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Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization
Joint Authors
Haber, Rodolfo E.
Beruvides, Gerardo
Castaño, Fernando
Quiza, Ramón
Villalonga, Alberto
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-17
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The complexity of machining processes relies on the inherent physical mechanisms governing these processes including nonlinear, emergent, and time-variant behavior.
The measurement of surface roughness is a critical step done offline by expensive quality control procedures.
The surface roughness prediction using an online efficient computational method is a difficult task due to the complexity of machining processes.
The paradigm of hybrid incremental modeling makes it possible to address the complexity and nonlinear behavior of machining processes.
Parametrization of models is, however, one bottleneck for full deployment of solutions, and the optimal setting of model parameters becomes an essential task.
This paper presents a method based on simulated annealing for optimal parameters tuning of the hybrid incremental model.
The hybrid incremental modeling plus simulated annealing is applied for predicting the surface roughness in milling processes.
Two comparative studies to assess the accuracy and overall quality of the proposed strategy are carried out.
The first comparative demonstrates that the proposed strategy is more accurate than theoretical, energy-based, and Taguchi models for predicting surface roughness.
The second study also corroborates that hybrid incremental model plus simulated annealing is better than a Bayesian network and a multilayer perceptron for correctly predicting the surface roughness.
American Psychological Association (APA)
Beruvides, Gerardo& Castaño, Fernando& Haber, Rodolfo E.& Quiza, Ramón& Villalonga, Alberto. 2017. Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization. Complexity،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1143380
Modern Language Association (MLA)
Beruvides, Gerardo…[et al.]. Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization. Complexity No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1143380
American Medical Association (AMA)
Beruvides, Gerardo& Castaño, Fernando& Haber, Rodolfo E.& Quiza, Ramón& Villalonga, Alberto. Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization. Complexity. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1143380
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143380