[HTML][HTML] Tribological characteristics of additively manufactured 316 stainless steel against 100 cr6 alloy using deep learning

MK Gupta, ME Korkmaz, CS Shibi, NS Ross… - Tribology …, 2023 - Elsevier
Under different working conditions, the tribological characteristics of materials show a
complicated and non-linear relation. As a result, it is crucial to advance tribology by …

Do technologies really affect that much? Exploring the potential of several industry 4.0 technologies in today's lean manufacturing shop floors

A Sartal, J Llach, F León-Mateos - Operational Research, 2022 - Springer
We investigated the synergies and trade-offs between lean management practices and
digital transformation promoted via Industry 4.0 (I4. 0) technologies in current manufacturing …

A novel physics-regularized interpretable machine learning model for grain growth

W Yan, J Melville, V Yadav, K Everett, L Yang… - Materials & Design, 2022 - Elsevier
Experimental grain growth observations often deviate from grain growth simulations,
revealing that the governing rules for grain boundary motion are not fully understood. A …

Designing Ti alloy for hard tissue implants: a machine learning approach

ACA Raj, S Datta - Journal of Materials Engineering and Performance, 2023 - Springer
Many of the hard tissue implants are made of titanium alloys, due to its low specific strength
and low elastic modulus with excellent biocompatibility and good corrosion resistance. The …

Anomaly detection for high-speed machining using hybrid regularized support vector data description

Z Ma, M Zhao, X Dai, Y Chen - Robotics and Computer-Integrated …, 2025 - Elsevier
Process monitoring in high-speed machining (HSM) is essential to guarantee product quality
and improve manufacturing efficiency. Nevertheless, the data acquired from practical …

Toward data-driven research: preliminary study to predict surface roughness in material extrusion using previously published data with machine learning

F García-Martínez, D Carou… - Rapid Prototyping …, 2023 - emerald.com
Purpose Material extrusion is one of the most commonly used approaches within the
additive manufacturing processes available. Despite its popularity and related technical …

Optimizing the quality characteristics of glass composite vias for RF-MEMS using central composite design, metaheuristics, and bayesian regularization-based …

A Dvivedi, P Kumar - Measurement, 2025 - Elsevier
Technological improvement in micro devices has accentuated the demand for glass and its
composites. The μ-ECDM is emerging as an evolutionary technique for glass composite …

Integrating Industry 4.0 technologies into lean thinking for the development of efficient, low-carbon processes

A Sartal, F León-Mateos, R Bellas - Lean thinking in Industry 4.0 and …, 2023 - igi-global.com
This chapter aims to explore how lean manufacturing (LM) can leverage Industry 4.0
resources to achieve better industrial performance while achieving cleaner processes. In …

Concept for Predictive Quality in Carbon Fibre Manufacturing

S Gellrich, T Groetsch, M Maghe, C Creighton, R Varley… - 2024 - dro.deakin.edu.au
Remarkable mechanical properties make carbon fibres attractive for many industrial
applications. However, up to today, carbon fibres come with a significant environmental …

Development of a deep learning machining feature recognition network for recognition of four pilot machining features

N Mohammadi, MJ Nategh - The International Journal of Advanced …, 2022 - Springer
Over the past few decades, several methods have been introduced for the recognition of
machining features from design files. These methods entail considerable effort to infer the …