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Statistical Process Monitoring from Industry 2.0 to Industry 4.0: Insights into Research and Practice
被引:6
|作者:
Colosimo, Bianca M.
[1
]
Jones-Farmer, L. Allison
[2
]
Megahed, Fadel M.
[2
]
Paynabar, Kamran
[3
]
Ranjan, Chitta
[4
]
Woodall, William H.
[5
]
机构:
[1] Politecn Milan, Mech Engn, Milan, Italy
[2] Miami Univ, Informat Syst & Analyt, Oxford, OH 45056 USA
[3] Georgia Inst Technol, Ind & Syst Engn, Atlanta, GA USA
[4] Amazon, Bangalore, India
[5] Virginia Polytech Inst & State Univ, Stat, Blacksburg, VA USA
关键词:
Applications and case studies;
Quality control/process improvement;
Statistical process control (SPC);
CHARTS RECENT DEVELOPMENTS;
BIG DATA;
DATA SCIENCE;
ARTIFICIAL-INTELLIGENCE;
MULTIVARIATE;
QUALITY;
SYSTEMS;
CHALLENGES;
MANAGEMENT;
ANALYTICS;
D O I:
10.1080/00401706.2024.2327341
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
Industry 4.0 has emerged as an important era for process monitoring and improvement. Our expository paper provides a historical perspective on research and practice of statistical process monitoring (SPM) from the 1920s to the present to bring a high-level view of current practice and research directions. We focus on the Industry 4.0 era, which began around 2011 with the introduction of cyber-physical systems and the growth of the Internet of Things. These technological changes have brought tremendous challenges and opportunities to SPM that can only be met with new paradigms for the problems we aim to solve and the approaches we use to evaluate SPM methodology. We provide our perspective on these challenges, primarily focusing on industrial applications. We give recommendations on the evaluation and comparison of monitoring methods to improve the usefulness of research in this area.
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页码:507 / 530
页数:24
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