Journal ArticleDOI
Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments
TLDR
In this article, a neural network modeling approach is presented for the prediction of surface roughness (Ra) in CNC face milling using the Taguchi design of experiments (DoE) method.Abstract:
In this paper, a neural network modeling approach is presented for the prediction of surface roughness (Ra) in CNC face milling The data used for the training and checking of the networks’ performance derived from experiments conducted on a CNC milling machine according to the principles of Taguchi design of experiments (DoE) method The factors considered in the experiment were the depth of cut, the feed rate per tooth, the cutting speed, the engagement and wear of the cutting tool, the use of cutting fluid and the three components of the cutting force Using feedforward artificial neural networks (ANNs) trained with the Levenberg–Marquardt algorithm, the most influential of the factors were determined, again using DoE principles, and a 5×3×1 ANN based on them was able to predict the surface roughness with a mean squared error equal to 186% and to be consistent throughout the entire range of valuesread more
Citations
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Experimental investigation of high speed milling of aluminium alloy
TL;DR: In this paper, the influence of tool geometry (helix angle) and cutting conditions (cutting velocity, and feed rate) on the surface finish produced during high speed milling of aluminium alloy have been investigated.
Journal ArticleDOI
Optimization of end milling parameters for rough and finish machining of Al-4032/3%SiC metal matrix composite
Pardeep Saini,Pradeep K. Singh +1 more
Journal ArticleDOI
Developing an Evolving Multi-Layer Perceptron Network by genetic algorithm to predict Full-Scale Municipal Wastewater Treatment Plant Effluent
TL;DR: In this paper , a hybrid intelligent model was proposed to develop near-optimal MLP to simulate the non-linear WWTP processes and provide an accurate monitoring tool for managers to increase the resilience of WWTPs.
Journal ArticleDOI
Taguchi-Based Grey Relation Optimization of Machining Parameters and Cutting Path Strategies in CNC Pocket Milling Operations
TL;DR: In this paper, the authors focused on the Taguchi-based multi-response optimization of the pocket milling process for an optimal parametric combination to yield minimum surface roughness within a minimization of the roughness.
Journal ArticleDOI
Surface finish of additively manufactured Ti6Al4V workpieces after ball end milling
TL;DR: In this article, the machinability characteristics of additively manufactured Ti6Al4V titanium alloy workpieces in finishing machining using ball end mills on 45° inclined surfaces were investigated.
References
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Book
Taguchi techniques for quality engineering
TL;DR: Taguchi as discussed by the authors presented Taguchi Techniques for Quality Engineering (TQE), a technique for quality engineering in the field of high-level geometry. Technometrics: Vol. 31, No. 2, pp. 253-255.
Journal ArticleDOI
A Mechanistic Model for the Prediction of the Force System in Face Milling Operations
Journal ArticleDOI
An in-process surface recognition system based on neural networks in end milling cutting operations
TL;DR: In this paper, an in-process surface recognition system was developed to predict the surface roughness of machined parts in the end milling process to assure product quality and increase production rate by predicting the surface finish parameters in real time.
Journal ArticleDOI
On-line prediction of surface finish and dimensional deviation in turning using neural network based sensor fusion
Riadh Azouzi,Michel Guillot +1 more
TL;DR: In this paper, the authors examined the feasibility of an intelligent sensor fusion technique to estimate on-line surface finish (Ra) and dimensional deviations (DD) during machining and presented a systematic method for sensor selection and fusion using neural networks.
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