Results 21 to 30 of about 9,590 (172)

Locating Error when Clamping Workpiece between Centers [PDF]

MATEC Web of Conferences, 2021
The total machining error includes some distinct errors summed up by following certain rules. One of these errors is the workpiece locating error, which occurs when the workpiece reference base does not match the workpiece locating surface.
Slătineanu Laurentiu, Coteaţă Margareta, Dodun Oana, Nagîţ Gheorghe, Hriţuc Adelina, Beşliu-Băncescu Irina, Boca Mihai   +6 more
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Modelling of transitional workpiece deformation in end-milling considering workpiece rigidity reduction

Nihon Kikai Gakkai ronbunshu, 2023
Workpiece rigidity during end-milling processes decreases monotonously. Reduction rates of the rigidity become large when the end-milling operations have large cutting stock such as carve out machining.
Koji TERAMOTO, Yutaro NAKAO, Yuya HIBINO
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Geometric Theorems and Application of the DOF Analysis of the Workpiece Based on the Constraint Normal Line

Advances in Materials Science and Engineering, 2021
Aiming at the problem of judging the degree of freedom (DOF) of the workpiece in the fixture by experience, it is difficult to adapt to the analysis of the DOF of some singular workpieces.
Guojun Luo, Xiaohui Wang, Xianguo Yan
doaj   +1 more source

Improvement of form accuracy in cylindrical traverse grinding with steady rest by controlling traverse speed

Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2021
In cylindrical traverse grinding, a slender workpiece is bent by the normal grinding force due to its low stiffness. Consequently, a form error is generated by the elastic deformation of the workpiece during the grinding process.
Hidetaka FUJII, Takashi ONISHI, Chinhu LIN, Moriaki SAKAKURA, Kazuhito OHASHI   +4 more
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Electromechanical Coupling Dynamic and Vibration Control of Robotic Grinding System for Thin-Walled Workpiece

Actuators, 2023
The robotic grinding system for a thin-walled workpiece is a multi-dimensional coupling system composed of a robot, a grinding spindle and the thin-walled workpiece.
Yufei Liu, Dong Tang, Jinyong Ju
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Study of the deformation state during the pulling of the workpiece in a special die

Metalurgija, 2021
The article presents the results of a study of the deformation state when pulling a metal workpiece in a special die, preventing unidirectional metal flow in the longitudinal direction. The study of the deformation state and the construction of fields of
Zh. A. Ashkeyev, M. Zh. Abishkenov, S. A. Mashekov, A. Kawałek, K. A. Nogaev   +4 more
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ANALYSIS OF THE THERMAL FRICTION DRILLING PROCESS FOR EFFECTIVE PARAMETRIC CHOICE ON THE DRILLING OF AISI 304 STAINLESS STEEL USING THE FUZZY AHP-MOORA METHOD

Mağallaẗ Al-kūfaẗ Al-handasiyyaẗ
Attaining effective quality control of drilled samples in thermal friction drilling is a challenge considering the disproportionate allocation of drilling resources to parameters.
Ugochukwu Sixtus Nwankiti, Adeyinka Oluwo, Manasseh Olusegun Oyekeye, John Rajan, Swaminathan Jose, Rajeshwar Kadadevarmath, Sunday Ayoola Oke, Samuel Bolaji Aderibigbe, Samson Oluwaseun Odudare   +8 more
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Strain state and microstructure evolution of AISI-316 austenitic stainless steel during high-pressure torsion (HPT) process in the new stamp design

Metalurgija, 2021
The investigation of strain state and microstructure evolution of AISI-316 austenitic stainless steel during highpressure torsion process in the new stamp design was performed. The study using Deform-3D program was conducted.
A. Volokitin, I. Volokitina, E. Panin, A. Naizabekov, S. Lezhnev   +4 more
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Irregular Workpiece Template-Matching Algorithm Using Contour Phase

Algorithms, 2022
The current template-matching algorithm can match the target workpiece but cannot give the position and orientation of the irregular workpiece. Aiming at this problem, this paper proposes a template-matching algorithm for irregular workpieces based on ...
Shaohui Su, Jiadong Wang, Dongyang Zhang
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PolishNet-2d and PolishNet-3d: Deep Learning-Based Workpiece Recognition

IEEE Access, 2019
In recent years, there have been many deep learning research projects based on two-dimensional object detection and three-dimensional point cloud recognition.
Fuqiang Liu, Zongyi Wang
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