Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges

Y Xu, S Kohtz, J Boakye, P Gardoni, P Wang - Reliability Engineering & …, 2023 - Elsevier
The computerized simulations of physical and socio-economic systems have proliferated in
the past decade, at the same time, the capability to develop high-fidelity system predictive …

Industry 4.0 and digitalisation in healthcare

VV Popov, EV Kudryavtseva, N Kumar Katiyar… - Materials, 2022 - mdpi.com
Industry 4.0 in healthcare involves use of a wide range of modern technologies including
digitisation, artificial intelligence, user response data (ergonomics), human psychology, the …

[HTML][HTML] A review and perspective on hybrid modeling methodologies

AM Schweidtmann, D Zhang, M von Stosch - Digital Chemical Engineering, 2024 - Elsevier
The term hybrid modeling refers to the combination of parametric models (typically derived
from knowledge about the system) and nonparametric models (typically deduced from data) …

Deep neural network-based hybrid modeling and experimental validation for an industry-scale fermentation process: Identification of time-varying dependencies …

P Shah, MZ Sheriff, MSF Bangi, C Kravaris… - Chemical Engineering …, 2022 - Elsevier
Kinetic modeling of fermentation processes is difficult due to the use of micro-organisms that
follow complex reaction mechanisms. Kinetic models are usually not perfect owing to …

Perspectives on the integration between first-principles and data-driven modeling

W Bradley, J Kim, Z Kilwein, L Blakely… - Computers & Chemical …, 2022 - Elsevier
Efficiently embedding and/or integrating mechanistic information with data-driven models is
essential if it is desired to simultaneously take advantage of both engineering principles and …

Machine learning in process systems engineering: Challenges and opportunities

P Daoutidis, JH Lee, S Rangarajan, L Chiang… - Computers & Chemical …, 2024 - Elsevier
This “white paper” is a concise perspective of the potential of machine learning in the
process systems engineering (PSE) domain, based on a session during FIPSE 5, held in …

A review on the modernization of pharmaceutical development and manufacturing–Trends, perspectives, and the role of mathematical modeling

F Destro, M Barolo - International Journal of Pharmaceutics, 2022 - Elsevier
Recently, the pharmaceutical industry has been facing several challenges associated to the
use of outdated development and manufacturing technologies. The return on investment on …

Empirical investigation of extended TOE model on Corporate Environment Sustainability and dimensions of operating performance of SMEs: A high order PLS-ANN …

M Dadhich, KK Hiran - Journal of Cleaner Production, 2022 - Elsevier
Aims The goal of economic expansion, which ignores social welfare and environmental
restrictions, has been supplanted in the business environment. The paper investigates how …

Physics-informed neural networks for hybrid modeling of lab-scale batch fermentation for β-carotene production using Saccharomyces cerevisiae

MSF Bangi, K Kao, JSI Kwon - Chemical Engineering Research and Design, 2022 - Elsevier
Abstract β-Carotene has a positive impact on human health as a precursor of vitamin A.
Building a kinetic model for its production using Saccharomyces cerevisiae in a batch …

Bioprocess control: current progress and future perspectives

AS Rathore, S Mishra, S Nikita, P Priyanka - Life, 2021 - mdpi.com
Typical bioprocess comprises of different unit operations wherein a near optimal
environment is required for cells to grow, divide, and synthesize the desired product …