scholarly journals Prediction of tangential force and maximum temperature generation at the tool tip using ANFIS model during CNC turning operations for an intricate shape

2017 ◽  
Vol 4 (2) ◽  
pp. 106-102
Author(s):  
Goutam Paul ◽  
Pritam Patra
Keyword(s):  
Tangential Force ◽  
Maximum Temperature ◽  
Anfis Model ◽  
Turning Operations ◽  
Cnc Turning ◽  
Intricate Shape

scholarly journals Shape optimization of turbine blades with the integration of aerodynamics and heat transfer

1998 ◽  
Vol 4 (1) ◽  
pp. 21-42 ◽  
Author(s):  
J. N. Rajadas ◽  
A. Chattopadhyay ◽  
N. Pagaldipti ◽  
S. Zhang
Keyword(s):  
Heat Transfer ◽  
Shape Optimization ◽  
Tangential Force ◽  
Turbine Blades ◽  
Leading Edge ◽  
Optimization Techniques ◽  
Multidisciplinary Optimization ◽  
Heat Transfer Analysis ◽  
Maximum Temperature ◽  
Force Coefficient

A multidisciplinary optimization procedure, with the integration of aerodynamic and heat transfer criteria, has been developed for the design of gas turbine blades. Two different optimization formulations have been used. In the first formulation, the maximum temperature in the blade section is chosen as the objective function to be minimized. An upper bound constraint is imposed on the blade average temperature and a lower bound constraint is imposed on the blade tangential force coefficient. In the second formulation, the blade average and maximum temperatures are chosen as objective functions. In both formulations, bounds are imposed on the velocity gradients at several points along the surface of the airfoil to eliminate leading edge velocity spikes which deteriorate aerodynamic performance. Shape optimization is performed using the blade external and coolant path geometric parameters as design variables. Aerodynamic analysis is performed using a panel code. Heat transfer analysis is performed using the finite element method. A gradient based procedure in conjunction with an approximate analysis technique is used for optimization. The results obtained using both optimization techniques are compared with a reference geometry. Both techniques yield significant improvements with the multiobjective formulation resulting in slightly superior design.

Optimization of CNC Turning Operations with Multiple Performance Characteristics using Taguchi based Grey Relational Analysis

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
P. Lakshmikanthan ◽  
B. Prabu
Keyword(s):  
Analysis Of Variance ◽  
Grey Relational Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Performance ◽  
Turning Operations ◽  
Cnc Turning ◽  
Relational Analysis ◽  
Grey Relational

This study investigates the optimization of CNC turning operation parameters for Al6061 nickel coated graphite (NCG) metal matrix composite using the Taguchi based grey relational analysis method. The turning operations are carried out with carbide cutting tool inserts. According to the Taguchi quality concept, 3-level orthogonal array was chosen for the experiments. The experiments are conducted at three different cutting speeds (125, 175, 225m/min) with feed rates (0.1, 0.15, 0.2mm/rev) and depth of cut (0.5, 1, 1.5mm) and different % of reinforcement (2.5%, 5%, 7.5%), signal to noise ratio and the analysis of variance are used to optimize cutting parameters. The effects of cutting speed, feed rate and depth of cut on surface roughness and MRR are analyzed. Mathematical models are developed by using the response surface method to formulate the cutting parameters experimental results shown that machining performance can be improved effectively by using this approach, the analysis of variance (ANOVA) is applied to identify the most significant factor for the turning operations according to the weighted sum grade of the GRG. The predict responses shows the models have more than 95% of confident level of R2 value, from the obtained confirmation experiment result, it is observed, there is a good agreement between the estimated value and the experimental value of the grey relational grade. This experimental study reveals that the grey-Taguchi and RSM can be applied successfully for multi response characteristic performances.

scholarly journals Prediction Model of Cutting Parameters for Turning High Strength Steel Grade-H: Comparative Study of Regression Model versus ANFIS

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Adel T. Abbas ◽  
Mohanad Alata ◽  
Adham E. Ragab ◽  
Magdy M. El Rayes ◽  
Ehab A. El Danaf
Keyword(s):  
Experimental Data ◽  
Surface Roughness ◽  
Regression Analysis ◽  
High Strength Steel ◽  
Removal Rate ◽  
High Strength ◽  
Cutting Parameters ◽  
Turning Operations ◽  
Cnc Turning ◽  
Accuracy And Repeatability

The Grade-H high strength steel is used in the manufacturing of many civilian and military products. The procedures of manufacturing these parts have several turning operations. The key factors for the manufacturing of these parts are the accuracy, surface roughness (Ra), and material removal rate (MRR). The production line of these parts contains many CNC turning machines to get good accuracy and repeatability. The manufacturing engineer should fulfill the required surface roughness value according to the design drawing from first trail (otherwise these parts will be rejected) as well as keeping his eye on maximum metal removal rate. The rejection of these parts at any processing stage will represent huge problems to any factory because the processing and raw material of these parts are very expensive. In this paper the artificial neural network was used for predicting the surface roughness for different cutting parameters in CNC turning operations. These parameters were investigated to get the minimum surface roughness. In addition, a mathematical model for surface roughness was obtained from the experimental data using a regression analysis method. The experimental data are then compared with both the regression analysis results and ANFIS (Adaptive Network-based Fuzzy Inference System) estimations.

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