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Non parametric control charts for monitoring individuals
Université de Nantes, Nantes

Statistics Engineering 
Full Description:

Control charts are widely adopted to monitor and improve the quality of a process in the field of Statistical Process Monitoring. In typical applications of traditional control charts, they are established on the belief that the observations of a process are assumed to follow a normal or specified probability distribution. However, using analogs of these control charts to monitor process shifts is not justified when the observations are from a non-normal or unknown distribution. Thus, for a nonparametric approach, constructing control charts seems to be a reasonable alternative. The advantages of nonparametric control charts are (i) simplicity, (ii) no requirement for assuming a specified parametric distribution, (iii) increased robustness and efficiency in detecting process shifts, and (iv) their in-control performance is the same for all continuous distributions. Hence, it seems reasonable for quality practitioners to use nonparametric methods in control chart applications.

If several non parametric control charts have already been developped in the case of sample size n>1, few of them are able to handle situations where the sample size reduces to n=1. The goal of this PhD is to propose and investigate the proerties of *new* non parametric control charts for monitoring the position and the dispersion and able to handle samples for which the size is n=1.

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REMARK : this PhD subject is not funded from the french side but candidates with their own funding are welcomed.


Posted on: 01 February 2016Deadline to apply: 30 June 2016Start Date: 01 September 2016 Duration: 36 months
The Fund category is Not Funded and the salary is Not Funded
Doctoral School is Science and technology of information and mathematics (STIM) in the Pays de la Loire Region.

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