33 citations · 88 across the 14 of their papers we have counts for
14 papers
Monitoring Covariance in Multichannel Profiles via Functional Graphical Models
Christian Capezza, Davide Forcina, Antonio Lepore +1
Most statistical process monitoring methods for multichannel profiles focus solely on the mean and are almost ineffective when changes involve the covariance structure. Although it…
An Adaptive Multivariate Functional Control Chart
Fabio Centofanti, Antonio Lepore, Biagio Palumbo
New data acquisition technologies allow one to gather huge amounts of data that are best represented as functional data. In this setting, profile monitoring assesses the stability…
Stream-Based Active Learning for Process Monitoring
Christian Capezza, Antonio Lepore, Kamran Paynabar
Statistical process monitoring (SPM) methods are essential tools in quality management to check the stability of industrial processes, i.e., to dynamically classify the process sta…
Functional Mixture Regression Control Chart
Christian Capezza, Fabio Centofanti, Davide Forcina +2
Industrial applications often exhibit multiple in-control patterns due to varying operating conditions, which makes a single functional linear model (FLM) inadequate to capture the…
An Adaptive Multivariate Functional EWMA Control Chart
Christian Capezza, Giovanna Capizzi, Fabio Centofanti +2
In many modern industrial scenarios, the measurements of the quality characteristics of interest are often required to be represented as functional data or profiles. This motivates…
Functional Neural Network Control Chart
Murat Kulahci, Antonio Lepore, Biagio Palumbo +1
In many Industry 4.0 data analytics applications, quality characteristic data acquired from manufacturing processes are better modeled as functions, often referred to as profiles.…
funcharts: Control charts for multivariate functional data in R
Christian Capezza, Fabio Centofanti, Antonio Lepore +3
Modern statistical process monitoring (SPM) applications focus on profile monitoring, i.e., the monitoring of process quality characteristics that can be modeled as profiles, also…
Robust Multivariate Functional Control Chart
Christian Capezza, Fabio Centofanti, Antonio Lepore +1
In modern Industry 4.0 applications, a huge amount of data is acquired during manufacturing processes that are often contaminated with anomalous observations in the form of both ca…
Real-time Monitoring of Functional Data
Fabio Centofanti, Antonio Lepore, Murat Kulahci +1
With the rise of Industry 4.0, huge amounts of data are now generated that are apt to be modelled as functional data. In this setting, standard profile monitoring methods aim to as…
Sparse and Smooth Functional Data Clustering
Fabio Centofanti, Antonio Lepore, Biagio Palumbo
A new model-based procedure is developed for sparse clustering of functional data that aims to classify a sample of curves into homogeneous groups while jointly detecting the most…
Adaptive Smoothing Spline Estimator for the Function-on-Function Linear Regression Model
Fabio Centofanti, Antonio Lepore, Alessandra Menafoglio +2
In this paper, we propose an adaptive smoothing spline (AdaSS) estimator for the function-on-function linear regression model where each value of the response, at any domain point,…
Functional clustering methods for resistance spot welding process data in the automotive industry
Christian Capezza, Fabio Centofanti, Antonio Lepore +1
Quality assessment of resistance spot welding (RSW) joints of metal sheets in the automotive industry is typically based on costly and lengthy off-line tests that are unfeasible on…
Smooth Lasso Estimator for the Function-on-Function Linear Regression Model
Fabio Centofanti, Matteo Fontana, Antonio Lepore +1
A new estimator, named S-LASSO, is proposed for the coefficient function of the Function-on-Function linear regression model. The S-LASSO estimator is shown to be able to increase…
Plotting positions close to the exact unbiased solution: application to the Pozzuoli's bradeysism earthquake data
Pasquale Erto, Antonio Lepore
Graphical techniques are recommended for critical applications in order to share information with non-statisticians, since they allow for a visual analysis and helpful understandin…