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Prediction of Burr Formation During Face Milling Using an ANN with Optimized Cutting Conditions

Title
Prediction of Burr Formation During Face Milling Using an ANN with Optimized Cutting Conditions
Author
이성환
Keywords
face milling; burr; optimization; cutting parameters; Taguchi method; ANOVA; ANN
Issue Date
2007-12
Publisher
PROFESSIONAL ENGINEERING PUBLISHING LTD
Citation
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE, v. 221, No. 12, Page. 1705-1714
Abstract
Burrs formed during face milling operations are difficult to characterize because there are several parameters with complex interactions that affect the cutting process. In this paper, a combined artificial intelligence and optimization approach is introduced to predict burr types formed during face milling. The Taguchi method was selected for the optimization and an artificial neural network (ANN) was constructed for the machining of aluminium alloy 6061-T6. For the training of the ANN, the input was non-dimensionalized using the optimized results from the Taguchi method. The resulting ANN output was in agreement with experimental results, validating the proposed scheme.
URI
https://journals.sagepub.com/doi/abs/10.1243/09544054jem870https://repository.hanyang.ac.kr/handle/20.500.11754/107534
ISSN
0954-4054; 2041-2975
DOI
10.1243/09544054JEM870
Appears in Collections:
COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > MECHANICAL ENGINEERING(기계공학과) > Articles
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