A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines

KTP Nguyen, K Medjaher, DT Tran - Artificial Intelligence Review, 2023 - Springer
The past decade has witnessed the adoption of artificial intelligence (AI) in various
applications. It is of no exception in the area of prognostics and health management (PHM) …

Artificial intelligence for control and optimization of boilers' performance and emissions: A review

MA Nemitallah, MA Nabhan, M Alowaifeer… - Journal of Cleaner …, 2023 - Elsevier
Burning fossil fuels is a major concern for global warming control. In Saudi Arabia, steam
power plants that relay on boilers to produce the steam accounted for around 50% of the …

[HTML][HTML] Artificial intelligence (AI) or intelligence augmentation (IA): what is the future?

H Hassani, ES Silva, S Unger, M TajMazinani… - Ai, 2020 - mdpi.com
Artificial intelligence (AI) is a rapidly growing technological phenomenon that all industries
wish to exploit to benefit from efficiency gains and cost reductions. At the macrolevel, AI …

Engineering applications of artificial intelligence: A bibliometric analysis of 30 years (1988–2018)

AK Shukla, M Janmaijaya, A Abraham… - … applications of artificial …, 2019 - Elsevier
Abstract The Engineering Applications of Artificial Intelligence (EAAI) is a journal of very high
repute in the domain of Engineering and Computer Science. This paper gives a broad view …

A review of data-driven fault detection and diagnosis methods: Applications in chemical process systems

N Md Nor, CR Che Hassan… - Reviews in Chemical …, 2020 - degruyter.com
Fault detection and diagnosis (FDD) systems are developed to characterize normal
variations and detect abnormal changes in a process plant. It is always important for early …

Applications of artificial intelligence‐based modeling for bioenergy systems: A review

M Liao, Y Yao - GCB Bioenergy, 2021 - Wiley Online Library
Bioenergy is widely considered a sustainable alternative to fossil fuels. However, large‐
scale applications of biomass‐based energy products are limited due to challenges related …

Machine learning techniques for quality control in high conformance manufacturing environment

CA Escobar… - Advances in Mechanical …, 2018 - journals.sagepub.com
In today's highly competitive global market, winning requires near-perfect quality. Although
most mature organizations operate their processes at very low defects per million …

XGBoost model as an efficient machine learning approach for PFAS removal: Effects of material characteristics and operation conditions

E Karbassiyazdi, F Fattahi, N Yousefi… - Environmental …, 2022 - Elsevier
Due to the implications of poly-and perfluoroalkyl substances (PFAS) on the environment
and public health, great attention has been recently made to finding innovative materials …

[HTML][HTML] Effective use of artificial intelligence in healthcare supply chain resilience using fuzzy decision-making model

M Deveci - Soft Computing, 2023 - Springer
AI technologies are absolutely changing the rules of the game all around the world.
However, the diffusion rate of AI is widely ranging across countries. This study aims to fulfill a …

[HTML][HTML] When computer science is not enough: universities knowledge specializations behind artificial intelligence startups in Italy

A Colombelli, E D'Amico, E Paolucci - The Journal of Technology Transfer, 2023 - Springer
This paper investigates the role of local knowledge specializations from universities in the
artificial intelligence (AI) startup creation process. The empirical analysis is grounded in the …