scholarly journals Robust Parametrization of a Model Predictive Controller for a CNC Machining Center Using Bayesian Optimization

2020 ◽  
Vol 53 (2) ◽  
pp. 10388-10394
Author(s):  
David Stenger ◽  
Muzaffer Ay ◽  
Dirk Abel
2019 ◽  
Vol 20 (3) ◽  
pp. 99-106
Author(s):  
Florin Chifan ◽  
◽  
Constantin Luca ◽  
Mihaita Horodinca ◽  
Catalin Gabriel Dumitras ◽  
...  

Author(s):  
Márcio Maciel da Silva ◽  
Michel Lenhago Beneducci Afonso ◽  
Stephanny Lohanny Nunes Silva ◽  
Fernanda Christina Teotonio Dias Troysi ◽  
Ítalo Bruno dos Santos ◽  
...  

Author(s):  
Kazumasa Kawasaki ◽  
Isamu Tsuji ◽  
Hiroshi Gunbara

Double-helical gears are usually manufactured using special type of machine tools, such as gear hobbing and shaping machines. In this paper, a manufacturing method of double-helical gears using a CNC machining center instead of the special type of machine tools is proposed. This manufacturing method has the following advantages: (i) the tooth surfaces can be modified arbitrarily, (ii) all we have to do in gear machining is only one machine setting, (iii) the hole and blank diameter and so on except the tooth surface can be also machined, and (iv) the auxiliary apparatus, special type of tools, and special type of machine tools are not needed. For this study, first the tooth profiles of the double-helical gear were modelled using a 3D computer-aided design system and the gear was machined using a CNC machining center based on a computer-aided manufacturing system. Next, the profile deviations, helix deviations, pitch deviations, and surface roughnesses of the manufactured double-helical gears were measured. Afterwards, the relationship between the tool wear and life time of the end mill were made clear. Finally, this manufacturing method was applied to the gears for a double-helical gear pump. As a result, the validity and effectiveness of the manufacturing method of double-helical gears using a CNC machining center were confirmed.


2012 ◽  
Vol 2012.87 (0) ◽  
pp. _14-6_
Author(s):  
Ryohei KAWAI ◽  
Eiichi AOYAMA ◽  
Toshiki HIROGAKI ◽  
Keiji OGAWA

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