Results 71 to 80 of about 5,320,548 (290)

A Hybrid Deep Learning Model as the Digital Twin of Ultra-Precision Diamond Cutting for In-Process Prediction of Cutting-Tool Wear

Applied Sciences, 2023
Diamond cutting-tool wear has a direct impact on the processing accuracy of the machined surface in ultra-precision diamond cutting. It is difficult to monitor the tool’s condition because of the slight wear amount.
Lei Wu, Kaijie Sha, Ye Tao, Bingfeng Ju, Yuanliu Chen   +4 more
doaj   +1 more source

Elastic–Plastic Modeling and Experimental Characterization of Granular Jamming Actuators

Advanced Engineering Materials, EarlyView.
Granular jamming enables rapid switching between soft and rigid mechanical states. Here, a reduced‐order elastic‐perfectly‐plastic beam framework captures pressure‐dependent loading, unloading, residual deformation, and hysteresis in jammed beams, while matching three‐point bending experiments across materials and geometries. The framework links design
Saheli Patel, Prashant K. Purohit, Jordan R. Raney   +2 more
wiley   +1 more source

Tool wear monitoring using generalized regression neural network

Advances in Mechanical Engineering, 2019
To improve the modeling accuracy and efficiency of the tool wear monitoring system, a generalized regression neural network is adopted to build the tool wear prediction model because its excellent performance on learning speed and fast convergence to the
Ling Kang, Sibao Wang, Shilong Wang, Chi Ma, Lili Yi, Haixu Zou   +5 more
doaj   +1 more source

Thermal Cycle–Microstructure–Property Relationships in Rail Steel Heat‐Affected Zone Simulated by Gleeble

Advanced Engineering Materials, EarlyView.
Microstructural evolution of premium rail steel during flash butt welding (FBW), comparing physically simulated heat‐affected zones with actual weld regions. Thermal cycles induce phase transformations and microstructural heterogeneity that influence weld quality and mechanical performance. These findings provide insights into optimizing FBW parameters
Emmanoelle Cintra da Cunha Araújo, João Marcos da Silva Nunes, Marcelly Cristiny Nunes de Carvalho, Alex Rojas, Cristie Luis Kugelmeier, Cristhian Ricardo Loayza Loayza, João Carlos Ferreira, Maria Veronica Goncalves Rodrigues, Rute Sayuri Kano, Isaac Araújo Furtado, Jacyara Dalylla da Silva Nunes, Jhonatan Peres de Sousa, Marcos Natan da Silva Lima, Eden Santos Silva, Gedeon Silva Reis, Samuel Filgueiras Rodrigues   +15 more
wiley   +1 more source

Tool Wear Predicting Based on Multisensory Raw Signals Fusion by Reshaped Time Series Convolutional Neural Network in Manufacturing

IEEE Access, 2019
Tool wear monitoring is a typical multi-sensor information fusion task. The handcrafted features may be a suboptimal choice that will lower the monitoring accuracy and require significant computational costs that hinder the real-time applications.
Zhiwen Huang, Jianmin Zhu, Jingtao Lei, Xiaoru Li, Fengqing Tian   +4 more
doaj   +1 more source

Microstructural Evolution and In Situ Formation of TiB and TiC in Ti─5Al─2.5Sn Alloy Processed by Powder Metallurgy

Advanced Engineering Materials, EarlyView.
Accelerated in situ formation of TiB and TiC in Ti–5Al–2.5Sn–B4C is driven by transient liquid phase formation, which enhances particle reactions and microstructural evolution. This process increases hardness and establishes a coupled relationship between sintering temperature and reinforcement content, strongly influencing porosity in the resulting ...
Fernando. Y. Kojima, Juliano. Soyama
wiley   +1 more source

Soft computing for tool life prediction a manufacturing application of neural - fuzzy systems [PDF]

, 1997
Tooling technology is recognised as an element of vital importance within the manufacturing industry. Critical tooling decisions related to tool selection, tool life management, optimal determination of cutting conditions and on-line machining process ...
Emmanouilidis, Christos I.
core  

Use of Neural Networks in Tool Wear Prediction [PDF]

MATEC Web of Conferences, 2019
Modern CNC machine tools include a number of sensors that collect machine status data. These data are used to control the production process and for control of the CNC machine status. No less importantpart of the production process is also a machine tool.
Kundrík Juraj, Kočiško Marek, Pollák Martin, Telišková Monika, Bašistová Anna, Fiala Zdeněk   +5 more
openaire   +2 more sources

Coordinated Architectural and Chemical Reinforcement in the Crushing Mandible of a Soldier Termite

Advanced Functional Materials, EarlyView.
The crushing mandible of a soldier termite withstands substantial biting loads despite lacking mineral. Its cuticle is partitioned: convex teeth pair hardness and zinc enrichment with aligned chitin fibers for contact durability, while stiffer concave regions between teeth carry bending loads.
Andrew Tran Nguyen, Patryk Wąsik, Juan Fernando Cucuyame Morales, Marie Kate Palau, Adrian Francisco Duran Ornelas, Phani Saketh Dasika, Jin Hee Kim, Radhika Laxminarayana, Eric Hintsala, Greta Chang, Junzhi Liao, Lizhi Sun, Nathan Lord, Atsushi Arakaki, Paul Bardunias, Pablo Zavattieri, David Kisailus   +16 more
wiley   +1 more source

Spatially Resolved Tool Wear Prediction in Finish Milling

, 2021
S.85-90Tool wear is a cost driver in the metal cutting industry. The development of tool wear is mostly unknown during process planning of a finish milling operation. This study investigates a tool wear prediction method based on a dexel-based engagement
Eduardo Maia Garcia, Philipp Ganser, Ganser, Philipp, Thomas Bergs, Holst, Carsten, Carsten Holst, Michael Königs, Bergs, Thomas, Königs, Michael, Garcia, Eduardo Maia   +9 more
core   +1 more source