Analysis of surface finish in drilling of composites using neural networks

Composite materials are widely used in the aerospace industry because of their high strength-to-weight ratio. Although they have many advantages, their inhomogeneity and anisotropy pose problems. Because of these properties, machining of composites, unlike conventional metal working, needs more inve...

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Bibliographic Details
Main Author: Madiwal, Shashidhar
Other Authors: Bahr, Behnam
Format: Others
Language:en_US
Published: 2007
Subjects:
Online Access:http://hdl.handle.net/10057/566
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spelling ndltd-WICHITA-oai-soar.wichita.edu-10057-5662013-04-19T20:59:45ZAnalysis of surface finish in drilling of composites using neural networksMadiwal, ShashidharComposite materialsDrillingArtificial Neural NetworkElectronic dissertationsComposite materials are widely used in the aerospace industry because of their high strength-to-weight ratio. Although they have many advantages, their inhomogeneity and anisotropy pose problems. Because of these properties, machining of composites, unlike conventional metal working, needs more investigation. Conventional drilling of composites is one such field that requires extensive study and research. Among various parameters that determine the quality of a drilled hole, surface finish is of vital importance. The surface finish of a drilled hole depends on speed, feed-rate, material of the work piece, and geometry of the drill bit. This project studied the effect of speed and feed on surface finish and also the optimization of these parameters. Experiments were conducted based on Design of Experiment (DOE) and qualitative verification using Artificial Neural Network (ANN). Relevant behavior of surface finish was also studied. In this project, holes were drilled using a conventional twist drill at different cutting speeds (2,000 to 5,000 rpm) and feed rate was varied from 0.001 to 0.01 ipr for solid carbon fiber laminate (composite material). The other material drilled is BMS 8-276 form 3 (toughened resin system). Also five different drill bits were used to conduct experiments on BMS 8-276 form 3. Speed values were 5,000, 3,000, and 2,000 rpm and feed rates were 0.004, 0.006, and 0.01 ipr. The effect of speed, feed rate, and different drill geometries was analyzed with respect to surface finish in the drilled composites.Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Mechanical Engineering."July 2006."Includes bibliographic references (leaves 79-81).Bahr, Behnam2007-05-02T13:53:59Z2007-05-02T13:53:59Z2006-07Thesisxv, 91 leaves: ill., digital, PDF file.5039484 bytesapplication/pdft06105http://hdl.handle.net/10057/566en_USCopyright Shashidhar Madiwal, 2006. All rights reserved.
collection NDLTD
language en_US
format Others
sources NDLTD
topic Composite materials
Drilling
Artificial Neural Network
Electronic dissertations
spellingShingle Composite materials
Drilling
Artificial Neural Network
Electronic dissertations
Madiwal, Shashidhar
Analysis of surface finish in drilling of composites using neural networks
description Composite materials are widely used in the aerospace industry because of their high strength-to-weight ratio. Although they have many advantages, their inhomogeneity and anisotropy pose problems. Because of these properties, machining of composites, unlike conventional metal working, needs more investigation. Conventional drilling of composites is one such field that requires extensive study and research. Among various parameters that determine the quality of a drilled hole, surface finish is of vital importance. The surface finish of a drilled hole depends on speed, feed-rate, material of the work piece, and geometry of the drill bit. This project studied the effect of speed and feed on surface finish and also the optimization of these parameters. Experiments were conducted based on Design of Experiment (DOE) and qualitative verification using Artificial Neural Network (ANN). Relevant behavior of surface finish was also studied. In this project, holes were drilled using a conventional twist drill at different cutting speeds (2,000 to 5,000 rpm) and feed rate was varied from 0.001 to 0.01 ipr for solid carbon fiber laminate (composite material). The other material drilled is BMS 8-276 form 3 (toughened resin system). Also five different drill bits were used to conduct experiments on BMS 8-276 form 3. Speed values were 5,000, 3,000, and 2,000 rpm and feed rates were 0.004, 0.006, and 0.01 ipr. The effect of speed, feed rate, and different drill geometries was analyzed with respect to surface finish in the drilled composites. === Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Mechanical Engineering. === "July 2006." === Includes bibliographic references (leaves 79-81).
author2 Bahr, Behnam
author_facet Bahr, Behnam
Madiwal, Shashidhar
author Madiwal, Shashidhar
author_sort Madiwal, Shashidhar
title Analysis of surface finish in drilling of composites using neural networks
title_short Analysis of surface finish in drilling of composites using neural networks
title_full Analysis of surface finish in drilling of composites using neural networks
title_fullStr Analysis of surface finish in drilling of composites using neural networks
title_full_unstemmed Analysis of surface finish in drilling of composites using neural networks
title_sort analysis of surface finish in drilling of composites using neural networks
publishDate 2007
url http://hdl.handle.net/10057/566
work_keys_str_mv AT madiwalshashidhar analysisofsurfacefinishindrillingofcompositesusingneuralnetworks
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