View in EDS HTML Full Text PDF Full Text

A Fuzzy Logic-Based Prediction Model for Kerf Width in Laser Beam Machining.

Saved in:
Bibliographic Details
Title: A Fuzzy Logic-Based Prediction Model for Kerf Width in Laser Beam Machining.
Authors: Hossain, Anamul1 (AUTHOR), Hossain, Altab1 (AUTHOR) altab75@um.edu.my, Nukman, Y.1,2 (AUTHOR), Hassan, M. A.1,2 (AUTHOR), Harizam, M. Z.1 (AUTHOR), Sifullah, A. M.1 (AUTHOR), Parandoush, P.1 (AUTHOR)
Source: Materials & Manufacturing Processes. 2016, Vol. 31 Issue 5, p679-684. 6p.
Subjects: Fuzzy logic, Laser beam cutting, Carbon fiber-reinforced plastics, Prediction models, Polymethylmethacrylate
Abstract: In laser beam machining, the main concern is the machining quality as kerf width of the end product. It is essential for industrial applications to cut the workpiece with minimum kerf width. However, it is difficult to develop a precise functional relationship between input and output variables in laser machining. Therefore, an effort has been conducted to build up an intelligent fuzzy expert system (FES) model to predict the kerf width in CO2laser cutting. The employed input parameters were assisting gas pressure, laser power, cutting speed, and standoff distance. The fuzzy logic was performed on fuzzy toolbox in MATLAB R2009b by employing Mamdani technique. In total, 81 experiments were carried out and experimental results were used for training and testing of the developed fuzzy model. Relative error and goodness of fit were used to investigate the accuracy of the prediction ability and the values of 3.852% and 0.994, respectively, were found to be satisfactory. This paper will extend knowledge about the prediction of kerf width by using FES model. [ABSTRACT FROM PUBLISHER]
Copyright of Materials & Manufacturing Processes is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 111999483
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A Fuzzy Logic-Based Prediction Model for Kerf Width in Laser Beam Machining.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hossain%2C+Anamul%22">Hossain, Anamul</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hossain%2C+Altab%22">Hossain, Altab</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> altab75@um.edu.my</i><br /><searchLink fieldCode="AR" term="%22Nukman%2C+Y%2E%22">Nukman, Y.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hassan%2C+M%2E+A%2E%22">Hassan, M. A.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Harizam%2C+M%2E+Z%2E%22">Harizam, M. Z.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Sifullah%2C+A%2E+M%2E%22">Sifullah, A. M.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Parandoush%2C+P%2E%22">Parandoush, P.</searchLink><relatesTo>1</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Materials+%26+Manufacturing+Processes%22">Materials & Manufacturing Processes</searchLink>. 2016, Vol. 31 Issue 5, p679-684. 6p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+beam+cutting%22">Laser beam cutting</searchLink><br /><searchLink fieldCode="DE" term="%22Carbon+fiber-reinforced+plastics%22">Carbon fiber-reinforced plastics</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction+models%22">Prediction models</searchLink><br /><searchLink fieldCode="DE" term="%22Polymethylmethacrylate%22">Polymethylmethacrylate</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: In laser beam machining, the main concern is the machining quality as kerf width of the end product. It is essential for industrial applications to cut the workpiece with minimum kerf width. However, it is difficult to develop a precise functional relationship between input and output variables in laser machining. Therefore, an effort has been conducted to build up an intelligent fuzzy expert system (FES) model to predict the kerf width in CO2laser cutting. The employed input parameters were assisting gas pressure, laser power, cutting speed, and standoff distance. The fuzzy logic was performed on fuzzy toolbox in MATLAB R2009b by employing Mamdani technique. In total, 81 experiments were carried out and experimental results were used for training and testing of the developed fuzzy model. Relative error and goodness of fit were used to investigate the accuracy of the prediction ability and the values of 3.852% and 0.994, respectively, were found to be satisfactory. This paper will extend knowledge about the prediction of kerf width by using FES model. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Materials & Manufacturing Processes is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=111999483
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/10426914.2015.1037901
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 6
        StartPage: 679
    Subjects:
      – SubjectFull: Fuzzy logic
        Type: general
      – SubjectFull: Laser beam cutting
        Type: general
      – SubjectFull: Carbon fiber-reinforced plastics
        Type: general
      – SubjectFull: Prediction models
        Type: general
      – SubjectFull: Polymethylmethacrylate
        Type: general
    Titles:
      – TitleFull: A Fuzzy Logic-Based Prediction Model for Kerf Width in Laser Beam Machining.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Hossain, Anamul
      – PersonEntity:
          Name:
            NameFull: Hossain, Altab
      – PersonEntity:
          Name:
            NameFull: Nukman, Y.
      – PersonEntity:
          Name:
            NameFull: Hassan, M. A.
      – PersonEntity:
          Name:
            NameFull: Harizam, M. Z.
      – PersonEntity:
          Name:
            NameFull: Sifullah, A. M.
      – PersonEntity:
          Name:
            NameFull: Parandoush, P.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: 2016
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-print
              Value: 10426914
          Numbering:
            – Type: volume
              Value: 31
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: Materials & Manufacturing Processes
              Type: main
ResultId 1