A new development of an adaptive X − R control chart under a fuzzy environment
by Hamed Sabahno; Seyed Meysam Mousavi; Amirhossein Amiri
International Journal of Data Mining, Modelling and Management (IJDMMM), Vol. 11, No. 1, 2019

Abstract: It is proved that adaptive control charts have better performance than classical control charts due to adaptability of some or all of their parameters to the previous process information. Fuzzy classical control charts have been occasionally considered by many researchers in the last two decades; however, fuzzy adaptive control charts have not been investigated. In this paper, we introduce a new adaptive X − R fuzzy control chart that allows all of the charts' parameters to adapt based on the process state in the previous sample. Also, the warning limits are redefined in the fuzzy environments. We utilise fuzzy mode defuzzification technique to design the decision procedure in the proposed fuzzy adaptive control chart. Finally, an illustrative example is used to present the application of the proposed control chart.

Online publication date: Wed, 05-Dec-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Mining, Modelling and Management (IJDMMM):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com