scholarly journals Optimization of Injection Molding Parameters for HDPE/TiO2 Nanocomposites Fabrication with Multiple Performance Characteristics Using the Taguchi Method and Grey Relational Analysis

Materials ◽  
2016 ◽  
Vol 9 (8) ◽  
pp. 710 ◽  
Author(s):  
Hifsa Pervez ◽  
Mohammad Mozumder ◽  
Abdel-Hamid Mourad
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Relational Analysis ◽  
Grey Relational

Optimization of Cutting Parameters of Multiple Performance Characteristics in End Milling of AlSi/AIN MMC – Taguchi Method and Grey Relational Analysis

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
S. H. Tomadi ◽  
J. A. Ghani ◽  
C. H. Che Haron ◽  
M. S. Kasim ◽  
A. R. Daud
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Volume Fraction ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Grey Relational

The main objective of this paper is to investigate and optimize the cutting parameters on multiple performance characteristics in end milling of Aluminium Silicon alloy reinforced with Aluminium Nitride (AlSi/AlN MMC) using Taguchi method and Grey relational analysis (GRA). The fabrication of AlSi/AlN MMC was made via stir casting with various volume fraction of particles reinforcement (10%, 15% and 20%). End milling machining was done under dry cutting condition by using two types of cutting tool (uncoated & PVD TiAlN coated carbide). Eighteen experiments (L18) orthogonal array with five factors (type of tool, cutting speed, feed rate, depth of cut, and volume fraction of particles reinforcement) were implemented. The analysis of optimization using GRA concludes that the better results for the combination of lower surface roughness, longer tool life, lower cutting force and higher material removal could be achieved when using uncoated carbide with cutting speed 240m/min, feed 0.4mm/tooth, depth of cut 0.3mm and 15% volume fraction of AlN particles reinforcement. The study confirmed that with a minimum number of experiments, Taguchi method is capable to design the experiments and optimized the cutting parameters for these performance characteristics using GRA for this newly develop material under investigation.

Multiple Performance Optimization in the Wire EDM Process of SKD61 Tool Steel Using Taguchi Grey Relational Analysis and Fuzzy Logic

2014 ◽  
Vol 493 ◽  
pp. 523-528 ◽  
Author(s):  
Nuraini Lusi ◽  
Bobby Oedy Pramoedyo Soepangkat ◽  
Bambang Pramujati ◽  
H.C. Kis Agustin
Keyword(s):  
Fuzzy Logic ◽  
Taguchi Method ◽  
Tool Steel ◽  
Grey Relational Analysis ◽  
Performance Characteristics ◽  
Relational Analysis ◽  
The Wire ◽  
Grey Relational ◽  
Wedm Process ◽  
Different Levels

This paper propose the optimization of the wire electrical discharge machining (WEDM) process of SKD61 tool steel (AISI H13). The use of the Taguchi method combined with grey relational analysis and fuzzy logic has been applied for optimization of multiple quality characteristics. The WEDM machining parameters (arc on time, on time, open voltage, off time and servo voltage) were optimized with considerations of multiple performance characteristics, i.e., MRR, SR and kerf. Arc on time was set at two different levels while the other four were set at three different levels. Based on Taguchi method, an L18mixed-orthogonal array was chosen for the experiments. Experimental results have shown that machining performance characteristics of WEDM process can be improved effectively through the combination of Taguchi method and grey-fuzzy logic.

scholarly journals Analysis of injection molding for computer cooling fans by Taguchi method and grey relational analysis

Filomat ◽  
2016 ◽  
Vol 30 (15) ◽  
pp. 4199-4211
Author(s):  
Chi-Hung Lo
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Operating Conditions ◽  
Influential Factor ◽  
Injection Molding Process ◽  
Melt Temperature ◽  
Relational Analysis ◽  
Grey Relational

Various factors affect the quality of a plastic product during the injection molding process. In this study, the quality engineering planning method, Taguchi Method, and grey relational analysis were used in this study to determine these factors and the Moldflow Plastics Insight (MPI) was used to conduct the moldflow analysis. By varying different types of operating conditions, the results obtained from the experiments were analyzed so as to verify the influence of each factor on the quality of the final product. The optimal processing parameters which can reduce the mold tryout time and the analysis cost were then determined. The plastic impeller of a computer cooling fan is selected as the case study and the goal is to resolve the warping problems. The deviations in the shear stress distribution as obtained by varying the S/N ratio of variance factors during the experiments are in agreement with the results of analyzing the grey information relational degrees. The most influential factor is the mold temperature, followed sequentially by the fill time, fill pressure, and melt temperature.

scholarly journals Grey Relational Analysis to Determine the Optimum Process Parameters for Open-End Spinning Yarns

2012 ◽  
Vol 7 (2) ◽  
pp. 155892501200700 ◽  
Author(s):  
Hossein Hasani ◽  
Somayeh Akhavan Tabatabaei ◽  
Ghafour Amiri
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Raw Materials ◽  
Performance Characteristics ◽  
Optimum Process ◽  
Rotor Speed ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

This article focuses on an approach based on the Taguchi method with grey relational analysis for optimizing the process parameters for open-end spun yarns with multiple performance characteristics. A grey relational grade obtained from the grey relational analysis is used to optimize the process parameters. Optimal process parameters can then be determined by the Taguchi method using the grey relational grade as the performance index. CVm%, hair number per meter, and tenacity of yarn were selected as quality characteristics. Using these characteristics, the process parameters, including rotor speed, rotor diameter, opener speed, yarn linear density and navel type are optimized. The raw materials used in this investigation were cotton fibers (35%) and cotton waste (65%) collected from ginning machines. The Experimental results show parameter rotor speed has the most significant effect on the multiple performance characteristics.

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