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   Articles with "process data" as a keyword



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Soft sensor based on 2D‐fluorescence and process data enabling real‐time estimation of biomass in Escherichia coli cultivations

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recommendations! Published in 2020 at "Engineering in Life Sciences"

DOI: 10.1002/elsc.201900076

Abstract: In bioprocesses, specific process responses such as the biomass cannot typically be measured directly on‐line, since analytical sampling is associated with unavoidable time delays. Accessing those responses in real‐time is essential for Quality by Design… read more here.

Keywords: soft sensor; real time; biomass; process data ... See more keywords

End‐Point Prediction of Converter Steelmaking Based on Main Process Data

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recommendations! Published in 2024 at "steel research international"

DOI: 10.1002/srin.202400151

Abstract: In this article, main process data, notably time–series data such as lance position patterns, are analyzed during converter steelmaking, and methodologies in data processing and transforming are proposed. In this study, utilizing both the transformed… read more here.

Keywords: converter steelmaking; end point; point; process data ... See more keywords
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EMD-based online Filtering of Process Data

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recommendations! Published in 2017 at "Control Engineering Practice"

DOI: 10.1016/j.conengprac.2017.03.008

Abstract: Abstract In chemical industries, measurements corrupted by noise or outliers may affect operators’ recognition of the current situation and lead them to make inappropriate control decisions. Data quality is a critical factor for process monitoring… read more here.

Keywords: filtering process; online filtering; process data; emd based ... See more keywords
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Analysis and Modelling of an Industrial Pressure Filtration using Process Data

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recommendations! Published in 2017 at "IFAC-PapersOnLine"

DOI: 10.1016/j.ifacol.2017.08.2152

Abstract: Abstract In order to understand a series of pressure leaf filters located in the downstream line of a bio-based production site, historical process data have been analysed. In general, changing raw materials induce variability into… read more here.

Keywords: filtration; process data; process; analysis modelling ... See more keywords

Quality Prediction of Reamed Bores Based on Process Data and Machine Learning Algorithm: A Contribution to a More Sustainable Manufacturing

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recommendations! Published in 2020 at "Procedia Manufacturing"

DOI: 10.1016/j.promfg.2020.02.180

Abstract: Abstract During the manufacturing of machined workpieces with very narrow tolerances in serial production, slight quality deviations can cause high scrap rates and a waste of resources. In-process quality surveillance makes it possible to take… read more here.

Keywords: machine; quality; reamed bores; process data ... See more keywords

Using Process Data to Improve Classification Accuracy of Cognitive Diagnosis Model.

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recommendations! Published in 2023 at "Multivariate behavioral research"

DOI: 10.1080/00273171.2022.2157788

Abstract: With the advance of computer-based assessments, many process data, such as response times (RTs), action sequences, Eye-tracking data, the log data for collaborative problem-solving (CPS) and mouse click/drag becomes readily available. Findings from previous studies… read more here.

Keywords: model; classification accuracy; process; process data ... See more keywords
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A Big Data and Learning Analytics Approach to Process-Level Feedback in Cognitive Simulations

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recommendations! Published in 2017 at "Academic Medicine"

DOI: 10.1097/acm.0000000000001234

Abstract: Collecting and analyzing large amounts of process data for the purposes of education can be considered a big data/learning analytics (BD/LA) approach to improving learning. However, in the education of health care professionals, the application… read more here.

Keywords: big data; data learning; learning analytics; process data ... See more keywords

Dynamic Probabilistic Latent Variable Model for Process Data Modeling and Regression Application

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recommendations! Published in 2019 at "IEEE Transactions on Control Systems Technology"

DOI: 10.1109/tcst.2017.2767022

Abstract: Dynamic and uncertainty are two main features of the industrial process data which should be paid attention when carrying out process data modeling and analytics. In this paper, the dynamical and uncertain data characteristics are… read more here.

Keywords: variable model; latent variable; process data; probabilistic latent ... See more keywords

Probabilistic Sequential Network for Deep Learning of Complex Process Data and Soft Sensor Application

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recommendations! Published in 2019 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2018.2869899

Abstract: Soft sensing of quality/key variables is critical to the control and optimization of industrial processes. One of the main drawbacks of data-driven soft sensors is to deal with the dynamic and nonlinear characteristics of process… read more here.

Keywords: soft sensor; deep learning; network; process data ... See more keywords

Vertices Packaging-Based Interval Independent Component Analysis (VP-I2CA) for Fault Detection With Process Uncertainty

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recommendations! Published in 2024 at "IEEE Transactions on Industrial Informatics"

DOI: 10.1109/tii.2023.3271737

Abstract: The fault detection capability of traditional data-driven process monitoring methods is highly dependent on the quality of process data. However, affected by measurement noise, harsh operation scenarios and other factors, the process data are inevitably… read more here.

Keywords: process; fault detection; process data; vertices packaging ... See more keywords

Deep Nonlinear Dynamic Feature Extraction for Quality Prediction Based on Spatiotemporal Neighborhood Preserving SAE

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recommendations! Published in 2021 at "IEEE Transactions on Instrumentation and Measurement"

DOI: 10.1109/tim.2021.3122187

Abstract: Complex industrial process data often exhibit nonlinear static and dynamic characteristics. Traditional deep learning methods such as stacked autoencoder (SAE) have excellent nonlinear static feature learning capabilities, but they ignore the dynamic correlation existing in… read more here.

Keywords: feature; process data; process; spatiotemporal neighborhood ... See more keywords