Systematic review on tool breakage monitoring techniques in machining operations

X Li, X Liu, C Yue, SY Liang, L Wang - International Journal of Machine …, 2022 - Elsevier
Tool condition monitoring (TCM) in machining operations is crucial to maximise the useful
tool life while reducing the risks associated with tool breakage. Unlike progressive tool wear …

Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research

S Gawde, S Patil, S Kumar, P Kamat, K Kotecha… - … Applications of Artificial …, 2023 - Elsevier
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …

[HTML][HTML] A few shot classification methods based on multiscale relational networks

W Zheng, X Tian, B Yang, S Liu, Y Ding, J Tian, L Yin - Applied Sciences, 2022 - mdpi.com
Learning information from a single or a few samples is called few-shot learning. This
learning method will solve deep learning's dependence on a large sample. Deep learning …

Augmented data driven self-attention deep learning method for imbalanced fault diagnosis of the HVAC chiller

C Shen, H Zhang, S Meng, C Li - Engineering Applications of Artificial …, 2023 - Elsevier
The chiller fault diagnosis is of great significance to maintain the normal operation of the
HVAC system and indoor comfort. Due to the difficulty in collecting the chiller's fault data, we …

[HTML][HTML] A low-cost multi-sensor data acquisition system for fault detection in fused deposition modelling

S Kumar, T Kolekar, S Patil, A Bongale, K Kotecha… - Sensors, 2022 - mdpi.com
Fused deposition modelling (FDM)-based 3D printing is a trending technology in the era of
Industry 4.0 that manufactures products in layer-by-layer form. It shows remarkable benefits …

[HTML][HTML] Towards resilient and sustainable rail and road networks: A systematic literature review on digital twins

J Vieira, J Poças Martins, N Marques de Almeida… - Sustainability, 2022 - mdpi.com
The digital transformation of engineering assets has been receiving increased attention from
the scientific community in the last few years. In this regard, Digital Twins (DTs) have been …

[HTML][HTML] Fault detection in induction motor using time domain and spectral imaging-based transfer learning approach on vibration data

S Misra, S Kumar, S Sayyad, A Bongale, P Jadhav… - Sensors, 2022 - mdpi.com
The induction motor plays a vital role in industrial drive systems due to its robustness and
easy maintenance but at the same time, it suffers electrical faults, mainly rotor faults such as …

CycleGAN for undamaged-to-damaged domain translation for structural health monitoring and damage detection

F Luleci, FN Catbas, O Avci - Mechanical Systems and Signal Processing, 2023 - Elsevier
The advances in data science in the last few decades have benefitted many other fields,
including Structural Health Monitoring (SHM). Artificial Intelligence (AI), such as Machine …

A systematic literature review on transfer learning for predictive maintenance in industry 4.0

MS Azari, F Flammini, S Santini, M Caporuscio - IEEE access, 2023 - ieeexplore.ieee.org
The advent of Industry 4.0 has resulted in the widespread usage of novel paradigms and
digital technologies within industrial production and manufacturing systems. The objective of …

[HTML][HTML] Stunting convergence management framework through system integration based on regional service governance

A Prasetyo, N Noviana, W Rosdiana, MA Anwar… - Sustainability, 2023 - mdpi.com
The acceleration of stunting reduction in Indonesia is one of the priority agendas in the
health sector, its implementation being through various regional and tiered approaches. This …