Performance measurement system and quality management in data-driven Industry 4.0: A review
The birth of mass production started in the early 1900s. The manufacturing industries were
transformed from mechanization to digitalization with the help of Information and …
transformed from mechanization to digitalization with the help of Information and …
Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective
Carbon capture, utilization, and storage (CCUS) is a promising pathway to decarbonize
fossil-based power and industrial sectors and is a bridging technology for a sustainable …
fossil-based power and industrial sectors and is a bridging technology for a sustainable …
A novel integrated BPNN/SNN artificial neural network for predicting the mechanical performance of green fibers for better composite manufacturing
Since the mechanical properties of green cellulosic fibers are only determined
experimentally with high diversity, introducing prediction methods for such intrinsic …
experimentally with high diversity, introducing prediction methods for such intrinsic …
Mechanical properties prediction of composite laminate with FEA and machine learning coupled method
C Zhang, Y Li, B Jiang, R Wang, Y Liu, L Jia - Composite Structures, 2022 - Elsevier
In order to predict mechanical properties of composite laminate, a method coupling finite
element analysis (FEA) and machine learning is established to analyze three examples of …
element analysis (FEA) and machine learning is established to analyze three examples of …
[HTML][HTML] Advances in machine learning-aided design of reinforced polymer composite and hybrid material systems
Reinforced composite is a preferred choice of material for the design of industrial lightweight
structures. As of late, composite materials analysis and development utilizing machine …
structures. As of late, composite materials analysis and development utilizing machine …
Is information and communications technology effective for industrial energy conservation and emission reduction? Evidence from three energy-intensive industries in …
Abstract Information and communications technology (ICT) can significantly contribute to
industrial energy conservation and emission reduction by improving production and …
industrial energy conservation and emission reduction by improving production and …
[HTML][HTML] Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques
This paper examines the crashworthiness performance of composite rectangular tubes
using experimental and artificial neural network (ANN) techniques. Based on experimentally …
using experimental and artificial neural network (ANN) techniques. Based on experimentally …
Prediction of ultimate conditions and stress–strain behaviour of steel-confined ultra-high-performance concrete using sequential deep feed-forward neural network …
Recognising that ultra-high-performance concrete (UHPC) is gaining momentum in
structural applications, providing an accurate confinement model is essential to develo** …
structural applications, providing an accurate confinement model is essential to develo** …
Parametric analysis on explosion resistance of composite with finite element and artificial neural network
C Chen, M Li, Q Wang, R Guo, P Zhao… - Mechanics of Advanced …, 2024 - Taylor & Francis
To analyze the factors influencing the explosion resistance of composite laminates
subjected to explosive blasts in air, a finite element analysis (FEA) model was utilized. The …
subjected to explosive blasts in air, a finite element analysis (FEA) model was utilized. The …
[HTML][HTML] A critical review on machine learning applications in fiber composites and nanocomposites: Towards a control loop in the chain of processes in industries
Fiber composites must be evaluated to achieve correct use in various fields. Their
properties, performance, condition, and integrity can be quickly predicted and optimized by …
properties, performance, condition, and integrity can be quickly predicted and optimized by …