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Wyszukujesz frazę "Sadek, M." wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Effect of the sign of anisotropy constants on the properties of the system of interacting ferromagnetic nanoparticles
Autorzy:
Sadek, M.
Marchwiany, M.
Woinska, M.
Majhofer, A.
Gosk, J.
Twardowski, A.
Szczytko, J.
Powiązania:
https://bibliotekanauki.pl/articles/1159850.pdf
Data publikacji:
2016-01
Wydawca:
Polska Akademia Nauk. Instytut Fizyki PAN
Tematy:
75.40.Mg
75.50.Tt
75.75.-c
Opis:
We use the Monte Carlo simulation method to investigate the influence of the signs of magnetocrystalline anisotropy constants and the magnetic dipole-dipole interactions on the zero field cooled-field cooled magnetization experiments and hysteresis curves of a system of magnetic nanoparticles. Positive first cubic anisotropy constant K₁ results in larger blocking temperatures and larger coercive fields of a system, while the second anisotropy constant K₂ is practically of negligible importance for the phenomena investigated. Magnetic dipole-dipole interactions are important only in the most dense systems of particles and their effects practically disappear for systems where the distance between the closest particles exceeds three particle diameters.
Źródło:
Acta Physica Polonica A; 2016, 129, 1a; A-53-A-55
0587-4246
1898-794X
Pojawia się w:
Acta Physica Polonica A
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent cyber-physical monitoring and control of I4.0 machining systems – an overview and future perspectives
Autorzy:
Hassan, Mahmoud
Sadek, Ahmad
Attia, M. Helmi
Powiązania:
https://bibliotekanauki.pl/articles/2052195.pdf
Data publikacji:
2022
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
machining process
artificial intelligence
modelling
optimisation
tool condition monitoring
Opis:
Rapid evolution in sensing, data analysis, and industrial internet of things technologies had enabled the manufacturing of advanced smart tooling. This has been fused with effective digital inter-connectivity and integrated process control intelligence to form the industry I4.0 platform. This keynote paper presents the recent advances in smart tooling and intelligent control techniques for machining processes. Self-powered wireless sensing nodes have been utilized for non-intrusive measurement of process-born phenomena near the cutting zone, as well as tool wear and tool failure, to increase confidence in the process and tool condition monitoring accuracy. Cyber-physical adaptive control approaches have been developed to optimize the cycle time and cost while eliminating machined part defects. Novel artificial intelligence AI-based signal processing and modeling approaches were developed to guarantee the generalization and practicality of these systems. The paper concludes with the outlook for future work needed for seamless implementation of these developments in industry.
Źródło:
Journal of Machine Engineering; 2022, 22, 1; 5-24
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent machining: real-time tool condition monitoring and intelligent adaptive control systems
Autorzy:
Hassan, M.
Sadek, A.
Attia, M. H.
Thomson, V.
Powiązania:
https://bibliotekanauki.pl/articles/99921.pdf
Data publikacji:
2018
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
adaptive control
tool condition monitoring
intelligent machining
Opis:
Unmanned manufacturing systems has recently gained great interest due to the ever increasing requirements of optimized machining for the realization of the fourth industrial revolution in manufacturing ‘Industry 4.0’. Real-time tool condition monitoring (TCM) and adaptive control (AC) machining system are essential technologies to achieve the required industrial competitive advantage, in terms of reducing cost, increasing productivity, improving quality, and preventing damage to the machined part. New AC systems aim at controlling the process parameters, based on estimating the effects of the sensed real-time machining load on the tool and part integrity. Such an aspect cannot be directly monitored during the machining operation in an industrial environment, which necessitates developing new intelligent model-based process controllers. The new generations of TCM systems target accurate detection of systematic tool wear growth, as well as the prediction of sudden tool failure before damage to the part takes place. This requires applying advanced signal processing techniques to multi-sensor feedback signals, in addition to using ultra-high speed controllers to facilitate robust online decision making within the very short time span (in the order of 10 ms) for high speed machining processes. The development of new generations of Intelligent AC and TCM systems involves developing robust and swift communication of such systems with the CNC machine controller. However, further research is needed to develop the industrial internet of things (IIOT) readiness of such systems, which provides a tremendous potential for increased process reliability, efficiency and sustainability.
Źródło:
Journal of Machine Engineering; 2018, 18, 1; 5-17
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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