming item, p, be extremely small. Traditional Shewhart charts such as the p-chart, are not reliable for monitoring this type of process. A comprehensive literature review of control chart procedures for this type of process is given. The equivalence between two cumulative sum (CUSUM) charts, based on geometric and Bernoulli random variables is explored. An evaluation of the unit and group--runs (UGR) chart is performed, where it is shown that the in--control behavior of this chart is quite misleading and should not be recommended for practitioners.Ph. D.
30
Peng, Yiming. "GLR Control Charts for Process Monitoring with Sequential Sampling". Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/50819.
Abstract (sommario):
The objective of this dissertation is to investigate GLR control charts based on a sequential sampling scheme (SS GLR charts). Phase II monitoring is considered and the goal is to quickly detect a wide range of changes in the univariate normal process mean parameter and/or the variance parameter. The performance of the SS GLR charts is evaluated and design guidelines for SS GLR charts are provided so that practitioners can easily apply the SS GLR charts in applications. More specifically, the structure of this dissertation is as follows:
We first develop a two-sided SS GLR chart for monitoring the mean μ of a normal process. The performance of the SS GLR chart is evaluated and compared with other control charts. The SS GLR chart has much better performance than that of the fixed sampling rate GLR chart. It is also shown that the overall performance of the SS GLR chart is better than that of the variable sampling interval (VSI) GLR chart and the variable sampling rate (VSR) CUSUM chart. The SS GLR chart has the additional advantage that it requires fewer parameters to be specified than other VSR charts. The optimal parameter choices are given, and regression equations are provided to find the limits for the SS GLR chart.
If detecting one-sided shifts in μ is of interest, the above SS GLR chart can be modified to be a one-sided chart. The performance of this modified SS GLR chart is investigated.
Next we develop an SS GLR chart for simultaneously monitoring the mean μ and the variance 𝜎² of a normal process. The performance and properties of this chart are evaluated. The design methodology and some illustrative examples are provided so that the SS GLR chart can be easily used in applications. The optimal parameter choices are given, and the performance of the SS GLR chart remains very good as long as the parameter choices are not too far away from the optimized choices.Ph. D.
31
Vidová, Katarína. "Statistické vlastnosti regulačních diagramů a modelů způsobilosti". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417799.
Abstract (sommario):
The diploma thesis is focused on process stability and capability assessment. It describes certain types of control charts, basic capability indices as well as Box-Cox transformation. The practical part of the study is concerned with applying control charts on generated data and consequently on real data. By this, it focuses on comparing various methods of estimating sample standard deviation and on the impact of non-compliance with the assumption of normal distribution of process variable on process stability and capability assessment.
32
Kubíček, Jan. "Statistická podpora procesu řízení firmy". Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-443764.
Abstract (sommario):
Master’s thesis describes statistical process control as a support for company management. Statistical process control methods and tools are introduced. Requirements for automotive industry are stated specifically for IATF 16949 standard and VDA 6.3 process audit method. Thesis presents current state in company Sanmina-SCI Czech Republic s.r.o regarding statistical regulation. Applies statistical process controls into the new process considering automotive requirements. It is all happening together with a new business introduction of automotive customer.
33
Megahed, Fadel M. "The Use of Image and Point Cloud Data in Statistical Process Control". Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/26511.
Abstract (sommario):
The volume of data acquired in production systems continues to expand. Emerging imaging technologies, such as machine vision systems (MVSs) and 3D surface scanners, diversify the types of data being collected, further pushing data collection beyond discrete dimensional data. These large and diverse datasets increase the challenge of extracting useful information. Unfortunately, industry still relies heavily on traditional quality methods that are limited to fault detection, which fails to consider important diagnostic information needed for process recovery. Modern measurement technologies should spur the transformation of statistical process control (SPC) to provide practitioners with additional diagnostic information. This dissertation focuses on how MVSs and 3D laser scanners can be further utilized to meet that goal. More specifically, this work: 1) reviews image-based control charts while highlighting their advantages and disadvantages; 2) integrates spatiotemporal methods with digital image processing to detect process faults and estimate their location, size, and time of occurrence; and 3) shows how point cloud data (3D laser scans) can be used to detect and locate unknown faults in complex geometries. Overall, the research goal is to create new quality control tools that utilize high density data available in manufacturing environments to generate knowledge that supports decision-making beyond just indicating the existence of a process issue. This allows industrial practitioners to have a rapid process recovery once a process issue has been detected, and consequently reduce the associated downtime.Ph. D.
34
Lee, Hyun Cheol. "Robust design of control charts for autocorrelated processes with model uncertainty". Texas A&M University, 2004. http://hdl.handle.net/1969.1/2778.
Abstract (sommario):
Statistical process control (SPC) procedures suitable for autocorrelated processes have been extensively investigated in recent years. The most popular method is the residual-based control chart. To implement this method, a time series model, which is usually an autoregressive moving average (ARMA) model, of the process is required. However, the model must be estimated from data in practice and the resulting ARMA modeling errors are unavoidable. Residual-based control charts are known to be sensitive to ARMA modeling errors and often suffer from inflated false alarm rates. As an alternative, control charts can be applied directly to the autocorrelated data with widened control limits. The widened amount is determined by the autocorrelation function of the process. The alternative method, however, can not be also free from the effects of modeling errors because it relies on an accurate process model to be effective.
To compare robustness to the ARMA modeling errors between the preceding two kinds of methods for control charting autocorrelated data, this dissertation investigates the sensitivity analytically. Then, two robust design procedures for residual-based control charts are developed from the result of the sensitivity analysis. The first approach for robust design uses the worst-case (maximum) variance of a chart statistic to guarantee the initial specification of control charts. The second robust design method uses the expected variance of the chart statistic. The resulting control limits are widened by an amount that depends on the variance of chart statistic - maximum or expected - as a function of (among other things) the parameter estimation error covariances.
35
Kaya, Yaren Bilge. "Statistical Monitoring of Queuing Networks". Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7534.
Abstract (sommario):
Queuing systems are important parts of our daily lives and to keep their operations at an efficient level they need to be monitored by using queuing Performance Metrics, such as average queue lengths and average waiting times. On the other hand queue lengths and waiting times are generally random variables and their distributions depend on different properties like arrival rates, service times, number of servers. We focused on detecting the change in service rates in this report. Therefore, we monitored queues by using Cumulative Sum(CUSUM) charts based on likelihood ratios and compared the Average Run Length values of different service rates.
36
Ferreira, Paula de Oliveira. "Utiliza??o do controle estat?stico do processo para monitoramento do peso m?dio de c?psulas de Tuberculost?ticos: estudo de caso no NUPLAM- RN". Universidade Federal do Rio Grande do Norte, 2008. http://repositorio.ufrn.br:8080/jspui/handle/123456789/14894.
Abstract (sommario):
Made available in DSpace on 2014-12-17T14:52:39Z (GMT). No. of bitstreams: 1
PaulaOF.pdf: 1749658 bytes, checksum: c5a7f0123f17bea5eee66bccfbc7edd0 (MD5)
Previous issue date: 2008-08-29Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior
This Master Thesis presents a case study on the use of Statistical Process Control (SPC) at the N?cleo de Pesquisas em Alimentos e Medicamentos (NUPLAM). The SPC basic tools have been applied in the process of the tuberculost?ticos drugs encapsulation, primarily concerning the objective to choose, between two speeds, which one is the best one to perform the tuberculostatics encapsulation. Later on, with the company effectively operating, the SPC was applied intending to know the variability of the process and, through the tracking of the process itself, to arrive at an estimated limit for the control of future lots of tuberculostatics of equal dosage. As special causes were detected acting in the process, a cause-and-effect diagram was built in order to try to discover, in each factor that composes the productive process, the possible causes of variation of the capsules average weight. The hypotheses raised will be able to serve as a base for deepened the study to eliminate or reduce these interferences in the process. Also a study on the capacity of the process to attend the specifications was carried out, and this study has shown the process?s inaptitude to take care of them. However, on the side of NUPLAM exists a real yearning to implant the SPC and consequently to improve the existing quality already present on its medicines
Esta disserta??o apresenta um estudo de caso sobre a utiliza??o do Controle Estat?stico do Processo (CEP) no N?cleo de Pesquisas em Alimentos e Medicamentos (NUPLAM). As ferramentas b?sicas do CEP foram aplicadas no processo de encapsulamento de tuberculost?ticos primeiramente com o objetivo de escolher entre duas velocidades qual a melhor para a realiza??o do encapsulamento dos tuberculost?ticos. Posteriormente, com a empresa efetivamente funcionando, o CEP foi aplicado com o intuito de conhecer a variabilidade do processo e atrav?s do monitoramento do mesmo chegar a um limite de controle estimado para o controle de lotes futuros de tuberculost?ticos que possuam a mesma dosagem do tuberculost?tico monitorado. Como foram detectadas causas especiais atuando no processo, um diagrama de causa-e- efeito foi constru?do a fim de tentar descobrir em cada fator que comp?e o processo produtivo as poss?veis causas de varia??o do peso m?dio das c?psulas. As hip?teses levantadas poder?o servir de base para um estudo mais aprofundado para a elimina??o ou redu??o dessas interfer?ncias no processo. Tamb?m foi realizado um estudo sobre a capacidade do processo em atender ?s especifica??es o qual se mostrou incapaz de atend?-las. Contudo, existe por parte do NUPLAM um real anseio em implantar o CEP e conseq?entemente melhorar a qualidade j? existente em seus medicamentos
37
Hack, Pedro da Silva. "Influência da incerteza de medição no uso de cartas de controle". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2012. http://hdl.handle.net/10183/61367.
Abstract (sommario):
A incerteza de medição ainda é tema de estudo e desenvolvimento, mesmo quase vinte anos após o lançamento do ISO GUM, que definiu um padrão internacional para o cálculo de incerteza. Mesmo assim, poucos estudos tratam da interface entre a incerteza de medição e outros aspectos da qualidade industrial, em especial ferramentas de controle de processo como cartas de controle. Assim, o objetivo deste trabalho é estudar os efeitos da incerteza em cartas de controle e identificar sob quais situações de aplicação ela exerce maior influência. Foi feito um mapeamento dos artigos publicados entre 2004 e 2010 sobre incerteza de medição, para identificar quais as metodologias de cálculo e abordagem são mais utilizadas. Na sequência, foi desenvolvido um método incluir nas cartas de controle a incerteza do sistema de medição, modificando as probabilidades de erros tipo I e tipo II. Finalmente, foi elaborada uma simulação computacional utilizando o método desenvolvido, para que fosse possível analisar quais as situações nas quais a incerteza de medição deve ser obrigatoriamente considerada e quais ela pode ser negligenciada.The measurement uncertainty is still subject of study and development, even almost twenty years after the release of the ISO GUM, which set an international standard for the its calculation. Still, few studies have addressed the interface between the measurement uncertainty and other aspects of industrial quality, in particular process control tools like control charts. The objective of this work is to study the effects of measurement uncertainty on control charts and to identify the situations in which its application exerts greater influence. A research was made, mapping of the articles published between 2004 and 2010 regarding measurement uncertainty, aiming to identify which calculation methods and approaches are most widely used. After, a method was developed to include uncertainty of the measurement system in control charts, modifying the probabilities of type I and type II errors. Finally, it was created a computer simulation using the method developed, to make it possible to analyze those situations in which the measurement uncertainty must be considered and which it can be neglected.
38
Tonini, Enrico. "General Profile Monitoring Through Nonparametric Techniques". Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3423081.
Abstract (sommario):
This Ph.D. thesis is devoted to Statistical Process Control (SPC) methods for monitoring over time the stability of a relation between two variables (profile). Very often in literature the functional form of the relation is assumed to be known, whereas in this work we concentrated on generic and unknown relations which have to be estimated with the usual nonparametric regression techniques. The original contributes are two, resented in chapters 2 and 3 respectively. In Chapter 1 we make a brief overview on the topic in order to make you become familiar with these specific problems of Statistical Process Control (SPC) applications and we introduce you to the
original parts of this work. In Chapter 2 we envelope and compare five new control charts for monitoring on-line unknown general, and not only linear, relations among variables over time under the assumption of the normality of the errors; these charts combine in an original way the following techniques: self-starting methods, useful to drop the distinction between Phase I and Phase II of the analysis; very known multivariate charting schemes as MEWMA and CUSCORE; nonparametric testing techniques as wavelet methods and kernel linear smoothing. In Chapter 3, instead, we construct a test statistic useful to check with a completely nonparametric procedure the
stability of a process retrospectively, thus off-line. Both second and third chapters are structured in the following way: brief literature review; framework and model considered in our study; simulation study; a section with some useful complements on the topics and relative research carried out; conclusion and suggestions for future research.Questa tesi è dedicata ai metodi per il Controllo Statistico della Qualità (CSQ) per il monitoraggio della stabilità nel tempo della relazione tra due variabili (profilo). Spesso in letteratura si assume nota la forma funzionale della relazione, viceversa in questo lavoro ci si è concentrati su relazioni generiche ed ignore e quindi da stimare con le usuali tecniche di regressione non parametrica. I contributi originali sono due, presentati nei capitoli 2 e 3 rispettivamente. Nel Capitolo 1 presentiamo una breve panoramica dell’argomento in modo da far prendere familiarità al lettore con questi problemi specifici delle applicazioni del Controllo Statistico della Qualità (CSQ) e introdurlo alle parti originali di questo lavoro. Nel Capitolo 2 sviluppiamo e confrontiamo cinque nuove carte di controllo per il monitoraggio on-line di relazioni ignote generiche, e non solo lineari, tra variabili sotto l’assunzione di normalità degli errori; queste carte mettono insieme in modo originale le seguenti tecniche: metodi self-starting, utili per eliminare la distinzione tra Fase I e Fase II dell’analisi; alcune carte di controllo multivariate ben note come MEWMA e CUSCORE; tecniche non parametriche per la verifica di ipotesi come metodi wavelet o il lisciamento lineare con il metodo del kernel. Nel Capitolo 3, invece, costruiamo una statistica test utile per verificare con una procedura completamente non parametrica la stabilità di un processo in maniera retrospettiva, quindi off-line. Sia il secondo che il terzo capitolo sono strutturati nel modo seguente: breve revisione della letteratura; contesto e modello considerati in questo studio; simulazioni; una sezione con alcuni complementi utili sugli argomenti e relativa ricerca effettuata; conclusione e suggerimenti per la ricerca futura.
39
Lee, Joongsup. "New control charts for monitoring univariate autocorrelated processes and high-dimensional profiles". Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42711.
Abstract (sommario):
In this thesis, we first investigate the use of automated variance estimators in distribution-free statistical process control (SPC) charts for univariate autocorrelated processes. We introduce two variance estimators---the standardized time series overlapping area estimator and the so-called quick-and-dirty autoregressive estimator---that can be obtained from a training data set and used effectively with distribution-free SPC charts when those charts are applied to processes exhibiting nonnormal responses or correlation between successive responses. In particular, we incorporate the two estimators into DFTC-VE, a new
distribution-free tabular CUSUM chart developed for autocorrelated processes; and we compare its performance with other state-of-the-art distribution-free SPC charts. Using either of the two variance estimators, the DFTC-VE outperforms its competitors in terms of both in-control and
out-of-control average run lengths when all the competing procedures are tested on the same set of independently sampled realizations of selected
autocorrelated processes with normal or nonnormal noise components.
Next, we develop WDFTC, a wavelet-based distribution-free CUSUM chart for detecting shifts in the mean of a high-dimensional profile with noisy components that may exhibit nonnormality, variance heterogeneity, or correlation between profile components. A profile describes the relationship between a selected quality characteristic and an input (design) variable over the experimental region. Exploiting a discrete wavelet transform (DWT) of the mean in-control profile, WDFTC selects a reduced-dimension vector of the associated DWT components from which the mean in-control profile can be
approximated with minimal weighted relative reconstruction error. Based on randomly sampled Phase I (in-control) profiles, the covariance matrix of the corresponding reduced-dimension DWT vectors is estimated using a matrix-regularization method; then the DWT vectors are aggregated (batched) so that the nonoverlapping batch means of the reduced-dimension DWT vectors
have manageable covariances. To monitor shifts in the mean profile during Phase II operation, WDFTC computes a Hotelling's T-square--type statistic from successive nonoverlapping batch means and applies a CUSUM procedure to those statistics, where the associated control limits are evaluated
analytically from the Phase I data. We compare WDFTC with other state-of-the-art profile-monitoring charts using both normal and nonnormal
noise components having homogeneous or heterogenous variances as well as independent or correlated components; and we show that WDFTC performs well, especially for local shifts of small to medium size, in terms of both in-control and out-of-control average run lengths.
40
Noronha, Rossano Santos. "Projeto Econômico da Carta de Controle X : um modelo com custos dependentes dos desvios". Universidade do Vale do Rio dos Sinos, 2017. http://www.repositorio.jesuita.org.br/handle/UNISINOS/6276.
Abstract (sommario):
Submitted by JOSIANE SANTOS DE OLIVEIRA (josianeso) on 2017-05-22T13:46:14Z
No. of bitstreams: 1
Rossano Santos Noronha_.pdf: 585085 bytes, checksum: 88117b318c3e9c30134fce5bf0bdc22e (MD5)Made available in DSpace on 2017-05-22T13:46:14Z (GMT). No. of bitstreams: 1 Rossano Santos Noronha_.pdf: 585085 bytes, checksum: 88117b318c3e9c30134fce5bf0bdc22e (MD5) Previous issue date: 2017-03-07
CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Devido à dificuldade em se estimar os custos de operação associados ao monitoramento estatístico do processo nos trabalhos identificados na literatura, este trabalho tem por objetivo propor um modelo de otimização econômico para a carta de controle _X que considere as incertezas em relação aos custos variáveis e dependentes do desvio em relação à média do processo. O levantamento bibliográfico efetuado auxiliou no entendimento de como a incerteza em relação aos custos na utilização das cartas de controle são tratados. Percebeu-se o tratamento dos custos bem como do parâmetro de desvio do processo em relação a média _ como variáveis discretas e que impactavam na carta. A proposta aqui apresentada consiste em tratar não apenas o desvio em relação a média mas também dois dos custos associados à operação da carta de controle _X como variáveis aleatórias de distribuição contínua, inserindo assim um componente de incerteza na sua estimação. Desenvolveu-se assim uma nova formulação para o problema de otimização. Foram escolhidas instâncias para a otimização e comparados os resultados com os obtidos por autores da literatura. Os resultados foram obtidos por meio da metaheurística simulated annealing. Como resultados, o método mostrou-se eficiente, mostrando que o nível de dependência entre o parâmetro de mudança de processo e o custo e, da incerteza que se tem quanto aos valores definidos de custo de operação impactam nos custos totais de operação do CEP. A principal contribuição deste trabalho de pesquisa está na apresentação de uma formulação matemática de otimização da carta de controle _X que trata não somente o desvio em relação à média do processo mas também os custos de operação do CEP como variáveis aleatórias. A originalidade da formulação está em considerar os custos linearmente dependentes do tamanho do desvio do processo em relação a sua média.
Due to the difficulty in estimating the operating costs associated to the statistical monitoring of the process described in the literature, this paper aims to propose a model of economic optimization for the _X control chart that considers the uncertainties in relation to the variable costs and dependent on the deviation in relation to the average of the process. The literature review performed supported the understanding of how the uncertainty in relation to costs in the use of control charts is treated. The treatment of the costs as well as the parameter of deviation of the process in relation to the _ average were indicated as discrete variables and that impacted on the chart. The proposal presented here consists of treating not only the deviation from the mean but also two costs associated with the operation of the _X control chart as random variables of continuous distribution, thus inserting a component of uncertainty in its estimation. A new formulation for the optimization problem was developed. Instances for optimization were chosen and the results were compared with those obtained by authors described in the literature. The results were obtained through simulated annealing metaheuristics. As a result, the method proved to be efficient, showing that the level of dependence between the process change parameter and the cost, as well as the uncertainty regarding the defined operating cost values impact on the total cost of operation of the SPC. The main contribution of this research work is the presentation of a mathematical formulation of optimization of the _X control chart that treats not only the deviation in relation to the average of the process but also the operating costs of the SPC as random variables. The originality of the formulation is to consider costs linearly dependent on the size of the process deviation in relation to its mean.
41
Assareh, Hassan. "Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals". Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/53342/1/Hassan_Assareh_Thesis.pdf.
Abstract (sommario):
Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods.
Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses.
Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle.
Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time.
Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained.
Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated.
The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital.
The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model.
The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered.
The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.
42
Hassan, Sara. "IMPLEMENTERING AV STATISTISK PROCESSTYRNING VID SMÅ SERIER". Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-27810.
Abstract (sommario):
Statistisk processtyrning, SPS, är ett välkänt verktyg som används för kvalitetsförbättringar inom organisationer världen över. De senaste åren har tillverkande organisationer tenderat att gå mot kortare serier, vilket medför en problematik när de vill tillämpa statistiska metoder som är utvecklade för traditionell masstillverkning. Framgångsfaktorer för implementering av SPS vid små serier är ett relativt outforskat område och kräver därför ytterligare forskning. Syftet med denna studie var att ta fram en modell över hur SPS framgångsrikt kan implementeras av organisationer med små serier och en stor detaljflora. För att besvara syftet genomfördes en fallstudie med både kvantitativ och kvalitativ metod. Deltagande observationer och en workshop med 15 deltagare utfördes för att identifiera existerande variationer samt definiera nuläget i det avgränsade produktionsflödet, vars processer studerades i studien. Tre produktfamiljer och kritiska parametrar som representerade produktkvalitén valdes ut för att följas upp i styrdiagram. En mätsystemanalys utfördes för att undersöka om de mätdon som i stor utsträckning användes för kvalitetskontroll i processen var tillförlitliga. Styrdiagram upprättades anpassade för små serier och statistiska analyser utfördes för att undersöka om SPS var en användbar metod för kvalitetsförbättringar i processer med små serier. En kvalitativ benchmark med fyra deltagande organisationer utfördes även för att ta del av deras erfarenheter relaterat till implementering och arbete med SPS. Resultatet visade att den studerade organisationen behöver utföra förändringar gällande arbetsmetoder för kvalitetskontroll samt hantering av processer och mätsystem. Det finns även behov av ett omfattande förbättringsarbete, för att eliminera det flertalet orsaker till systematiska variationer som identifierades påverka processerna och produktkvalitén. Dessa förändringar krävs innan en implementering av SPS kan genomföras. Verktyg inom SPS visade sig med framgång kunna användas för att förbättra processer med små serier, vid användning av standardiserade styrdiagram som möjliggör analys av flera produkter i samma diagram. Processer med små serier och en stor detaljflora medför en utökad komplexitet vid statistiska analyser och visar tecken på ett flertal svårigheter som ökar risken för en fallerad implementering. Utifrån analyser av det kvalitativa och kvantitativa resultatet skapades en modell med 15 framgångsfaktorer för implementering av SPS vid små serier. Faktorerna bör följas av organisationer med små serier som vill lyckas med att implementera SPS. Framgångsfaktorerna är följande: (1) Var beredd på en kulturförändring som kräver att SPS vävs in i hela organisationen, (2) Förmedla ett tydligt mål och hållbar strategi för arbetet med SPS, (3) Skapa ett utbrett engagemang i hela organisationen, (4) Utse en SPS-koordinator, (5) Inför utbildning och uppföljning från start, (6) Skapa tvärfunktionella team, (7) Främja samarbete och delaktighet under förbättringsarbetet, (8) Ställ krav på ett dugligt mätsystem, (9) Utför en pilotstudie där det finns intresse, (10) Identifiera kritiska processer, produktfamiljer och parametrar, (11) Börja med att lära känna processerna, (12) Upprätta standardiserade styrdiagram, (13) Tolkning och analys av styrdiagram utförs enligt Montgomerys metod för statistiska analyser, (14) Sträva efter stabila processer, (15) Utför kontinuerlig uppföljning.Statistical process control, SPC, is a widely used technique for quality improvements by companies all over the world. The current trend in manufacturing organizations is directed towards shorter productions runs, which cause problems when applying traditional statistical methods developed for SPC on mass production runs. The critical factors for a successful implementation of SPC on short runs are still not fully explored and require further research. The main purpose of this study was to present a conceptual framework that illustrates the successful implementation of SPC in organizations with short runs and extensive product portfolio. In order to answer the research questions, a case study research methodology with both quantitative and qualitative methods was used. Participant observations and a workshop including 15 participators were performed in order to identify existing process variability’s and current state of the studied production processes. Three product families and key quality characteristics of each product were chosen to be monitored in control charts, based on scrap costs and staff experiences of the production process. A measurement system analysis was used to determine if the gauges, used to make measurement quality controls, were capable. Control charts were constructed and adjusted to short production runs. Statistical analysis was then made on the information gathered through the control charts to determine if statistical tools within SPC was useful for quality improvements on short production runs. Also a qualitative benchmark was performed with four manufacturing companies to take part of their experiences and knowledge related to the implementation and application of SPC. The findings indicate that the studied organization needs to improve working methods related to quality inspections and monitoring of the production processes. The organization also needs to improve the measurement system and make an extensive work of improvement to reduce the many identified special causes of variation that affects the processes and product quality, before implementing SPC in the organization. Findings showed that SPC tools and techniques successfully can be adopted to improve short run production processes when using standardized control charts for different product types. Short run production processes involve more complex statistical analysis which could inhibit the success of an implementation of SPC. The analysis of the qualitative and quantitative findings resulted in a framework including 15 critical success factors for the implementation of SPC in short production runs. All the following critical success factors should be taken into account by organizations with short runs that aspire a successful implementation of SPC: (1) Be ready to make a cultural change including the recognition of the importance of SPC within the whole organization, (2) Communicate a clear goal and long-term strategy, (3) Create motivation and commitment from top management to operators on the shop floor, (4) Select a SPC coordinator, (5) Introduce a training programme with feedback from start, (6) Create cross-functional teams, (7) Stimulate cooperation and participation within the work of improvements, (8) Ensure a capable measurement system, (9) Perform a pilot project with enthusiastic employees, (10) Identify critical processes, product families and key quality characteristics, (11) Focus on exploring process behaviors, (12) Construct standardized control charts, (13) Interpret and analyze control charts according to Montgomery’s method for statistical analysis, (14) Attempt to obtain processes in control, (15) Perform continuous follow ups.
43
Lacina, Michael Allen. "Relationships Between Training Load Metrics and Injury in Collegiate Women's Soccer". Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/100946.
Abstract (sommario):
Injury risk reduction is an ever-evolving topic within an athletic environment. Consequences from an injury include participation time loss, financial, social, and personal costs. Coaching and medical staff strive to reduce the risk through various manners. Training load monitoring is one method that is utilized in injury risk reduction through global positioning systems (GPS) with statistical modeling. The purpose of this study was to investigate the external loads for training sessions and competition in starters versus non-starters; to determine if there were control chart violations associated with sustained injuries; and to determine whether in-season injuries were associate with one or more control chart violations. NCAA Division I female soccer players were recruited during the fall 2019 season. Participants were provided a STATSports GPS unit to wear during all practice and competition sessions to analyze the following variables: total distance, high metabolic load distance, sprints, accelerations, decelerations, and dynamic stress load (DSL). These variables were analyzed using statistical process control charts (SPC Charts) and Nelson Rules. Overall, there were 1,235 violations for the team, with the highest amount coming from DSL. Throughout the season, there were 16 time-loss injuries. Within the 3- and 7-day periods prior to injury, there were only two cases in which the injured athlete had more violations when compared to the team average. Therefore, SPC Charts were not a good indicator of injury risk prediction within this population. Future research includes reassessing these methods within a larger population and for a longer duration (i.e. several seasons).Master of Science
Reducing the risk of injury in athletes is a focal point for many coaches, training, and medical staffs in collegiate athletics. The consequences of injury range from loss of playing time to financial and long-term health costs. Being able to reduce the risk of injuries not only has personal implications for the athlete but also relates to overall team success. Using global positioning systems (GPS) to track the amount of work done in training can possibly reduce injury risk. This study planned to investigate the workload in NCAA Division 1 collegiate female soccer athletes and if any injuries were sustained during both training and competition settings. The results suggest that statistical process control (SPC) charts and the Nelson Rules did not predict injury risk within this population. There is limited research that has used these tools. Future work can reassess these methods within larger collegiate athletic populations, over a longer period of time.
44
Peroutka, Michal. "Využití statistických metod pro zajištění způsobilosti procesu výroby". Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2016. http://www.nusl.cz/ntk/nusl-241569.
Abstract (sommario):
The diploma thesis deals with usage of statistical methods to assure capability of production process. The theoretical part includes the definition of quality management, basic statistical concepts and statistical process control. The practical part presents basic information about the company P & L, spol. s r. o. and analyzes the production process of selected parts. The tools of statistical process control are applied and measures to assure capability of production process are proposed.
45
Cassady, Charles Richard. "Statistical quality control techniques using multilevel discrete product quality measures". Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-06062008-151120/.
46
Mahmoud, Mahmoud A. "The Monitoring of Linear Profiles and the Inertial Properties of Control Charts". Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/29544.
Abstract (sommario):
The Phase I analysis of data when the quality of a process or product is characterized by a linear function is studied in this dissertation. It is assumed that each sample collected over time in the historical data set consists of several bivariate observations for which a simple linear regression model is appropriate, a situation common in calibration applications. Using a simulation study, the researcher compares the performance of some of the recommended approaches used to assess the stability of the process. Also in this dissertation, a method based on using indicator variables in a multiple regression model is proposed.
This dissertation also proposes a change point approach based on the segmented regression technique for testing the constancy of the regression parameters in a linear profile data set. The performance of the proposed change point method is compared to that of the most effective Phase I linear profile control chart approaches using a simulation study. The advantage of the proposed change point method over the existing methods is greatly improved detection of sustained step changes in the process parameters.
Any control chart that combines sample information over time, e.g., the cumulative sum (CUSUM) chart and the exponentially weighted moving average (EWMA) chart, has an ability to detect process changes that varies over time depending on the past data observed. The chart statistics can take values such that some shifts in the parameters of the underlying probability distribution of the quality characteristic are more difficult to detect. This is referred to as the "inertia problem" in the literature. This dissertation shows under realistic assumptions that the worst-case run length performance of control charts becomes as informative as the steady-state performance. Also this study proposes a simple new measure of the inertial properties of control charts, namely the signal resistance. The conclusions of this study support the recommendation that Shewhart limits should be used with EWMA charts, especially when the smoothing parameter is small. This study also shows that some charts proposed by Pignatiello and Runger (1990) and Domangue and Patch (1991) have serious disadvantages with respect to inertial properties.Ph. D.
47
Yontay, Petek. "A Two-sided Cusum For First-order Integer-valued Autoregressive Processes Of Poisson Counts". Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613385/index.pdf.
Abstract (sommario):
Count data are often encountered in manufacturing and service industries due to ease of data collection. These counts can be useful in process monitoring to detect shifts of a process from an in-control state to various out-of-control states. It is usually assumed that the observations are independent and identically distributed. However, in practice, observations may be autocorrelated and this may adversely affect the performance of the control charts developed under the assumption of independence. In this thesis, the cumulative sum (CUSUM) control chart for monitoring autocorrelated processes of counts is investigated. To describe the autocorrelation structure of counts, a Poisson integer-valued autoregressive moving average model of order 1, Poisson INAR(1), is employed. Changes in the process mean in both positive and negative directions are taken into account while designing the CUSUM chart. A trivariate Markov Chain approach is utilized for evaluating the performance of the chart.
48
Dostál, Petr. "Zavedení SPC ve výrobním procesu". Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2010. http://www.nusl.cz/ntk/nusl-222511.
Abstract (sommario):
The thesis deals with implementing of statistical process control (SPC) on CNC cut center into the mechanic production. One part of the project is engaged in theoretical information gathering, process monitoring and data collection. Second part deals with stabilization, regulation and improvement of the process using right statistical instruments. As a result is implementing measuring station from where will be the process data transferred to a server and evaluated. On the basis of that is possible to implement a correction in the right time if the process isn´t stabilized. The main objectives of the thesiss are cost reduction, scrap reduction and modernization of the process.
49
Ječmínková, Michaela. "Využití regulačních diagramů pro kontrolu jakosti". Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2014. http://www.nusl.cz/ntk/nusl-224704.
Abstract (sommario):
This diploma thesis deals with use of Shewhart Control Charts in quality control. The thesis describes the currently used process of quality control in the enterprise. Afterwards practical guidance for implementation of the statistical process control of the selected component and evaluation of capability is provided. An application for creating control charts and monitoring the quality of the product is included.
50
Wang, Sai. "GLR Control Charts for Monitoring the Mean Vector or the Dispersion of a Multivariate Normal Process". Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/77227.
Abstract (sommario):
In many applications, the quality of process outputs is described by more than one characteristic variable. These quality variables usually follow a multivariate normal (MN) distribution. This dissertation discusses the monitoring of the mean vector and the covariance matrix of MN processes.
The first part of this dissertation develops a statistical process control (SPC) chart based on a generalized likelihood ratio (GLR) statistic to monitor the mean vector. The performance of the GLR chart is compared to the performance of the Hotelling Χ² chart, the multivariate exponentially weighted moving average (MEWMA) chart, and a multi-MEWMA combination. Results show that the Hotelling Χ² chart and the MEWMA chart are only effective for a small range of shift sizes in the mean vector, while the GLR chart and some carefully designed multi-MEWMA combinations can give similarly better overall performance in detecting a wide range of shift magnitudes. Unlike most of these other options, the GLR chart does not require specification of tuning parameter values by the user. The GLR chart also has the advantage in process diagnostics: at the time of a signal, estimates of change-point and out-of-control mean vector are immediately available to the user. All these advantages of the GLR chart make it a favorable option for practitioners. For the design of the GLR chart, a series of easy to use equations are provided to users for calculating the control limit to achieve the desired in-control performance. The use of this GLR chart with a variable sampling interval (VSI) scheme has also been evaluated and discussed.
The rest of the dissertation considers the problem of monitoring the covariance matrix. Three GLR charts with different covariance matrix estimators have been discussed. Results show that the GLR chart with a multivariate exponentially weighted moving covariance (MEWMC) matrix estimator is slightly better than the existing method for detecting any general changes in the covariance matrix, and the GLR chart with a constrained maximum likelihood estimator (CMLE) gives much better overall performance for detecting a wide range of shift sizes than the best available options for detecting only variance increases.Ph. D.