Results 91 to 100 of about 9,973,281 (284)

Investigation using single point incremental forming (SPIF) to fabricate patient-specific, titanium orbital floor implants [PDF]

open access: yesMATEC Web of Conferences
The floor of the human orbit is composed of thin bone that is prone to traumatic fracture. This leads to a loss of support for the eye, which can cause vision changes. Therefore, fractures may need surgical reconstruction using a thin, sheet-like implant.
Mamros Elizabeth M.   +2 more
doaj   +1 more source

Experimental force measurements in single point incremental sheet forming SPIF

open access: yes, 2015
This paper provides the experimental protocol, of the process of a single point incremental sheet forming “SPIF”, allowing predicting the efforts of forming. To speak about parameters of a single point incremental sheet forming (SPIF),
Badreddine Saidi   +3 more
core   +1 more source

Inverse Identification of Energy‐Dependent Laser Absorptivity in NiTi Laser Powder‐Bed Fusion via Calibrated Melt Pool Simulation

open access: yesAdvanced Engineering Materials, EarlyView.
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi   +3 more
wiley   +1 more source

Study the Effect of Multilayer Single Point Incremental Forming on Residual Stresses for Bottom Plates

open access: yesAl-Khawarizmi Engineering Journal, 2017
Knowing the amount of residual stresses and find technological solutions to minimize and control them during the production operation are an important task because great levels of deformation which occurs in single point incremental forming (SPIF), this ...
Aseel Hamad Abed   +2 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

Robot-assisted Single Point Incremental Forming: Focus on shape accuracy of the final part [PDF]

open access: yesMATEC Web of Conferences
Single Point Incremental Forming (SPIF) is regarded as an innovative and flexible manufacturing process able to produce complex shapes: in fact, the punch, moving along a toolpath, incrementally deforms a blank until the required geometry is reached. The
Cannillo Michele   +7 more
doaj   +1 more source

Continuous Stiffness Graded Metal–Ceramic Femoral Stems: UMAT‐Based Design and Finite Element Assessment

open access: yesAdvanced Engineering Materials, EarlyView.
Functionally graded metal–ceramic femoral stems are engineered through continuous UMAT‐based stiffness tailoring, eliminating discrete material interfaces while enhancing biomechanical compatibility. Low‐index power‐law gradation optimizes load transfer, reduces stress shielding, and controls implant–bone micromotion, highlighting a materials‐design ...
Rihem Nouira, Sameh Elleuch, Hanen Jrad
wiley   +1 more source

THE EXPERIMRNTAL RESEARCH ON SINGLE POINT INCREMENTAL FORMING U-SHAPED METAL BELLOWS

open access: yesJixie qiangdu, 2018
The manufacturing requirements and research status of plastic forming pipe fittings in the industrial field are analyzed. The working principle of single point incremental forming metal bellows is introduced.
HOU XiaoLi   +4 more
doaj  

Roundness and positioning deviation prediction in single point incremental forming using deep learning approaches

open access: yesAdvances in Mechanical Engineering, 2019
This article proposes a deep learning technique for the prevision of the geometric accuracy in single point incremental forming. Moreover, predicting geometric accuracy is one of the most crucial measures of part quality.
Sofien Akrichi   +3 more
doaj   +1 more source

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