학술논문

Development and Application of an Intelligent System to Predict and Optimize the Surface Roughness of 1018 and 4140 Steel
Document Type
Conference
Source
2008 Electronics, Robotics and Automotive Mechanics Conference (CERMA '08) Electronics, Robotics and Automotive Mechanics Conference, 2008. CERMA '08. :33-38 Sep, 2008
Subject
Components, Circuits, Devices and Systems
Robotics and Control Systems
Steel
Machining
Surface roughness
Rough surfaces
Artificial neural networks
Surface treatment
Optimization
neural network
machining parameters
surface roughness
random search
hill climbing
Language
Abstract
The aim of this research is to present a new methodology for predicting and optimizing the surface roughness during machining of 1018 and 4140 Steel. There is particular interest in finding the best machining value parameters that should be used to achieve good surface roughness. These parameter values can be found by this neural intelligent approach. This methodology analyzes and identifies the parameters involved in the machining process; with this information the model is able to predict the surface roughness value in different conditions and then optimize the results with different intelligent heuristics. The experimental results show that we may conclude that this intelligent system is a suitable methodology for predicting and optimizing surface roughness during the machining of 1018 and 4140 Steel.