Digital twins in pharmaceutical and biopharmaceutical manufacturing: a literature review
The development and application of emerging technologies of Industry 4.0 enable the
realization of digital twins (DT), which facilitates the transformation of the manufacturing …
realization of digital twins (DT), which facilitates the transformation of the manufacturing …
Modelling for digital twins—potential role of surrogate models
The application of white box models in digital twins is often hindered by missing knowledge,
uncertain information and computational difficulties. Our aim was to overview the difficulties …
uncertain information and computational difficulties. Our aim was to overview the difficulties …
A novel long short-term memory artificial neural network (LSTM)-based soft-sensor to monitor and forecast wastewater treatment performance
Commercial instrumentation for measurement of various wastewater treatment processes
parameters is costly and time-consuming in wastewater treatment plants (WWTPs). Long …
parameters is costly and time-consuming in wastewater treatment plants (WWTPs). Long …
Linking models and experiments
This position paper gives an overview of the discussion that took place at FIPSE 2 at
Aldemar Resort, east of Heraklion, Crete, in June 21–23, 2014. This is the second …
Aldemar Resort, east of Heraklion, Crete, in June 21–23, 2014. This is the second …
Semi-supervised adaptive PLS soft-sensor with PCA-based drift correction method for online valuation of NOx emission in industrial water-tube boiler
The use of soft sensors for the prediction of Nitric Oxides (NOx) emissions to meet quality
regulations has become increasingly attractive from the economic point of view. However …
regulations has become increasingly attractive from the economic point of view. However …
[HTML][HTML] Machine learning for industrial sensing and control: A survey and practical perspective
With the rise of deep learning, there has been renewed interest within the process industries
to utilize data on large-scale nonlinear sensing and control problems. We identify key …
to utilize data on large-scale nonlinear sensing and control problems. We identify key …
Design and applications of soft sensors in polymer processing: A review
C Abeykoon - IEEE Sensors Journal, 2018 - ieeexplore.ieee.org
In manufacturing industry, process monitoring is a key to observe the product quality,
operational health, safety, and also for achieving good/satisfactory process control …
operational health, safety, and also for achieving good/satisfactory process control …
Semi-supervised online soft sensor maintenance experiences in the chemical industry
With the increasing availability of spectral, vibrational, thermal and other sensors, the
challenge of “Big Data” in chemical processing industry is not only to analyze the data …
challenge of “Big Data” in chemical processing industry is not only to analyze the data …
A hybrid modeling approach for catalyst monitoring and lifetime prediction
L Bui, M Joswiak, I Castillo, A Phillips, J Yang… - ACS Engineering …, 2021 - ACS Publications
In this work, we present a hybrid fundamental-empirical model to monitor and predict the
catalyst lifetime of an operating industrial reactor. The hybrid model combines a fundamental …
catalyst lifetime of an operating industrial reactor. The hybrid model combines a fundamental …
Dual learning-based online ensemble regression approach for adaptive soft sensor modeling of nonlinear time-varying processes
H Jin, X Chen, L Wang, K Yang, L Wu - Chemometrics and Intelligent …, 2016 - Elsevier
Soft sensors have been widely used to estimate difficult-to-measure variables in the process
industry. However, the nonlinear nature and time-varying behavior of many processes pose …
industry. However, the nonlinear nature and time-varying behavior of many processes pose …