Results 21 to 30 of about 21,463,749 (293)

Control Charts for Multivariate Nonlinear Time Series

Revstat Statistical Journal, 2015
In this paper control charts for the simultaneous monitoring of the means and the variances of multivariate nonlinear time series are introduced. The underlying target process is assumed to be a constant conditional correlation process (cf. [3]).
Robert Garthoff , Iryna Okhrin , Wolfgang Schmid   +2 more
doaj   +1 more source

Monitoring the mean with least-squares support vector data description

Gestão & Produção, 2021
: Multivariate control charts are essential tools in multivariate statistical process control (MSPC). “Shewhart-type” charts are control charts using rational subgroupings which are effective in the detection of large shifts.
Edgard M. Maboudou-Tchao
doaj   +1 more source

A branch and bound method for isolation of faulty variables through missing variable analysis [PDF]

, 2010
Fault detection and diagnosis is a critical approach to ensure safe and efficient operation of manufacturing and chemical processing plants. Although multivariate statistical process monitoring has received considerable attention, investigation into ...
Tao Chen, Pabara-Ebiere Odiowei, Vinay Kariwala, Kariwala, V, Kariwala, Vinay, Yi Cao, Odiowei, P. E., Chen, Tao, Odiowei, P-E, Chen, T, Cao, Y, Cao, Yi   +11 more
core   +1 more source

Principal alarms in multivariate statistical process control [PDF]

, 2006
This paper describes a methodology for the simulation of multivariate out of control situations using in-control data. The method is based on finding the independent factors of the variability of the process, and shifting these factors one by one.
González, Isabel, Sánchez, Ismael
core   +1 more source

Oversizing Thread Diagnosis in Tapping Operation

Metals, 2021
Automotive, railway and aerospace sectors require a high level of quality on the thread profiles in their manufacturing systems knowing that the tapping process is a complex manufacturing process and the last operation in a manufacturing cell. Therefore,
Alain Gil Del Val, Fernando Veiga, Mariluz Penalva, Miguel Arizmendi   +3 more
doaj   +1 more source

A FT-NIR Process Analytical Technology Approach for Milk Renneting Control

Foods, 2021
The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA).
Silvia Grassi, Lorenzo Strani, Cristina Alamprese, Nicolò Pricca, Ernestina Casiraghi, Giovanni Cabassi   +5 more
doaj   +1 more source

Validation Framework for Automated Aircraft Load Control Operations

Eng
This paper presents a validation framework for automated aircraft mass and balance operations, combining statistical process control with integrated risk scoring and addressing the critical gap between traditional centralised load control and emerging ...
Ivan Jakovljević, Olja Čokorilo, Ljubiša Vasov   +2 more
doaj   +1 more source

Probabilistic Multivariate Statistical Process Control via Kernel Parameter Uncertainty Propagation

IEEE Access
Kernel-based multivariate statistical process control (K-MSPC) extends classical latent-variable monitoring to nonlinear industrial processes, but its performance depends strongly on kernel parameters such as lengthscales and variance terms.
Zina-Sabrina Duma, Victoria Jorry, Ayesha Sarfraz, Maria Paola Di Crosta, Tuomas Sihvonen, Lassi Roininen, Satu-Pia Reinikainen   +6 more
doaj   +1 more source

Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate Variability

Sensors, 2020
A warning prior to seizure onset can help improve the quality of life for epilepsy patients. The feasibility of a wearable system for predicting epileptic seizures using anomaly detection based on machine learning is evaluated.
Toshitaka Yamakawa, Miho Miyajima, Koichi Fujiwara, Manabu Kano, Yoko Suzuki, Yutaka Watanabe, Satsuki Watanabe, Tohru Hoshida, Motoki Inaji, Taketoshi Maehara   +9 more
doaj   +1 more source

Monitoring and Interpretation of Process Variability Generated from the Integration of the Multivariate Cumulative Sum Control Chart and Artificial Intelligence

Applied Sciences
Variability in manufacturing processes must be properly monitored and controlled to avoid incurring quality problems; otherwise, the probability of manufacturing defective products increases, and, consequently, production costs rise.
Edgar Augusto Ruelas-Santoyo, Vicente Figueroa-Fernández, Moisés Tapia-Esquivias, Yaquelin Verenice Pantoja-Pacheco, Edgar Bravo-Santibáñez, Javier Cruz-Salgado   +5 more
doaj   +1 more source