Causal network inference and functional decomposition for decentralized statistical process monitoring: Detection and diagnosis

Root cause diagnosis in multivariate time series based on modified temporal convolution and multi-head self-attention

(2022) Yujie Zhou et al.   JOURNAL OF PROCESS CONTROL

Multiscale Partial Symbolic Transfer Entropy for Time-Delay Root Cause Diagnosis in Nonstationary Industrial Processes

(2022) Shuyu Duan et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

An Efficient Algorithm for Community Detection in Complex Weighted Networks

(2021) Leila Samandari Masooleh et al.   AICHE JOURNAL

Hierarchical hybrid distributed PCA for plant-wide monitoring of chemical processes

(2021) Yue Cao et al.   CONTROL ENGINEERING PRACTICE

Single Model-Based Analysis of Relative Causal Changes for Root-Cause Diagnosis in Complex Industrial Processes

(2021) Chang Tian et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Process monitoring using causal graphical models, with application to clogging detection in steel continuous casting

(2021) Shu Yang et al.   JOURNAL OF PROCESS CONTROL

Data preprocessing for multiblock modelling – A systematization with new methods

(2020) Maria P. Campos et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Multiscale and Multi-Granularity Process Analytics: A Review

(2019) Marco Reis   Processes

Incorporation of process-specific structure in statistical process monitoring: A review

(2019) Marco S. Reis et al.   JOURNAL OF QUALITY TECHNOLOGY

Data-driven methods for batch data analysis – A critical overview and mapping on the complexity scale

(2019) Ricardo Rendall et al.   COMPUTERS & CHEMICAL ENGINEERING

Plant-wide process monitoring by using weighted copula–correlation based multiblock principal component analysis approach and online-horizon Bayesian method

(2019) Ying Tian et al.   ISA TRANSACTIONS

Modified non-Gaussian multivariate statistical process monitoring based on the Gaussian distribution transformation

(2019) Wenyou Du et al.   JOURNAL OF PROCESS CONTROL

A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part II—Assessing Detection Speed

(2018) Tiago J. Rato et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Community detection in networks: A multidisciplinary review

(2018) Muhammad Aqib Javed et al.   JOURNAL OF NETWORK AND COMPUTER APPLICATIONS

Connectivity inference from neural recording data: Challenges, mathematical bases and research directions

(2018) Ildefons Magrans de Abril et al.   NEURAL NETWORKS

Industrial Process Monitoring in the Big Data/Industry 4.0 Era: from Detection, to Diagnosis, to Prognosis

(2017) Marco Reis et al.   Processes

Causation-Based T2 Decomposition for Multivariate Process Monitoring and Diagnosis

(2017) Jing Li et al.   JOURNAL OF QUALITY TECHNOLOGY

Block adaptive kernel principal component analysis for nonlinear process monitoring

(2016) Lei Xie et al.   AICHE JOURNAL

A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part I—Assessing Detection Strength

(2016) Tiago J. Rato et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

On-line process monitoring using local measures of association. Part II: Design issues and fault diagnosis

(2015) Tiago J. Rato et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

On-line process monitoring using local measures of association: Part I — Detection performance

(2015) Tiago J. Rato et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Canonical variate analysis-based monitoring of process correlation structure using causal feature representation

(2015) Benben Jiang et al.   JOURNAL OF PROCESS CONTROL

Diagnosis of multiple and unknown faults using the causal map and multivariate statistics

(2015) Leo H. Chiang et al.   JOURNAL OF PROCESS CONTROL

Non-causal data-driven monitoring of the process correlation structure: A comparison study with new methods

(2014) Tiago J. Rato et al.   COMPUTERS & CHEMICAL ENGINEERING

Sensitivity enhancing transformations for monitoring the process correlation structure

(2014) Tiago J. Rato et al.   JOURNAL OF PROCESS CONTROL

Analysis of smearing-out in contribution plot based fault isolation for Statistical Process Control

(2013) Pieter Van den Kerkhof et al.   CHEMICAL ENGINEERING SCIENCE

Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR)

(2013) Tiago J. Rato et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Advantage of Using Decorrelated Residuals in Dynamic Principal Component Analysis for Monitoring Large-Scale Systems

(2013) Tiago J. Rato et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Review of Recent Research on Data-Based Process Monitoring

(2013) Zhiqiang Ge et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Causal statistical inference in high dimensions

(2013) Peter Bühlmann   MATHEMATICAL METHODS OF OPERATIONS RESEARCH

Decentralized Fault Diagnosis of Large-Scale Processes Using Multiblock Kernel Partial Least Squares

(2009) Yingwei Zhang et al.   IEEE Transactions on Industrial Informatics

Multiscale statistical process control using wavelet packets

(2008) Marco S. Reis et al.   AICHE JOURNAL

Statistical-based monitoring of multivariate non-Gaussian systems

(2008) Xueqin Liu et al.   AICHE JOURNAL

Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks

(2008) Antonio Reverter et al.   BIOINFORMATICS

A practical method for identifying the propagation path of plant-wide disturbances

(2008) Margret Bauer et al.   JOURNAL OF PROCESS CONTROL

Hierarchical structure and the prediction of missing links in networks

(2008) Aaron Clauset et al.   NATURE

Multiway kernel independent component analysis based on feature samples for batch process monitoring

(2008) Xuemin Tian et al.   NEUROCOMPUTING