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Research solution for automatic hole quality analysis when drilling fiber-reinforced composites.

Authors :
Hrechuk, Andrii
Hörndahl, Mikael
Schultheiss, Fredrik
Source :
International Journal of Advanced Manufacturing Technology; Aug2023, Vol. 127 Issue 7/8, p3315-3324, 10p, 3 Color Photographs, 1 Black and White Photograph, 2 Diagrams, 2 Graphs
Publication Year :
2023

Abstract

Fiber-reinforced polymers are highly demanding composites in aerospace and automotive areas because of their excellent mechanical properties such as stiffness and strength-to-weight ratio. The drilling remains the major machining operation applied to composites to provide high-quality holes for joints between parts. Due to composites plied structure, the drilling is accompanied with unusual form metal cutting defects such as delamination and uncut fibers around the drilled hole. Considering that the tool life of some drills reaches over thousands of holes, the research of composites machinability becomes difficult due to demanded labor intensity in manual inspection of the hole quality. Therefore, this paper develops the research solution for automatic analysis of the hole quality in drilled fiber-reinforced materials. The paper proposes a complex of solutions aimed to speed up the analysis of the hole quality when composites drilling. The solution consists of the developed vacuum table, robot arm with high-speed camera, developed top and bottom lightning systems, and Image Processing algorithms for defect detection from captured images. The paper results show how the developed solution can be used for high routine research activities. The output data, including tested 72 cutting data parameters and full-size tool life test, allowed identifying the operational window for high-speed steel drills and the range of tool life, where drill ensures a certain hole quality. The paper shows the efficiency of the developed research solution can reach 5 s per hole including drilling and full cycle of measurements having measurement error of 1–3%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
127
Issue :
7/8
Database :
Complementary Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
164783353
Full Text :
https://doi.org/10.1007/s00170-023-11696-4