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Statistical process monitoring based on dissimilarity of process data
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Statistical process monitoring: basics and beyond
Journal of Chemometrics, 2003AbstractThis paper provides an overview and analysis of statistical process monitoring methods for fault detection, identification and reconstruction. Several fault detection indices in the literature are analyzed and unified. Fault reconstruction for both sensor and process faults is presented which extends the traditional missing value replacement ...
S. Qin
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Kernel-Based Statistical Process Monitoring and Fault Detection in the Presence of Missing Data
IEEE Transactions on Industrial Informatics, 2022Missing data widely exist in industrial processes and lead to difficulties in modeling, monitoring, fault diagnosis, and control. In this article, we propose a nonlinear method to handle the missing data problem in the offline modeling stage or/and the ...
Ieee Jicong Fan Member +2 more
semanticscholar +1 more source
Statistical Process Monitoring Based on Collaboration Preserving Embedding
IEEE Transactions on Instrumentation and Measurement, 2022The applications of dimensionality reduction method in statistical process monitoring have been widely researched in recent years. Considering the incompleteness and one-sidedness of the most existing methods on preserving the timing dynamic ...
Ruixiang Deng +3 more
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Run rules schemes for statistical process monitoring: a literature review
Quality Technology & Quantitative Management, 2022Different control charts are developed for monitoring various types of quality characteristics in the area of Statistical Process Monitoring (SPM). Moreover, new techniques are proposed to improve the performances of the suggested control charts.
Z. Jalilibal +3 more
semanticscholar +1 more source
Multivariate statistical process monitoring based on principal discriminative component analysis
Journal of the Franklin Institute, 2021A novel analytical algorithm called Principal Discriminative Component Analysis (PDCA) is proposed to implement just-in-time feature extraction, so that the deviation between the online monitored data and the normal operating dataset can be timely ...
Shanzhi Li, Yang Chen, Chudong Tong
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The role of the normal distribution in statistical process monitoring
, 2021We discuss issues related to the use of the normality assumption in statistical process monitoring with continuous data. Our illustrations involve the Shewhart X-chart.
M. Khakifirooz +2 more
semanticscholar +1 more source