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A Power-Transformation Technique in Designing Multi-Attribute C Control Charts
, M.Sc. Thesis Sharif University of Technology ; Akhavan Niaki, Taghi (Supervisor)
Abstract
In a production process, when the quality of a product depends on more than one characteristic, and there is correlation between them, using univariate control charts increases type І and type ΙΙ errors. So for monitoring these processes, multivariate quality control charts are used. Multivariate statistical process control is receiving increased attention in the literature,but little work has been done to deal with multi-attribute processes and just in recent years some techniques are developed in this field. In this thesis, based on the power transformation concept, two new techniques have been developed to monitor multi-attribute processes, in which the defect counts are important. In the...
A Max-EWMA approach to monitor and diagnose faults of multivariate quality control processes
, Article International Journal of Advanced Manufacturing Technology ; Volume 68, Issue 9-12 , 2013 , Pages 2283-2294 ; 02683768 (ISSN) ; Niaki, S. T. A ; Sharif University of Technology
2013
Abstract
A new approach is developed in this paper to detect general mean shifts of multivariate quality control systems and to determine the quality characteristic(s) responsible for the shift. This approach takes advantage of both a decomposition method and an EWMA-based control statistics that are employed for multivariate normal distributions. In order to evaluate the performance of the proposed methodology, simulation studies are provided to estimate the in- and out-of-control average run lengths under different mean and variance shift scenarios. Simulation experiments are also given to compare the performances of the proposed procedure with the ones of the well-known MEWMA and MCUSUM methods....
Decision-making in detecting and diagnosing faults of multivariate statistical quality control systems
, Article International Journal of Advanced Manufacturing Technology ; Volume 42, Issue 7-8 , 2009 , Pages 713-724 ; 02683768 (ISSN) ; Fallah Nezhad, M. S ; Sharif University of Technology
2009
Abstract
A new methodology is proposed in this paper to both monitor an overall mean shift and classify the states of a multivariate quality control system. Based on the Bayesian rule (Montgomery, Introduction to statistical quality control, 5th edn. Wiley, New York, USA, 2005), the belief that each quality characteristic is in an out-of-control state is first updated in an iterative approach and the proof of its convergence is given. Next, the decision-making process of the detection and classification the process mean shift is modeled. Numerical examples by simulation are provided in order to understand the proposed methodology and to evaluate its performance. Moreover, the in-control and...
A Change Point Method for phase II Monitoring of Generalized Linear Profiles with Drift and Multiple Changes
, M.Sc. Thesis Sharif University of Technology ; Mahlouji, Hashem (Supervisor)
Abstract
The aim of this research is to study performance of Rao Score Test control chart in phase II monitoring of generalized linear profiles for drift and multiple changes which can be isotonic or antitonic. Moreover, the performance of the method is compared with two common methods in the generalized linear profile literature: Hotelling T2 and multivariate exponential weighted moving average. Afterward multivariate cumulative sum chart is proposed to be used in monitoring antitonic multiple change in the parameter of Poisson profiles. Finally, a real world example is presented in which Rao Score Test method is applied to real data and the performance of this method is compared with other methods....