Machine learning and deep learning based predictive quality in manufacturing: a systematic review
With the ongoing digitization of the manufacturing industry and the ability to bring together
data from manufacturing processes and quality measurements, there is enormous potential …
data from manufacturing processes and quality measurements, there is enormous potential …
Intelligent disassembly of electric-vehicle batteries: a forward-looking overview
Retired electric-vehicle lithium-ion battery (EV-LIB) packs pose severe environmental
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …
hazards. Efficient recovery of these spent batteries is a significant way to achieve closed …
Deep learning and model predictive control for self-tuning mode-locked lasers
T Baumeister, SL Brunton, JN Kutz - JOSA B, 2018 - opg.optica.org
Self-tuning optical systems are of growing importance in technological applications such as
mode-locked fiber lasers. Such self-tuning paradigms require intelligent algorithms capable …
mode-locked fiber lasers. Such self-tuning paradigms require intelligent algorithms capable …
Transfer-learning: Bridging the gap between real and simulation data for machine learning in injection molding
In the field of manufacturing process planning and initial operation of machines, machine
parameters are often provided from few either expensive and time-consuming experiments …
parameters are often provided from few either expensive and time-consuming experiments …
Experimental investigations and modeling for multi-pass laser micro-milling by soft computing-physics informed machine learning on PMMA sheet using CO2 laser
Laser micro-machining has gained significant attraction from industries and researchers due
to the wide range of processability and material flexibility with micro-scale accuracy …
to the wide range of processability and material flexibility with micro-scale accuracy …
Laser Processing of Emerging Nanomaterials for Optoelectronics and Photocatalysis
Optoelectronics and photocatalysis are two rapidly developing photonic fields that are
revolutionizing green energy, medicine, communications, and robotics. To advance these …
revolutionizing green energy, medicine, communications, and robotics. To advance these …
Industrial transfer learning: Boosting machine learning in production
In the field of production, machine learning offers great potentials to develop innovative
solutions for optimization or automation. However, it faces challenges with regard to the …
solutions for optimization or automation. However, it faces challenges with regard to the …
Modelling of fibre laser cutting via deep learning
AF Courtier, M McDonnell, M Praeger… - Optics …, 2021 - opg.optica.org
Laser cutting is a materials processing technique used throughout academia and industry.
However, defects such as striations can be formed while cutting, which can negatively affect …
However, defects such as striations can be formed while cutting, which can negatively affect …
Nanosecond pulsed laser ablation of silicon—finite element simulation and experimental validation
In the present work, we perform finite element simulations to investigate the ablated surface
morphology of silicon by nanosecond pulsed laser ablation using low laser fluences ranging …
morphology of silicon by nanosecond pulsed laser ablation using low laser fluences ranging …
Simplified ResNet approach for data driven prediction of microstructure-fatigue relationship
C Gebhardt, T Trimborn, F Weber, A Bezold… - Mechanics of …, 2020 - Elsevier
The heterogeneous microstructure in metallic components results in locally varying fatigue
strength. Metal fatigue strongly depends on size and shape of non-metallic inclusions and …
strength. Metal fatigue strongly depends on size and shape of non-metallic inclusions and …