Tiago J. Rato

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

Tiago J. Rato, Marco S. Reis · Chemometrics and Intelligent Laboratory Systems · 2013 · 159 citations

Engineering, Computer Engineering, Industrial Engineering +14

A systematic comparison of PCA‐based Statistical Process Monitoring methods for high‐dimensional, time‐dependent Processes

Tiago J. Rato, Marco S. Reis, Éric Schmitt et al. · AIChE Journal · 2015 · 112 citations · Full text

Computing, Chemical Engineering, Process Control +14

Defining the structure of DPCA models and its impact on process monitoring and prediction activities

Tiago J. Rato, Marco S. Reis · Chemometrics and Intelligent Laboratory Systems · 2013 · 79 citations

Business, Computer Science, Systems Engineering +16

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

Tiago J. Rato, Marco S. Reis · Industrial & Engineering Chemistry Research · 2013 · 62 citations

Computing, Systems Engineering, Fault-tolerant Computing +11

Translation-Invariant Multiscale Energy-Based PCA for Monitoring Batch Processes in Semiconductor Manufacturing

Tiago J. Rato, Jakey Blue, Jacques Pinaton et al. · IEEE Transactions on Automation Science and Engineering · 2016 · 55 citations

Engineering, Industrial Engineering, Manufacturing Engineering +17