Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/78578
Authors: 
Niaki, Seyed Taghi
Khedmati, Majid
Year of Publication: 
2013
Citation: 
[Journal:] Journal of Industrial Engineering International [ISSN:] 2251-712X [Publisher:] SpringerOpen [Place:] Heidelberg [Volume:] 9 [Year:] 2013 [Pages:] 1-11
Abstract: 
In this paper, a new control chart to monitor multi-binomial processes is first proposed based on a transformation method. Then, the maximum likelihood estimators of change points designed for both step changes and linear-trend disturbances are derived. At the end, the performances of the proposed change-point estimators are evaluated and are compared using some Monte Carlo simulation experiments, considering that the real change type presented in a process are of either a step change or a linear-trend disturbance. According to the results obtained, the change-point estimator designed for step changes outperforms the change-point estimator designed for linear-trend disturbances, when the real change type is a step change. In contrast, the change-point estimator designed for linear-trend disturbances outperforms the change-point estimator designed for step changes, when the real change type is a linear-trend disturbance.
Subjects: 
multi-binomial processes
maximum likelihood estimator
multi-attribute processes
step change
linear-trend disturbance
root/power transformation
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/2.0/
Document Type: 
Article

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