scholarly journals Multiobjective Optimization of Injection Moulding Process Parameters on Mechanical Properties Using Taguchi Method and Grey Relational Analysis

2018 ◽  
Vol 7 (3.7) ◽  
pp. 14 ◽  
Author(s):  
Mohd Amran Md Ali ◽  
Noorfa Idayu ◽  
Raja Izamshah ◽  
Mohd Shahir Kasim ◽  
Mohd Shukor Salleh ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Injection Moulding ◽  
Cooling Time ◽  
Mould Temperature ◽  
Plastic Part ◽  
Melt Temperature ◽  
Relational Analysis ◽  
Grey Relational

This study presents an optimization of injection moulding parameters on mechanical properties of plastic part using Taguchi method and Grey Relational Analysis (GRA) approach. The orthogonal array with L9 was used as the experimental design. Grey relational analysis for ultimate tensile strength, modulus and percentage of elongation from the Taguchi method can convert optimization of the multiple performance characteristics into optimization of a single performance characteristic called the grey relational grade (GRG). It is found that mould temperature of 62oC, melt temperature of 280oC, injection time of 0.70s and cooling time 15.4s are found as the optimum process setting. Furthermore, ANOVA result shows that the cooling time is the most influenced factor that affects the mechanical properties of plastic part followed by mould temperature and melt temperature.  

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.

Robust Process Design towards through-Silicon via Quality Improvement Based on Grey-Taguchi Method

2012 ◽  
Vol 217-219 ◽  
pp. 2183-2186
Author(s):  
Chao Wei Tang ◽  
Li Chang Chuang ◽  
Hong Tsu Young ◽  
Mike Yang ◽  
Hsueh Chuan Liao
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Chemical Etching ◽  
Through Silicon Via ◽  
Relational Analysis ◽  
Wet Chemical ◽  
Wet Chemical Etching ◽  
Etching Parameters ◽  
Grey Relational ◽  
Grey Taguchi

The robust design of chemical etching parameters is dealing with the optimization of the through-silicon via (TSV) roundness error and TSV lateral etching depth in the etching of silicon for laser drilled TSVs. The considered wet chemical etching parameters comprise the HNO3 molarity, HF molarity, and etching time. Grey-Taguchi method is combining the orthogonal array design of experiments with Grey relational analysis (GRA), which enables the determination of the optimal combination of wet chemical etching parameters for multiple process responses. The concept of Grey relational analysis is to find a Grey relational grade, which can be used for the optimization conversion from a multiple objective case to a single objective case. Also, GRG is used to investigate the parameter effects to the overall quality targets.

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.

scholarly journals Tribological Performance Optimization of Al-7.5% SiCp Composites Using the Taguchi Method and Grey Relational Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Shouvik Ghosh ◽  
Prasanta Sahoo ◽  
Goutam Sutradhar
Keyword(s):  
Taguchi Method ◽  
Metal Matrix Composite ◽  
Matrix Composite ◽  
Grey Relational Analysis ◽  
Metal Matrix ◽  
Friction And Wear ◽  
Tribological Performance ◽  
Relational Analysis ◽  
Test Parameters ◽  
Grey Relational

The present study considers an experimental study of tribological performance of Al-7.5% SiCp metal matrix composite and optimization of tribological testing parameters based on the Taguchi method coupled with grey relational analysis. A grey relational grade obtained from grey relational analysis is used as a performance index to study the behaviour of Al-7.5% SiCp MMC with respect to friction and wear characteristics. The tribological experiments are carried out by utilizing the combinations of tribological test parameters based on the L27 Taguchi orthogonal design with three test parameters, namely, load, speed, and time. The material Al-7.5% SiCp metal matrix composite is developed by reinforcing LM6 aluminium alloy with 7.5% (by weight) SiC particle of 400 mesh size (~37 μm) in an electric melting furnace. It is observed that sliding time has a significant contribution in controlling the friction and wear behaviour of Al-7.5% SiCp MMC. Furthermore, all the interactions between the parameters have significant influence on tribological performance. A confirmation test is also carried out to verify the accuracy of the results obtained through the optimization problem. In addition, a scanning electron microscopy (SEM) test is performed on the wear tracks to study the wear mechanism.

Mechanical Behaviour of Polylactic Acid Parts Fabricated via Material Extrusion Process: A Taguchi-Grey Relational Analysis Approach

2020 ◽  
Vol 46 ◽  
pp. 32-44
Author(s):  
Peter Kayode Farayibi ◽  
Babatunde Olamide Omiyale
Keyword(s):  
Mechanical Properties ◽  
Tensile Strength ◽  
Impact Strength ◽  
Layer Thickness ◽  
Polylactic Acid ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Extrusion Temperature ◽  
Relational Analysis ◽  
Grey Relational

The acceptance and application of functional parts produced via additive manufacturing technologies is faced with challenges of poor surface finish, dimensional accuracy and mechanical properties among other which is mostly dependent on process parameters employed. In this study, the effect of infill density, layer thickness and extrusion temperature on mechanical properties of polylactic acid (PLA) part manufactured using fused deposition modelling process was investigated to obtain optimum process parameters to achieve the best properties. Solid cuboid bars were produced from which tensile, impact and hardness test specimens were obtained. A statistical approach based on Taguchi design of experiment was employed with process parameters varied and grey relational analysis coupled with principal component analysis was employed to obtain the unified optimum parameter. The single optimisation results showed that 50% infill density, 220°C extrusion temperature and 0.4 mm layer thickness resulted in best tensile strength; 30% density, 210°C temperature and 0.2 mm layer thickness is required to achieve the best impact strength, while 50% density, 215°C temperature and 0.3 mm thickness is required for highest hardness. The multi-response optimisation indicated that for the best of all the three properties to be achieved at once in a PLA built part, 50% infill density, 220°C extrusion temperature and 0.3 mm is required which yielded tensile strength of 30.02±2.15 MPa, impact strength 4.20±0.12 J and hardness of 76.80±0.38 BHN.

Sign in / Sign up

Export Citation Format

Share Document