GUI Based Mamdani Fuzzy Inference System Modeling To Predict Surface Roughness in Laser Machining

Sivarao, Subramonian (2009) GUI Based Mamdani Fuzzy Inference System Modeling To Predict Surface Roughness in Laser Machining. International Journal of Electrical & Computer Sciences, 9 (9). pp. 281-287. ISSN 2077-1231

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Abstract

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 carried out by screening for the significant parameters before the explicit GUI is designed. Next, the GUI for Fuzzy based modeling has been developed using GUIDE and Fuzzy Toolbox in MATLAB. The fuzzy variables were also analyzed before finalizing the significant of its variables. The developed GUI has been programmed to interact with fuzzy variables in order to model the laser processing cut quality of two different thicknesses, 2.5 and 5.0 mm. The models were then compared for their statistical validation by Root Mean Square Error (RMSE). 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 improve cut quality of its end product.

Item Type:	Article
Subjects:	T Technology > TJ Mechanical engineering and machinery
Divisions:	Faculty of Manufacturing Engineering > Department of Manufacturing Process
Depositing User:	Assoc. Pror. Ir. Dr. Sivarao Subramonian
Date Deposited:	13 Aug 2013 15:40
Last Modified:	28 May 2015 04:02
URI:	http://eprints.utem.edu.my/id/eprint/9172
Statistic Details:	View Download Statistic

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