模糊环境下自适应X - R控制图的新发展

IF 0.4 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Data Mining Modelling and Management Pub Date : 2019-01-01 DOI:10.1504/IJDMMM.2019.10016838
H. Sabahno, S. Mousavi, A. Amiri
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引用次数: 0

摘要

由于自适应控制图的部分或全部参数对前一过程信息的适应性,证明了自适应控制图比经典控制图具有更好的性能。在过去的二十年里,模糊经典控制图偶尔被许多研究者所考虑;然而,模糊自适应控制图尚未得到研究。在本文中,我们引入了一种新的自适应X - R模糊控制图,它允许所有图表的参数根据前一个样本中的过程状态进行自适应。并对模糊环境下的预警界限进行了重新定义。我们利用模糊模式去模糊化技术来设计模糊自适应控制图的决策过程。最后,通过一个实例说明了所提出的控制图的应用。
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A new development of an adaptive X − R control chart under a fuzzy environment
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.
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来源期刊
International Journal of Data Mining Modelling and Management
International Journal of Data Mining Modelling and Management COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.10
自引率
0.00%
发文量
22
期刊介绍: Facilitating transformation from data to information to knowledge is paramount for organisations. Companies are flooded with data and conflicting information, but with limited real usable knowledge. However, rarely should a process be looked at from limited angles or in parts. Isolated islands of data mining, modelling and management (DMMM) should be connected. IJDMMM highlightes integration of DMMM, statistics/machine learning/databases, each element of data chain management, types of information, algorithms in software; from data pre-processing to post-processing; between theory and applications. Topics covered include: -Artificial intelligence- Biomedical science- Business analytics/intelligence, process modelling- Computer science, database management systems- Data management, mining, modelling, warehousing- Engineering- Environmental science, environment (ecoinformatics)- Information systems/technology, telecommunications/networking- Management science, operations research, mathematics/statistics- Social sciences- Business/economics, (computational) finance- Healthcare, medicine, pharmaceuticals- (Computational) chemistry, biology (bioinformatics)- Sustainable mobility systems, intelligent transportation systems- National security
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