Parameter Optimization of a Five-Axis Tool Grinder Using Grey Relational Analysis

2010 ◽  
Vol 458 ◽  
pp. 246-251 ◽  
Author(s):  
Jenn Yih Chen ◽  
Bean Yin Lee
Keyword(s):  
Grey Relational Analysis ◽  
End Mill ◽  
Relational Analysis ◽  
Control Factors ◽  
Planning And Design ◽  
End Mills ◽  
Optimal Values ◽  
Inspection Machine ◽  
Grey Relational ◽  
Five Axis

This paper uses the grey relational analysis to find the optimal values of parameters of the servo drives and the controller of a five-axis CNC tool grinder in order to improve precision of grinding and accuracy of end mills. The experimental planning and design are based on the Taguchi method. There are totally six control factors in the experiments, and each factor has three levels. An L18 orthogonal array was applied for the experiments, and each experiment was repeated three times. The grey relational approach was then employed to find the optimal values to the drives and the controller. These values were utilized for grinding a ball nose end mill of cemented tungsten carbide with two-flute and 6 mm in outside diameter. Finally, a well-known tool measuring and inspection machine was used to measure the geometric parameters of the end mill for the initial design and the optimal design. Experimental results show that the grinding time is reduced up to 6.02 ％, and the precision of the ball nose end mill is also improved. Thus, the results demonstrate the effectiveness of the proposed approach.

Quasi-Optimal Parameter Design of Five-Axis Tool Grinders Based on Taguchi Method

2011 ◽  
Vol 697-698 ◽  
pp. 521-524
Author(s):  
Jenn Yih Chen ◽  
Bean Yin Lee ◽  
Z.H. Huang
Keyword(s):  
Optimal Parameter ◽  
Parameter Design ◽  
Tool Geometry ◽  
Control Factors ◽  
End Mills ◽  
Machine Interface ◽  
Optimal Values ◽  
Inspection Machine ◽  
Parameter Values ◽  
Five Axis

In order to improve precision of grinding as well as accuracy of ball nose end mills, the Taguchi approach was adopted to figure out quasi-optimal parameter values of the XYZ axes drives and the controller for a five-axis tool grinder. Firstly, the backlash and pitch errors of the transmission system and rotational axes were measured via a laser interferometer, and these errors were compensated by setting compensation values on a human machine interface of the controller. Four control factors with three levels and an L9 orthogonal array were used in the experiments, and each experiment was repeated three times. Next, this parameter design was applied to obtain quasi-optimal values of the drives and the controller, and further a tool grinder was employed to grind five ball nose end mills to confirm the practicability. Finally, a tool measuring and inspection machine was utilized to measure the tool geometry of each end mill for the initial and optimal designs. Experimental results were shown to indicate the considerable improvement of the accuracy of the end mills and demonstrate the effectiveness of our proposed scheme.

Modeling and multi response optimization of mechanical properties for E-glass/polyester composite using Taguchi-grey relational analysis

2020 ◽  
pp. 095440892096259
Author(s):  
Phaneendra Kumar Kopparthi ◽  
Vengal Rao Kundavarapu ◽  
Venkata Rao Kaki ◽  
Bhaskara Rao Pathakokila
Keyword(s):  
Mechanical Properties ◽  
Grey Relational Analysis ◽  
Composite Laminates ◽  
Injection Pressure ◽  
Relational Analysis ◽  
Control Factors ◽  
Resin Injection ◽  
Polyester Composite ◽  
Response Optimization ◽  
Grey Relational

In the present work, E-glass/polyester composite laminates were manufactured in a customized resin transfer mould (RTM) with different layers of fiber at selected resin injection pressures. Experiments were performed employing full factorial design to study the influence of number of fiber layers and resin injection pressure on mechanical properties of the composites. Analysis of variance was implemented to study the interaction effect of process parameters on multi-responses namely tensile, flexural and impact strengths. Taguchi method based grey relational analysis was used to determine optimal control factors for the responses. Numbers of fiber layers and the injection pressure have significance with respective 73.96% and 16.57% contributions on the grey relation grades of the three responses. An optimal working condition was suggested to produce quality composite. In addition, mathematical models for the mechanical properties were also developed using the experimental results.

Optimization of Reaming Process Parameters for Titanium Ti-6Al-4V Alloy Using Grey Relational Analysis

2016 ◽  
Author(s):  
Shakeel Ahmed L. ◽  
Pradeep Kumar M.
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Research Work ◽  
Cutting Temperature ◽  
Cutting Speed ◽  
Factors Affecting ◽  
Significant Control ◽  
Relational Analysis ◽  
Control Factors ◽  
Grey Relational

Reaming is one of the finishing processes that have been widely applied in manufacturing industries. Reaming of Titanium Ti-6Al-4V alloy material is an important and current research topic on manufacturing processes. Optimal process parameter setting is an important element in the machinability study of Titanium Ti-6Al-4V alloy. Optimization has most significant importance, particularly for reaming operations. This research work focuses on the multi-response optimization of reaming process parameters using the Taguchi and Grey relational technique to obtain minimum cutting temperature (T), thrust force (Ft), torque (Mt), surface roughness (Ra) and hole quality. The experiments were performed on Titanium Ti-6Al-4V alloy using uncoated carbide straight shank reamer under wet and cryogenic LN2 conditions. Eighteen experimental runs (L18) based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The environment, cutting speed and feed rate were selected as control factors. Grey relational analysis was used to determine the most significant control factors affecting the output parameters. Grey relational grade obtained from the grey relational analysis was used to solve the reaming process with the optimal levels of the multiple performance characteristics responses were established. The optimum results indicate that the reaming results have been improved in wet coolant than the cryogenic LN2 condition.

Sign in / Sign up

Export Citation Format

Share Document