Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining

The world of manufacturing has shifted its level to the era of space age machining. The purpose of this investigation is to develop Fuzzy based Graphical User Interface (GUI) for modeling of laser machining conditions. The developed fuzzy based GUI is expected to overcome the major problems faced by...

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Main Author: Sivarao, Subramonian
Format: Article
Language:English
Published: Engineering Technology Press 2009
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Online Access:http://eprints.utem.edu.my/id/eprint/9161/1/IJIITA_%282009_-_2%281%29_12-18%29.pdf
http://eprints.utem.edu.my/id/eprint/9161/
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Institution: Universiti Teknikal Malaysia Melaka
Language: English
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spelling my.utem.eprints.91612015-05-28T04:01:55Z http://eprints.utem.edu.my/id/eprint/9161/ Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining Sivarao, Subramonian TJ Mechanical engineering and machinery The world of manufacturing has shifted its level to the era of space age machining. The purpose of this investigation is to develop Fuzzy based Graphical User Interface (GUI) for modeling of laser machining conditions. The developed fuzzy based GUI is expected to overcome the major problems faced by most of the manufacturing industries nowadays with the increased number controllable parameters and the lack of expertise to operate the machine. Investigations were begun by screening for the significant parameters before the design for GUI is made. Then, the GUI for Fuzzy based modeling has been developed using GUIDE Toolbox and Fuzzy Toolbox. The fuzzy variables were also analyzed before finalizing the significant of its variables. The GUI developed has been programmed to interact with fuzzy variables in order to model the laser processing cut quality of two different thicknesses, 2.5 and 5 mm. The models were then compared for their statistical validation by Root Mean Square Error (RMSE) values. Few models with best and optimized variables were taken as prediction models, where their respective outputs were analyzed and compared based on percentage error for 128 data sets to validate the models. The best developed model was then recommended to the pressure vessel manufacturing industry to further reduce the production cost and enhance it end product quality. Engineering Technology Press 2009 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/9161/1/IJIITA_%282009_-_2%281%29_12-18%29.pdf Sivarao, Subramonian (2009) Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining. International Journal of Intelligent Information Technology Application, 2 (1). pp. 12-18. ISSN 1999-2459
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Sivarao, Subramonian
Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining
description The world of manufacturing has shifted its level to the era of space age machining. The purpose of this investigation is to develop Fuzzy based Graphical User Interface (GUI) for modeling of laser machining conditions. The developed fuzzy based GUI is expected to overcome the major problems faced by most of the manufacturing industries nowadays with the increased number controllable parameters and the lack of expertise to operate the machine. Investigations were begun by screening for the significant parameters before the design for GUI is made. Then, the GUI for Fuzzy based modeling has been developed using GUIDE Toolbox and Fuzzy Toolbox. The fuzzy variables were also analyzed before finalizing the significant of its variables. The GUI developed has been programmed to interact with fuzzy variables in order to model the laser processing cut quality of two different thicknesses, 2.5 and 5 mm. The models were then compared for their statistical validation by Root Mean Square Error (RMSE) values. Few models with best and optimized variables were taken as prediction models, where their respective outputs were analyzed and compared based on percentage error for 128 data sets to validate the models. The best developed model was then recommended to the pressure vessel manufacturing industry to further reduce the production cost and enhance it end product quality.
format Article
author Sivarao, Subramonian
author_facet Sivarao, Subramonian
author_sort Sivarao, Subramonian
title Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining
title_short Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining
title_full Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining
title_fullStr Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining
title_full_unstemmed Mamdani Fuzzy Inference System Modeling to Predict Surface Roughness in Laser Machining
title_sort mamdani fuzzy inference system modeling to predict surface roughness in laser machining
publisher Engineering Technology Press
publishDate 2009
url http://eprints.utem.edu.my/id/eprint/9161/1/IJIITA_%282009_-_2%281%29_12-18%29.pdf
http://eprints.utem.edu.my/id/eprint/9161/
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