Comprehensive analysis of change-point dynamics detection in time series data: A review

M Gupta, R Wadhvani, A Rasool - Expert Systems with Applications, 2024 - Elsevier
In the ever-evolving field of time series analysis, detecting changes in patterns and
dynamics is paramount for accurate forecasting and meaningful insights. This article …

Data-driven techniques for fault detection in anaerobic digestion process

P Kazemi, C Bengoa, JP Steyer, J Giralt - Process Safety and …, 2021 - Elsevier
Anaerobic digestion (AD) is an appropriate process for bio-energy (biogas) production from
waste and wastewater receiving a high level of attention at both academic and industrial …

[PDF][PDF] Intrusion detection system using multivariate control chart Hotelling's T2 based on PCA

M Ahsan, M Mashuri, H Kuswanto… - Int. J. Adv. Sci. Eng. Inf …, 2018 - researchgate.net
Statistical Process Control (SPC) has been widely used in industry and services. The SPC
can be applied not only to monitor manufacture processes but also can be applied to the …

[HTML][HTML] Process monitoring using kernel PCA and kernel density estimation-based SSGLR method for nonlinear fault detection

F Shahzad, Z Huang, WH Memon - Applied Sciences, 2022 - mdpi.com
Fault monitoring is often employed for the secure functioning of industrial systems. To
assess performance and enhance product quality, statistical process control (SPC) charts …

One-sided and two one-sided MEWMA charts for monitoring process mean

A Haq - Journal of Statistical Computation and Simulation, 2020 - Taylor & Francis
This study focuses on the development of new one-sided and two one-sided MEWMA charts
for monitoring the mean of a multivariate normal process. The one-sided MEWMA chart …

An integrated Markov chain model for the economic-statistical design of adaptive multivariate control charts and maintenance planning

J Taji, H Farughi, H Rasay - European Journal of Industrial …, 2023 - inderscienceonline.com
In this paper, the mean of a process with several quality characteristics is monitored using a
multivariate control chart which is a variable parameter (Vp) chi-square control chart with two …

Residual-based maximum MCUSUM control chart for joint monitoring the mean and variability of multivariate autocorrelated processes

H Khusna, M Mashuri, Suhartono… - Production & …, 2019 - Taylor & Francis
Maximum multivariate cumulative sum (Max-MCUSUM) is one of the single control charts
proposed for joint monitoring the mean and variability of independent observation. Since …

Tr(R2) control charts based on kernel density estimation for monitoring multivariate variability process

M Mashuri, H Haryono, DF Aksioma… - Cogent …, 2019 - Taylor & Francis
The multivariate control charts are not only used to monitor the mean vector but also can be
used to monitor the covariance matrix. The multivariate variability charts are used to …

Data-driven fault detection methods for detecting small-magnitude faults in anaerobic digestion process

P Kazemi, J Giralt, C Bengoa… - Water Science and …, 2020 - iwaponline.com
Early detection of small-magnitude faults in anaerobic digestion (AD) processes is a
mandatory step for preventing serious consequence in the future. Since volatile fatty acids …

The effectiveness of Max‐half‐Mchart over Max‐Mchart in simultaneously monitoring process mean and variability of individual observations

R Kruba, M Mashuri, DD Prastyo - Quality and Reliability …, 2021 - Wiley Online Library
Control charts are widely used in industrial environments for the simultaneous or separate
monitoring of the process mean and process variability. The Max‐Mchart is a multivariate …