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| Title: | Development of Man-Machine Interface using Matlab: an adaptive network-based fuzzy inference system modeling for laser machining |
| Authors: | Sivarao
Rizal, M.S.
Tajul, A.
Taufik |
| E-mail: | sivarao@live.utem.edu.my |
| Keywords: | Laser Machining
Man-Machine Interface
Human-machine systems
Adaptive Network-based Fuzzy Inference System (ANFIS)
Human-machine systems -- Design and construction |
| Issue Date: | 11-Oct-2009 |
| Publisher: | Universiti Malaysia Perlis |
| Citation: | p.4B5 1 - 4B5 8 |
| Series/Report no.: | Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2009) |
| Abstract: | Development of GUI on MATLAB environment is
rarely carried out by researchers especially for controlling complex and non-linear machining processes. Hence, it becomes more complicated and time consuming for one to
explore artificial intelligent tools to model a process using MATLAB due to unfamiliarity and phobia of programming.
In this paper, how GUI is developed and integrated to model laser machining process using Adaptive Network-based Fuzzy
Inference System (ANFIS) together with GUI’s ability in generating the model output is presented. Laser cutting machine is widely known for having the most number of
controllable parameters among the advanced machine tools and it becomes more difficult for the process to be engineered into desired responses such as surface roughness and kerf
width to achieve precision machining conditions. Knowing
both laser processing and ANFIS programming are difficult
and being fear of modelers, a novel GUI is developed and used
as an interface to model laser processing using ANFIS with
various setting capabilities where, numeric and graphical
output can be printed. On the other hand, the GUI can also be
used to predict the responses to conduct comparative analysis.
To validate the accuracy of the ANFIS modeling, the error is
calculated through Root Mean Square Error (RMSE) and
Average Percentage Error. The RMSE values are compared
with various type of trained variables and settings on ANFIS
platform, so that the best ANFIS model can be finalized before
prediction. The developed GUI can be used in industry of laser
machining for an operator to optimize the best machine setting
before the machine is operated. Thus, the industry could
reduce the production cost and down time by off-hand setting
as compared to the traditional way of trial and error method. |
| Description: | Organized by School of Mechatronic Engineering (UniMAP) & co-organized by The Institution of Engineering Malaysia (IEM), 11th - 13th October 2009 at Batu Feringhi, Penang, Malaysia. |
| URI: | http://hdl.handle.net/123456789/7388 |
| Appears in Collections: | Conference Papers
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