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.

When using control charts to monitor a process it is frequently necessary to simultaneously monitor more than one parameter of the process. Multivariate control charts for monitoring the mean vector, for monitoring variance-covariance matrix and for simultaneously monitoring the mean vector and the variance-covariance matrix of a process with a multivariate normal distribution are investigated. A variable sampling interval (VSI) feature is considered in these charts. Two basic approaches for using past sample information in the development of multivariate control charts are considered. The first approach, which is called the combine-accumulate approach, reduces each multivariate observation to a univariate statistic and then accumulates over past samples. The second approach, which is called the accumulate-combine approach, accumulates past sample information for each parameter and then forms a univariate statistic from the multivariate accumulations. Multivariate control charts are compared on the basis of their average time to signal (ATS) performance. The numerical results show that the multivariate control charts based on the accumulate-combine approach are more efficient than the corresponding multivariate control charts based on the combine-accumulate approach in terms of ATS. Also VSI charts are more efficient than corresponding FSI charts. / Ph. D.

Successfully implementing continuous improvement and quality methodologies have been challenging over the past century. Challenges occur in managing change in the organization, which can be effectively addressed through relationship building in concert with strong leadership. Even with solid leadership, change management, and relationship building, initiatives have challenges quantifying and identifying when to intervene in order to keep them on track for success. Creating a quantitative model using a 3-parameter logit s-curve, Blythe S-curve, to illustrate the growth and decay of the handoff of projects to the process owner will allow leadership the knowledge and direction to keep the initiative moving in a positive direction. Leveraging the Hotelling T2 multivariate charts on the residuals derived from the Blythe S-curve will give definitive statistical evidence on when to intervene on projects in the earliest possible time frame. Leaders in organizations implementing and actively using change management, relationship building, the Blythe S-curve model, and Hotelling T2 multivariate charts to drive quality and continuous improvement methodologies in their organization will improve the likelihood of success.

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This thesis examines the use of variable sampling intervals as they apply to control charts that use count data. Papers by Reynolds, Arnold, and R. Amin developed properties for charts with an underlying normal distribution. These properties are extended in this thesis to accommodate an underlying Poisson distribution. / Master of Science

An improved quality control model is suggested in this thesis. The improved quality control model is derived by treating the quality control problem as a process control problem. The quality control model is developed by formulating a process control model in terms of product quality parameters and control variables which affect the product quality parameters. SQC is used in the model to provide estimates about the state of the product quality variable as the product is processed by the plant. A state variable approach is used to determine the optimal control strategy. An example quality control model is formulated for a coke size-reduction process. Numerical values are assumed and sensitivity analysis results are discussed. The results show that the proposed quality control model is reasonable. Extensions to more complicated models are discussed. / M.S.

Given the continuing deployment of total quality control and total quality management initiatives by organizations, employees have seen changes in their work environment. Furthermore, the impact of downsizing has resulted in operators becoming responsible for the quality of their own processes. This study tested the impact of various display alternatives of control chart data on decision performance and mental workload.  The control charts were shown as multiple two dimensional displays, a composite two dimensional display, and a composite three dimensional perspective display. Multiple two dimensional displays were found to have significantly higher decision accuracy and decision confidence ratings than either composite displays. No significant difference in decision accuracy and decision confidence ratings was found among the composite displays. The type of display did not have a significant effect on decision time. Mental workload was also found to be significantly affected by the type of display used. Multiple two dimensional displays imposed significantly lower levels of mental workload than either composite display. No significant difference in mental workload was found among the composite displays. These results indicated that multiple two dimensional displays should be used when control chart data from multiple processes must be displayed. / Master of Science

[pt] Este trabalho mostra a implantação de técnicas de Controle Estatístico de Processo (CEP) em uma indústria de cosméticos, em uma situação em que as técnicas convencionais não são aplicáveis. O processo a ser controlado é constituído de oito canais, que produzem em um mesmo instante de tempo oito unidades de um mesmo produto. Tal processo possui a peculiaridade de ter médias variáveis no tempo, mesmo em estado de controle estatístico. Como os métodos de controle propostos na literatura para processos com múltiplos canais têm como premissa médias constantes ao longo do tempo e os canais terem médias e variâncias semelhantes, tais métodos não são aplicáveis ao processo em questão. Para o CEP do processo, então, foi desenvolvida uma metodologia adaptada à realidade da empresa, que conjuga os princípios de group charts e de gráficos de controle de aceitação. Foi ainda realizada uma revisão bibliográfica de algumas técnicas de controle estatístico de processos com múltiplos canais, contemplando métodos tradicionais e não tradicionais. / [en] This study shows the implantation of techniques of Statistical Process Control (SPC) in a cosmetics industry, in a situation in which conventional techniques are not applicable. The process to be controlled is composed of eight streams, which produce eight units of the product at a time. The process has the peculiarity that the means of the streams change in time, even in a condition of statistical control. The control schemes proposed in the literature hitherto for multiple-stream processes assume constant means, and streams with similar means and variance, and are therefore not applicable to this process. A new scheme was then developed for the statistical control of the process, which blends the principles of the group charts and of acceptance control charts. A review was also presented of some techniques of statistical control of multiple-stream processes, including traditional and more recent methods.