…
comment: The repository administrator has not yet configured an RDF license.
primary topic: Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions

Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
type: AcademicArticle
type: Article
abstract: Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were divided randomly into three subsets for training, validation, and testing the developed hybrid intelligent model. ANOVA results revealed that feed rate is highly affected by the surface roughness followed by the depth of cut. One-way ANOVA, including a Post-Hoc test, was used to evaluate the performance of three developed models. The hybrid model of Artificial Neural Network-Gravitational Search Algorithm (ANN-GSA) has outperformed Artificial Neural Network (ANN) and Artificial Neural Network-Genetic Algorithm (ANN-GA) models. ANN-GSA achieved minimum testing mean square error of 7.41 Ã� 10â��13 and a maximum R-value of 1. Further, its convergence speed was faster than ANN-GA. GSA proved its ability to improve the performance of BPNN, which suffers from local minima problems. © 2022 by the authors.
date: 2022
volume: 10
issue: 10
is part of: Lubricants
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository

MDPI
type: Organization

Lubricants
type: Collection
issn: 20754442

Mohd Shukor Salleh
type: Person
given name: Mohd Shukor
family name: Salleh

Salah Al-Zubaidi
type: Person
given name: Salah
family name: Al-Zubaidi

Che Hassan Che Haron
type: Person
given name: Che Hassan
family name: Che Haron

M. Abdulrazaq
type: Person
given name: M.
family name: Abdulrazaq

M.N. Mohammed
type: Person
given name: M.N.
family name: Mohammed

Oday I. Abdullah
type: Person
given name: Oday I.
family name: Abdullah

Jaharah A.Ghani
type: Person
given name: Jaharah
family name: A.Ghani

Adnan Naji Jameel Al-Tamimi
type: Person
given name: Adnan Naji
family name: Jameel Al-Tamimi

Samaher M.Sarhan
type: Person
given name: Samaher
family name: M.Sarhan

HTML Summary of #20587 Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
format: text/html
primary topic: Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions