Results 31 to 40 of about 119,208 (317)

Experimental and numerical study of laser-assisted machining of Ti6Al4V titanium alloy [PDF]

open access: yes, 2014
Laser-assisted machining combines several experimental parameters such as cutting speed, feed rate, depth of cut, laser power and distance between tool rake face and the laser beam axis.
GERMAIN, Guénaël   +3 more
core   +1 more source

Study on the Influence of Sapphire Crystal Orientation on Its Chemical Mechanical Polishing

open access: yesApplied Sciences, 2020
Sapphire has been the most widely used substrate material in LEDs, and the demand for non-C-planes crystal is increasing. In this paper, four crystal planes of the A-, C-, M- and R-plane were selected as the research objects.
Linlin Cao   +6 more
doaj   +1 more source

Segmented Four-Element Photodiodes in a Three-Dimensional Laser Beam Angle Measurement

open access: yesPhotonics, 2023
Based on the registration of two laser beam projections, a method for measuring the angular deviation of a laser beam from its initial position in three-dimensional space is proposed and experimentally demonstrated.
Stanislav Konov   +4 more
doaj   +1 more source

Degradation modes and tool wear mechanisms in finish and rough machining of Ti17 Titanium alloy under high-pressure water jet assistance [PDF]

open access: yes, 2013
This article presents the results of an experimental study on the Ti17 titanium alloy, which was carried out to analyze tool wear and the degradation mechanisms of an uncoated tungsten carbide tool insert. Two machining conditions, roughing and finishing,
GERMAIN, Guénaël   +3 more
core   +1 more source

Surface Modification of Silicon Carbide Wafers Using Atmospheric Plasma Etching: Effects of Processing Parameters

open access: yesMicromachines, 2023
Silicon carbide wafer serves as an ideal substrate material for manufacturing semiconductor devices, holding immense potential for the future. However, its ultra-hardness and remarkable chemical inertness pose significant challenges for the surface ...
Qi Jin, Julong Yuan, Jianxing Zhou
doaj   +1 more source

Machine transliteration [PDF]

open access: yesProceedings of the eighth conference on European chapter of the Association for Computational Linguistics -, 1997
It is challenging to translate names and technical terms across languages with different alphabets and sound inventories. These items are commonly transliterated, i.e., replaced with approximate phonetic equivalents. For example, "computer" in English comes out as "konpyuutaa" in Japanese.
Kevin Knight, Jonathan Graehl
openaire   +2 more sources

Cost of photochemical machining [PDF]

open access: yes, 2004
Photochemical machining (PCM), also known as photoetching, photofabrication or photochemical milling, is a non-traditional manufacturing method based on the combination of photoresist imaging and chemical etching.
Roy, Rajkumar   +2 more
core   +1 more source

Self-synchronization of Nonidentical Machines in Machine-to-Machine Systems

open access: yes2013 IEEE 7th International Conference on Self-Adaptive and Self-Organizing Systems, 2013
The notion of common time is very important information in distributed systems (e.g., for maintaining the consistency of distributed data). Namely, due to the lack of global time and imperfections (e.g., skew) of physical clocks, in order to agree on common time, distributed nodes have to synchronize themselves.
Bojić, Iva, Kušek, Mario
openaire   +3 more sources

An Experimental Investigation of Hot Machining with Induction to Improve Ti-5553 Machinability [PDF]

open access: yes, 2011
The manufacturing of aeronautic parts with high mechanical properties requires the use of high performance materials. That’s why; new materials are used for landing gears such as the titanium alloy Ti-5553.
Julien Sallaberry   +9 more
core   +1 more source

Machine Learned Learning Machines

open access: yesCoRR, 2017
There are two common approaches for optimizing the performance of a machine: genetic algorithms and machine learning. A genetic algorithm is applied over many generations whereas machine learning works by applying feedback until the system meets a performance threshold. Though these are methods that typically operate separately, we combine evolutionary
Leigh Sheneman, Arend Hintze
openaire   +2 more sources

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