Causal discovery in manufacturing: A structured literature review
Industry 4.0 radically alters manufacturing organization and management, fostering
collection and analysis of increasing amounts of data. Advanced data analytics, such as …
collection and analysis of increasing amounts of data. Advanced data analytics, such as …
An overview of industrial alarm systems: Main causes for alarm overloading, research status, and open problems
Alarm systems play critically important roles for the safe and efficient operation of modern
industrial plants. However, most existing industrial alarm systems suffer from poor …
industrial plants. However, most existing industrial alarm systems suffer from poor …
A review of alarm root cause analysis in process industries: Common methods, recent research status and challenges
In modern industrial plants with a variety of interconnected devices and control loops, a fault
may propagate through the information and material flow pathways. Alarms are indicators of …
may propagate through the information and material flow pathways. Alarms are indicators of …
Comparative analysis of Granger causality and transfer entropy to present a decision flow for the application of oscillation diagnosis
Causality analysis techniques can be used for fault diagnosis in industrial processes.
Multiple causality analysis techniques have been shown to be effective for fault diagnosis …
Multiple causality analysis techniques have been shown to be effective for fault diagnosis …
Causality countermeasures for anomaly detection in cyber-physical systems
The problem of attack detection in cyberphysical systems is considered in this paper.
Transferentropy-based causality countermeasures are introduced for both sensor …
Transferentropy-based causality countermeasures are introduced for both sensor …
Simplified Granger causality map for data-driven root cause diagnosis of process disturbances
Root cause diagnosis is an important step in process monitoring, which aims to identify the
sources of process disturbances. The primary challenge is that process disturbances …
sources of process disturbances. The primary challenge is that process disturbances …
Detection and root cause analysis of multiple plant-wide oscillations using multivariate nonlinear chirp mode decomposition and multivariate granger causality
Plant-wide oscillation detection and root cause diagnosis are important for maintaining
control performance. Existing methods are mainly limited to detecting single and time …
control performance. Existing methods are mainly limited to detecting single and time …
Causality detection with matrix-based transfer entropy
Transfer entropy (TE) is a powerful tool for analyzing causality between time series and
complex systems. However, it faces two key challenges. First, TE is often used to quantify the …
complex systems. However, it faces two key challenges. First, TE is often used to quantify the …
A direct transfer entropy-based multiblock Bayesian network for root cause diagnosis of process faults
In chemical processes, Bayesian network (BN)-based approaches have been extensively
applied for process fault diagnosis. Generally, BN is learned using score and search …
applied for process fault diagnosis. Generally, BN is learned using score and search …
Data-driven root-cause fault diagnosis for multivariate non-linear processes
B Rashidi, DS Singh, Q Zhao - Control Engineering Practice, 2018 - Elsevier
In a majority of multivariate processes, propagating nature of malfunctions makes the fault
diagnosis a challenging task. This paper presents a novel data-driven strategy for real-time …
diagnosis a challenging task. This paper presents a novel data-driven strategy for real-time …