717
Views
9
CrossRef citations to date
0
Altmetric
Original Articles

The application of multivariate statistical process monitoring in non-industrial processes

, &
Pages 526-549 | Accepted 18 Aug 2016, Published online: 14 Sep 2016

Keep up to date with the latest research on this topic with citation updates for this article.

Read on this site (9)

Sotirios Bersimis, Athanasios Sachlas & Economou Polychronis. (2023) Public health monitoring using control charts based on convex hull. Research in Statistics 1:1.
Read now
S. Bersimis & A. Sachlas. (2022) Surveilling public health through statistical process monitoring: A literature review and a unified framework. Communications in Statistics: Case Studies, Data Analysis and Applications 8:3, pages 515-543.
Read now
Sotiris Bersimis, Subhabrata Chakraborti & Athanasios C. Rakitzis. (2022) Pattern detection in phase I monitoring using runs-based tests. Communications in Statistics - Simulation and Computation 0:0, pages 1-17.
Read now
Gideon Mensah Engmann & Dong Han. (2022) The optimized CUSUM and EWMA multi-charts for jointly detecting a range of mean and variance change. Journal of Applied Statistics 49:6, pages 1540-1558.
Read now
Gideon Mensah Engmann & Dong Han. (2022) Asymptotic optimized CUSUM and EWMA multi-charts for jointly detecting and diagnosing unknown change. Journal of Statistical Computation and Simulation 92:3, pages 524-543.
Read now
Jiayun Jin & Geert Loosveldt. (2022) Nonparametric multivariate control chart for numerical and categorical variables. Communications in Statistics - Simulation and Computation 0:0, pages 1-19.
Read now
Vasyl Golosnoy & Miriam Isabel Seifert. (2021) Monitoring mean changes in persistent multivariate time series. Statistics 55:3, pages 475-488.
Read now
Inez M. Zwetsloot, Tahir Mahmood & William H. Woodall. (2021) Multivariate time-between-events monitoring: An overview and some overlooked underlying complexities. Quality Engineering 33:1, pages 13-25.
Read now
Yiqi Liu, Yumin Liu & Uk Jung. (2020) Nonparametric multivariate control chart based on density-sensitive novelty weight for non-normal processes. Quality Technology & Quantitative Management 17:2, pages 203-215.
Read now

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.