scholarly journals Experimental Study to Minimize The Burr Formation in Drilling Process With Artifical Neural Networks (ANN) Analysis

Author(s):  
B. Dey ◽  
N. Mondal ◽  
S. Mondal
Author(s):  
Dmitry Buryak ◽  
Nina Popova ◽  
Vladimir Voevodin ◽  
Yuri Konkov ◽  
Oleg Ivanov ◽  
...  

2009 ◽  
Vol 35 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Anne M. P. Canuto ◽  
Araken M. Santos ◽  
Rogério R. Vargas

2020 ◽  
pp. 002199832095774
Author(s):  
Eduardo Pires Bonhin ◽  
Sarah David-Müzel ◽  
Manoel Cléber de Sampaio Alves ◽  
Edson Cocchieri Botelho ◽  
Marcos Valério Ribeiro

The use of fiber metal laminates (FML) in aeronautics components has been increased in the last years, mainly due to the gain in mechanical properties combined with low specific mass. However, in the assembly of these materials on the structures to which they will be attached, mechanical screwing is still the main method used, which requires the performance of drilling processes. Something it is very complicated for these materials and can cause damage that compromises the performance. Therefore, this work aims to approach and summarize the evolution of the mechanical drilling process on FML developed in the last years. By the work, the main problems that occur during the drilling of these materials are punctually approached, such as delamination, burr formation, dimensional error, poor roughness, and tool wear. In addition, it is presented how these problems are affected by the machining parameters (cutting parameters, geometry, material/coating tool, and cutting environment), as well as suggestions for minimizing process problems. Thus, the article intends to provide as much information as possible available in the literature, seeking to help researchers gain a comprehensive view of the mechanical drilling of fiber metal laminates.


2002 ◽  
Vol 124 (3) ◽  
pp. 509-514 ◽  
Author(s):  
Chensong Dong ◽  
Chuck Zhang ◽  
Ben Wang ◽  
Guoxiong Zhang

Coordinate measuring machines (CMMs) are already widely utilized as measuring tools in the modern manufacturing industry. Rapidly approaching now is the trend for next-generation CMMs. However, the increases in measuring velocity of CMM applications are limited by dynamic errors that occur in CMMs. In this paper, a systematic approach for modeling the dynamic errors of a touch-trigger probe CMM is developed through theoretical analysis and experimental study. An overall analysis of the dynamic errors of CMMs is conducted, with weak components of the CMM identified with a laser interferometer. The probing process, as conducted with a touch-trigger probe, is analyzed. The dynamic errors are measured, modeled, and predicted using neural networks. The results indicate that, using this mode, it is possible to compensate for the dynamic errors of CMMs.


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