Search Results - "Rato, Tiago J"

Fault detection in the Tennessee Eastman benchmark process using dynamic principal components analysis based on decorrelated residuals (DPCA-DR) by Rato, Tiago J., Reis, Marco S.

“…Current multivariate control charts for monitoring large scale industrial processes are typically based on latent variable models, such as principal component…”
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Advantage of Using Decorrelated Residuals in Dynamic Principal Component Analysis for Monitoring Large-Scale Systems by Rato, Tiago J, Reis, Marco S

“…A new methodology is proposed for monitoring multi- and megavariate systems whose variables present significant levels of autocorrelation. The new monitoring…”
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Building Optimal Multiresolution Soft Sensors for Continuous Processes by Rato, Tiago J, Reis, Marco S

“…Data-driven models used in soft sensor applications are expected to capture the dominant relationships between the different process variables and the outputs,…”
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SS-DAC: A systematic framework for selecting the best modeling approach and pre-processing for spectroscopic data by Rato, Tiago J., Reis, Marco S.

“…Selecting the best combination of pre-processing and modeling methodologies is a critical activity while building soft sensors from spectroscopic Process…”
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Multiresolution Soft Sensors: A New Class of Model Structures for Handling Multiresolution Data by Rato, Tiago J, Reis, Marco S

“…The key quality features of industrial processes are typically obtained offline with a considerable delay and by resort to expensive equipment. To avoid this…”
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Markovian and Non-Markovian sensitivity enhancing transformations for process monitoring by Rato, Tiago J., Reis, Marco S.

“…•Process diagnosis requires causal information to be successful completed.•Current process monitoring methods are based on acausal models.•We propose a plug-in…”
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Optimal fusion of industrial data streams with different granularities by Rato, Tiago J., Reis, Marco S.

“…In the Industry 4.0 era, it is a common situation that measurements are available with different resolutions (or granularities). Multiresolution (or…”
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Optimal selection of time resolution for batch data analysis. Part I: Predictive modeling by Rato, Tiago J., Reis, Marco S.

“…Soft sensors based on multiway partial least squares (MW‐PLS) are often used to estimate, in useful time, the end quality of batch processes, due to their…”
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Design of Experiments: A comparison study from the non‐expert user's perspective by Santos, Catarina P., Rato, Tiago J., Reis, Marco S.

“…In a digital era where terabytes of structured and unstructured records are created and stored every minute, the importance of collecting small amounts of high…”
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A systematic PAT Soft Sensor screening and development methodology applied to the prediction of free fatty acids in industrial biodiesel production by Rato, Tiago J., Neves, Diogo M.G., Antunes, Anabela, Reis, Marco S.

“…A systematic approach for advanced soft sensor development was applied to predict free fatty acid (FFA) content from NIR spectra under real plant conditions,…”
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Sensitivity enhancing transformations for monitoring the process correlation structure by Rato, Tiago J., Reis, Marco S.

“…•Data pre-processing transformations improve the detection of structural changes.•Higher detections are obtained when pre-processing is based on process…”
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A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part IIAssessing Detection Speed by Rato, Tiago J, Rendall, Ricardo, Gomes, Veronique, Saraiva, Pedro M, Reis, Marco S

“…Since the first batch process monitoring approaches were published in the literature approximately 20 years ago, a significant number of extensions and new…”
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Multiscale and megavariate monitoring of the process networked structure: M2NET by Rato, Tiago J., Reis, Marco S.

“…We present a process monitoring scheme aimed at detecting changes in the networked structure of process data that is able to handle, simultaneously, three…”
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Non-causal data-driven monitoring of the process correlation structure: A comparison study with new methods by Rato, Tiago J., Reis, Marco S.

“…•Partial correlations (PC) detect subtle changes in correlation structure.•For the first time PC information was used in process monitoring.•Sensitivity…”
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A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part IAssessing Detection Strength by Rato, Tiago J, Rendall, Ricardo, Gomes, Veronique, Chin, Swee-Teng, Chiang, Leo H, Saraiva, Pedro M, Reis, Marco S

“…A significant number of batch process monitoring methods have been proposed since the first groundbreaking approaches were published in the literature, two…”
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An Advanced Data-Centric Multi-Granularity Platform for Industrial Data Analysis by Reis, Marco S., Rato, Tiago J.

“…Data collected in industrial processes are often high-dimensional, with dynamic and multi-granular characteristics that need to be properly accounted for in…”
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Improved Fault Diagnosis in Online Process Monitoring of Complex Networked Processes: a Data-Driven Approach by Rato, Tiago J., Reis, Marco S.

“…Many of the fault detection and diagnosis frameworks currently used in complex industrial processes rely on the application of data-driven models. Among these…”
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Sensitivity Enhancing Transformations for Large-Scale Process Monitoring by Rato, Tiago J., Reis, Marco S.

“…A new pre-processing methodology is proposed for improving the detection capability to changes in process structure. It is named sensitivity enhancing…”
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Statistical monitoring of control loops performance: an improved historical-data benchmark index by Rato, Tiago J., Reis, Marco S.

“…Control systems are key elements of virtually all industrial processes, whose performance directly impacts aspects as important as: product quality and…”
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A new data driven index for control performance monitoring by Rato, Tiago J., Reis, Marco S.

“…In this paper we address the problem of monitoring the performance of automatic control loops using data collected from the process. This topic has been…”
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