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Machining Parameters and Toolpath Productivity Optimization Using a Factorial Design and Fit Regression Model in Face Milling and Drilling Operations
Joint Authors
Méndez, J. Flores
Ambrosio Lázaro, R. C.
Ruiz-Huerta, Leopoldo
Minquiz, Gustavo M.
Borja, Vicente
López-Parra, Marcelo
Ramírez-Reivich, Alejandro C.
Sánchez, Alejandro Shigeru Yamamoto
Pavon-Solana, María-Esther
Vazquez-Leal, Hector
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-27
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Very commonly, a mechanical workpiece manufactured industrially includes more than one machining operation.
Even more, it is a common activity of programmers, who make a decision in this regard every time a milling and drilling operation is performed.
This research is focused on better understanding the power behavior for face milling and drilling manufacturing operations, and the methodology followed was the design of experiments (DOEs) with the cutting parameters set in combination with toolpath evaluation available in commercial software, having as main goal to get a predictive power equation validated in two ways, linear or nonlinear, and understanding the energy consumption and the quality surface in face milling and final diameter in drilling.
The results show that it is possible to find difference in a power demand of 1.52 kW to 3.9 kW in the same workpiece, depending on the operations (face milling or drilling), cutting parameters, and toolpath chosen.
Additionally, the equations modelled showed acceptable values to predict the power, with p values higher than 0.05 which is the significance level for the nonlinear and linear equations with an R square predictive of 98.36.
Some conclusions established that optimization of the cutting parameters combined with toolpath strategies can represent an energy consumption optimization higher than 0.21% and the importance to try to find an energy consumption balance when a workpiece has different milling operations.
American Psychological Association (APA)
Minquiz, Gustavo M.& Borja, Vicente& López-Parra, Marcelo& Ramírez-Reivich, Alejandro C.& Ruiz-Huerta, Leopoldo& Ambrosio Lázaro, R. C.…[et al.]. 2020. Machining Parameters and Toolpath Productivity Optimization Using a Factorial Design and Fit Regression Model in Face Milling and Drilling Operations. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1201541
Modern Language Association (MLA)
Minquiz, Gustavo M.…[et al.]. Machining Parameters and Toolpath Productivity Optimization Using a Factorial Design and Fit Regression Model in Face Milling and Drilling Operations. Mathematical Problems in Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1201541
American Medical Association (AMA)
Minquiz, Gustavo M.& Borja, Vicente& López-Parra, Marcelo& Ramírez-Reivich, Alejandro C.& Ruiz-Huerta, Leopoldo& Ambrosio Lázaro, R. C.…[et al.]. Machining Parameters and Toolpath Productivity Optimization Using a Factorial Design and Fit Regression Model in Face Milling and Drilling Operations. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1201541
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201541