[HTML][HTML] Machine learning and artificial intelligence in CNC machine tools, a review
Abstract Artificial Intelligence (AI) and Machine learning (ML) represents an important
evolution in computer science and data processing systems which can be used in order to …
evolution in computer science and data processing systems which can be used in order to …
Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …
for quality prediction and process optimization of metal additive manufacturing (AM) …
Process monitoring of machining
This keynote paper mainly focuses on advancements of machining technology and systems
for enhanced performance, increased system integration and augmented machine …
for enhanced performance, increased system integration and augmented machine …
A systematic literature review on machine tool energy consumption
N Sihag, KS Sangwan - Journal of Cleaner Production, 2020 - Elsevier
Energy efficiency has become an integral part of the metal manufacturing industries as a
means to improve economic and environmental performance, and increase …
means to improve economic and environmental performance, and increase …
Multimodal data fusion for systems improvement: A review
In recent years, information available from multiple data modalities has become increasingly
common for industrial engineering and operations research applications. There have been a …
common for industrial engineering and operations research applications. There have been a …
A generic energy prediction model of machine tools using deep learning algorithms
Energy prediction of machine tools plays an irreplaceable role in energy planning,
management, and conservation in the manufacturing industry. In the era of big machinery …
management, and conservation in the manufacturing industry. In the era of big machinery …
Surface roughness prediction through GAN-synthesized power signal as a process signature
Predicting machined surface roughness is critical for estimating a part's performance
characteristics such as susceptibility to fatigue and corrosion. Prior studies have indicated …
characteristics such as susceptibility to fatigue and corrosion. Prior studies have indicated …
[HTML][HTML] Prediction of specific cutting energy consumption in eco-benign lubricating environment for biomedical industry applications: Exploring efficacy of GEP, ANN …
This study emphasizes the criticality of measuring specific cutting energy in machining
Hastelloy C276 for biomedical industry applications, offering valuable insights into …
Hastelloy C276 for biomedical industry applications, offering valuable insights into …
Prediction of surface residual stress in end milling with Gaussian process regression
M Cheng, L Jiao, P Yan, L Feng, T Qiu, X Wang… - Measurement, 2021 - Elsevier
The residual stress has an important influence on the performance of parts such as fatigue
life, and many researches have been carried out for the quantitative evaluation or prediction …
life, and many researches have been carried out for the quantitative evaluation or prediction …
Predictive modelling and Pareto optimization for energy efficient grinding based on aANN-embedded NSGA II algorithm
J Wang, Y Tian, X Hu, Y Li, K Zhang, Y Liu - Journal of Cleaner Production, 2021 - Elsevier
A large amount of global power consumption and environmental pollution problems are
attributed to manufacturing industries. Grinding is one of the most energy intensive precision …
attributed to manufacturing industries. Grinding is one of the most energy intensive precision …