Statistical quality control and reliability estimation based on exponentiated inverse rayleigh distribution
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Date
2018
Authors
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Journal ISSN
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Publisher
The University of Dodoma
Abstract
This research gives some statistical quality control techniques and reliability estimation based on exponentiated inverse Rayleigh distribution (EIRD) which can be applied in different industries so as to improve the quality of their products. EIRD has been obtained through generalization process and its mathematical properties were discussed. Estimation of unknown parameters was done by using maximum likelihood method, least square method, weighted least square and percentile estimation method. The methods were compared by using Monte Carlo simulation approach based on the values of bias and MSE, the results show that ML performs well. Further, the estimation of single component stress-strength reliability and multi-component stress-stress reliability was done, confidence intervals of reliability were also obtained and the results show that the methods perform. An attribute control chart is also developed for EIRD under a time truncated life test. The performance of the proposed chart is discussed using average run length (ARL). A simulation study is carried out to obtain the performance of the proposed control chart for monitoring non-conforming items. The results show that the chart is effective in detecting any shift happens in the process. Also Shewhart individual control chart is developed to check whether the data used are in control state or not by using. The results show that the data are not in control.
Description
Dissertation (MSc Statistics)
Keywords
Quality control, Statistical quality control techniques, Rayleigh distribution, Statistical quality control, Rayleigh, Quality control techniques, Exponentiated Inverse Rayleigh Distribution, EIRD, Statistical quality reliability, Statistical quality control estimation
Citation
Mbwambo, S. H. (2018). Statistical quality control and reliability estimation based on exponentiated inverse rayleigh distribution. Dodoma: The University of Dodoma.