A new development of an adaptive X − R control chart under a fuzzy environment
(2019) In International Journal of Data Mining, Modelling and Management 11(1). p.19-44- 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... (More)
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.
(Less)
- author
- Sabahno, Hamed
LU
; Mousavi, Seyed Meysam and Amiri, Amirhossein
- publishing date
- 2019
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Adaptive control charts, Fuzzy uncertainty, Trapezoidal fuzzy numbers, TrFNs, X − R control charts
- in
- International Journal of Data Mining, Modelling and Management
- volume
- 11
- issue
- 1
- pages
- 26 pages
- publisher
- Inderscience Publishers
- external identifiers
-
- scopus:85058177941
- ISSN
- 1759-1163
- DOI
- 10.1504/IJDMMM.2019.096547
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: Copyright © 2019 Inderscience Enterprises Ltd.
- id
- 0e15133f-19c5-4891-95ae-e3082ddf3332
- date added to LUP
- 2025-03-20 12:20:17
- date last changed
- 2025-04-04 14:52:19
@article{0e15133f-19c5-4891-95ae-e3082ddf3332, abstract = {{<p>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.</p>}}, author = {{Sabahno, Hamed and Mousavi, Seyed Meysam and Amiri, Amirhossein}}, issn = {{1759-1163}}, keywords = {{Adaptive control charts; Fuzzy uncertainty; Trapezoidal fuzzy numbers; TrFNs; X − R control charts}}, language = {{eng}}, number = {{1}}, pages = {{19--44}}, publisher = {{Inderscience Publishers}}, series = {{International Journal of Data Mining, Modelling and Management}}, title = {{A new development of an adaptive X − R control chart under a fuzzy environment}}, url = {{http://dx.doi.org/10.1504/IJDMMM.2019.096547}}, doi = {{10.1504/IJDMMM.2019.096547}}, volume = {{11}}, year = {{2019}}, }