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Journal of Quality Technology
A Quarterly Journal of Methods, Applications and Related Topics
Volume 51, 2019 - Issue 3
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Articles

An adaptive thresholding-based process variability monitoring

Galal M. AbdellaDepartment of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar; View further author information
,
Jinho KimDepartment of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar; View further author information
,
Sangahn KimDepartment of Business Analytics and Actuarial Science, Siena College, Loudonville, New York; View further author information
,
Khalifa N. Al-KhalifaDepartment of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar; View further author information
,
Myong K. (MK) JeongDepartment of Industrial and Systems Engineering, Rutgers University, Piscataway, New JerseyCorrespondence[email protected]
View further author information
,
Abdel Magid HamoudaDepartment of Mechanical and Industrial Engineering, Qatar University, Doha, Qatar; View further author information
&
Elsayed A. ElsayedDepartment of Industrial and Systems Engineering, Rutgers University, Piscataway, New JerseyView further author information
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Pages 242-256 | Published online: 11 Apr 2019

Citations (12)

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Read on this site (3)

Mohsen Ebadi, Shojaeddin Chenouri, Dennis K. J. Lin & Stefan H. Steiner. (2022) Statistical monitoring of the covariance matrix in multivariate processes: A literature review. Journal of Quality Technology 54:3, pages 269-289.
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Olusola T. Omolofe, Nurudeen A. Adegoke, Olatunde A. Adeoti, Olusoga A. Fasoranbaku & Saddam Akber Abbasi. (2022) Multivariate control charts for monitoring process mean vector of individual observations under regularized covariance estimation. Quality Technology & Quantitative Management 19:3, pages 277-298.
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Hongying Jing, Jian Li & Kaizong Bai. (2022) Directional monitoring and diagnosis for covariance matrices. Journal of Applied Statistics 49:6, pages 1449-1464.
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Articles from other publishers (9)

Zahra Jalilibal, Mohammad Hassan Ahmadi Karavigh, Mohammad Reza Maleki & Amirhossein Amiri. (2024) Control charting methods for monitoring high dimensional data streams: A conceptual classification scheme. Computers & Industrial Engineering 191, pages 110141.
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Masoud Jafari, Mohammad Reza Maleki & Ali Salmasnia. (2022) A high-dimensional control chart for monitoring process variability under gauge imprecision effect. Production Engineering 17:3-4, pages 547-564.
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Ali Salmasnia, Mohammad Reza Maleki & Mohadeseh Mirzaei. (2023) Double Sampling Adaptive Thresholding LASSO Variability Chart for Phase II Monitoring of High-Dimensional Data Streams. Journal of Industrial Integration and Management, pages 1-22.
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李琳 高. (2023) An Adaptive Lasso Thresholding-Based Covariance Matrix EWMA Control Chart. Statistics and Application 12:02, pages 476-783.
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Nurudeen A. Adegoke, Jimoh Olawale Ajadi, Amitava Mukherjee & Saddam Akber Abbasi. (2022) Nonparametric multivariate covariance chart for monitoring individual observations. Computers & Industrial Engineering 167, pages 108025.
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Nuri Cihat Onat, Galal M. Abdella, Murat Kucukvar, Adeeb A. Kutty, Munera Al‐Nuaimi, Gürkan Kumbaroğlu & Melih Bulu. (2021) How eco‐efficient are electric vehicles across Europe? A regionalized life cycle assessment‐based eco‐efficiency analysis. Sustainable Development 29:5, pages 941-956.
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Nurudeen A. Adegoke, Muhammad Riaz, Khadijat Oladayo Ganiyu & Saddam Akber Abbasi. (2021) One-Sided and Two One-Sided Multivariate Homogeneously Weighted Moving Charts for Monitoring Process Mean. IEEE Access 9, pages 80388-80404.
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Adeeb A Kutty, Galal M Abdella & Murat Kucukvar. (2020) Ridge Penalization-based weighting approach for Eco-Efficiency assessment: The case in the food industry in the United States. IOP Conference Series: Materials Science and Engineering 947:1, pages 012003.
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Galal M. Abdella, Mohammad Reza Maleki, Sangahn Kim, Khalifa N. Al-Khalifa & Abdel Magid S. Hamouda. (2020) Phase-I monitoring of high-dimensional covariance matrix using an adaptive thresholding LASSO rule. Computers & Industrial Engineering 144, pages 106465.
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