Application of the Grey-Taguchi Method to the Optimization of Metal Injection Molding (MIM) Process

2010 ◽  
Vol 443 ◽  
pp. 63-68 ◽  
Author(s):  
Khairur Rijal Jamaludin ◽  
Norhamidi Muhamad ◽  
Mohd Nizam Ab. Rahman ◽  
Sufizar Ahmad ◽  
Mohd Halim Irwan Ibrahim ◽  
...  
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Mold Temperature ◽  
Parameter Design ◽  
Metal Injection Molding ◽  
Quality Performance ◽  
Surface Appearance ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Grey Taguchi

The Grey-Taguchi method was adopted in this study to optimize the injection molding parameters for the MIM green compacts with multiple quality performance. A Grey relational grade obtained from the Grey relational analysis is used as the quality performance in the Taguchi method. Then, the optimum injection molding parameters are determined using the parameter design proposed by the Taguchi method. The result concluded that the mold temperature (D) is very significant, by the fact that the ANOVA shows its contribution to excellent surface appearance as well as strong and dense green compacts is 38.82%.

Application of Taguchi Method for Parameters Optimization in Micro Metal Injection Molding

2011 ◽  
Vol 52-54 ◽  
pp. 244-248
Author(s):  
Haw Pei Li ◽  
Norhamidi Muhamad ◽  
Abu Bakar Sulong ◽  
Heng Shye Yunn ◽  
Hooman Abolhasani
Keyword(s):  
Injection Molding ◽  
Signal To Noise Ratio ◽  
Steel Powder ◽  
Mold Temperature ◽  
Parameters Optimization ◽  
Simultaneous Optimization ◽  
Metal Injection Molding ◽  
Surface Appearance ◽  
Optimal Injection ◽  
Acetate Butyrate

Optimization of injection parameters in Micro Metal Injection Molding (μMIM) was described in this study. Stainless steel powder was mixed with Polyethelena Glycol (PEG), Polymethyl Methacrilate (PMMA) and Cellulose Acetate Butyrate (CAB) to produce feedstock. Design of Experiments (DOE) of Taguchi L-27 (313) orthogonal array technique has been used to investigate the significance and optimal injection molding parameters. The signal-to-noise ratio and analysis of variance (ANOVA) are applied to study the optimum levels and effects of process parameters. Simultaneous optimization to obtain the highest green density and excellent surface appearance was discussed. The result concluded that the mold temperature (D) is the most statistically significant process parameter and its contribution to the best appearance and density is the highest.

Optimizing the Sintering Parameter of Metal Injection Molding Compact Using Robust Engineering Technique

2012 ◽  
Vol 445 ◽  
pp. 357-361
Author(s):  
Khairur Rijal Jamaludin ◽  
Norhamidi Muhamad ◽  
Sufizar Ahmad ◽  
Mohd Halim Irwan Ibrahim ◽  
Nor Hafiez Mohd Nor ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Injection Molding ◽  
Quality Characteristics ◽  
Metal Injection Molding ◽  
Sintered Part ◽  
Multiple Quality Characteristics ◽  
Sintering Time ◽  
Engineering Technique ◽  
Grey Relational Grade ◽  
Grey Relational

Sintering is a key step in the metal injection molding (MIM) process, which affects the mechanical properties of the sintered part. The mechanical properties of the sintered compacts are resulted from tremendous sintered part densification. This work utilizes robust engineering technique in optimizing sintering parameters of metal injection molding compacts. Three quality characteristics; shrinkage, density and flexure strength is optimized using Taguchi method-based grey analysis. The modified algorithm adopted here was successfully used for both detraining the optimum setting of the process parameters and for combining multiple quality characteristics into one integrated numerical value called grey relational grade. The sintering parameters investigated are: sintering temperature, sintering time, and heating rate. The result concluded that sintering time is the most significant for the combination of the quality characteristics.

Optimization of Micro Metal Injection Molding By Using Grey Relational Grade

2011 ◽  
Author(s):  
M. H. I. Ibrahim ◽  
N. Muhamad ◽  
A. B. Sulong ◽  
N. H. M. Nor ◽  
K. R. Jamaludin ◽  
...  
Keyword(s):  
Injection Molding ◽  
Metal Injection Molding ◽  
Grey Relational Grade ◽  
Grey Relational

scholarly journals Application of entropy measurement technique in grey based Taguchi method for optimization of MIG welding process parameters

1970 ◽  
Vol 8 (3) ◽  
pp. 13-26
Author(s):  
Rani Jatav ◽  
Vedansh Chaturvedi
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Measurement Technique ◽  
Welding Process ◽  
Quality Characteristic ◽  
Mig Welding ◽  
Entropy Measurement ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Grey Taguchi

We seldom realized that without this form of metal work, many structures would cease to be in existence. A skilled journeymen welder joins metal in such a way that it is not able to be parted unless it is cut. Welding is an absolutely essential technique used in various industries like automotive industry, construction industry as well as in the aviation industry. Hence welding process parameters are required to be optimized for their responses or welding characteristics. This study incorporates entropy measurement technique based on grey Taguchi method to analyze multiple quality characteristic optimization of metal inert gas welding of low carbon steel plates. For this study, four control variables are selected current, voltage, gas flow rate and wire feed rate and analysing their effect on the four quality characteristics ultimate tensile strength, elongation %, bending strength and hardness of the weldments have been investigated in this paper. In order to optimize the multiple quality characteristic of the MIG welding, grey relational analysis coupled with entropy measurement method has been employed. Using entropy measurement method, value of weight corresponding to each quality characteristic has been assigned, so that the importance can be properly determined. Using the theory of grey relational analysis, these have been accumulated to calculate the overall grey relational grade. Signal to Noise ratio (S/N ratio) is applied to find the optimal parameter setting. To determine the contribution of MIG welding process parameters, Analysis of variance (ANOVA) on grey relational grade has been calculated. The confirmatory test also has been done for verifying the results. A foresaid methodology has been found fruitful in the cases where simultaneous optimization of huge number of responses is required.Keywords: Metal Inert Gas (MIG) Welding, Grey-Taguchi Method, Entropy Measurement Technique, Analysis of variance (ANOVA), S-N ratio.

Optimization of Micro Metal Injection Molding SS 316L for the Highest Green Strength by Using Taguchi Method

2011 ◽  
Vol 264-265 ◽  
pp. 135-140 ◽  
Author(s):  
Mohd Halim Irwan Ibrahim ◽  
Norhamidi Muhamad ◽  
Abu Bakar Sulong ◽  
Khairur Rijal Jamaludin ◽  
Nor Hafiez Mohamad Nor ◽  
...  
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Injection Pressure ◽  
Rheological Characteristic ◽  
Mold Temperature ◽  
Metal Injection Molding ◽  
Small Scale ◽  
Injection Time ◽  
Green Strength ◽  
Injection Temperature

Micro metal injection molding which is a new develop technology has attract most researcher where it becomes among the promising method in powder metallurgy research to produce small-scale intricate part at an effective process and competitive cost for mass production. Due to highly stringent characteristics of micro MIM feedstock,the study has been emphasized in investigating the optimization of highest green strength which plays an important characteristic in determining the successful of micro MIM. Stainless steel SS 316L with D50 = 5.96μm was used with composite binder, which consists of PEG, PMMA and Stearic Acid. From rheological characteristic and highly significant parameter through screening experiment, feedstock with 61.5% with several injection parameters were optimized such as injection pressure(A), injection temperature(B), mold temperature(C), injection time(D) and holding time(E). Besides that, interaction effects between injection pressure, injection temperature and mold temperature were also considered to optimize in the Taguchi’s orthogonal array. Analysis of variance (ANOVA) in terms of signal-to-noise ratio (S/N-larger is better) for green strength was also presented in this paper. Result shows that interaction between injection temperature and mold temperature(BxC) give highest significant factor followed by interaction between injection pressure and injection temperature(AxB). Single factor that also contributes to significant optimization are mold temperature(C), injection time(D) and injection pressure(A). This study shows that Taguchi method would be among the best method to solve the problem with minimum number of trials.

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.

scholarly journals Multi-objective optimization of ciprofloxacin antibiotic removal from an aqueous phase with grey taguchi method

2018 ◽  
Vol 16 (4) ◽  
pp. 530-541 ◽  
Author(s):  
M. Salari ◽  
G. R. Rakhshandehroo ◽  
M. R. Nikoo
Keyword(s):  
Taguchi Method ◽  
Grey Relational Analysis ◽  
Water Soluble ◽  
H2o2 Concentration ◽  
Multi Objective Optimization ◽  
Anova Analysis ◽  
Multi Objective ◽  
Relational Analysis ◽  
Grey Relational ◽  
Grey Taguchi

Abstract Optimization methods are used to study and survey the optimal values for input factors and effect of optimized parameters on response variables. In this study, the effect of different factors on ciprofloxacin (CIP) removal of water soluble was studied. In this regard, a multi-objective optimization was performed utilizing the Taguchi method based on a grey relational analysis. Optimum levels of factors were determined to optimize three responses simultaneously with grey Taguchi. Meanwhile, grey relational analysis was applied to model and optimize three target responses, namely, CIP removal, chemical oxygen demand (COD) removal, and sludge to iron ratio. Multi-objective optimization results obtained based on grey relational analysis showed that the optimal value of the input factors were CIP concentration of 100 mg/L, H2O2 concentration of 100 mM, Fe(II) concentration of 10 mM, pH of 3, and a reaction time of 15 min. To confirm the results, the values obtained through a confirmation test were examined. Multi-objective optimization results from process factors were determined by analysis of variance (ANOVA) analysis and grey Taguchi method. Based on ANOVA analysis for the grey relational grade, Fe(II) concentration and H2O2 concentration were found to be the most influencing factors.

Characterization of Micro Metal Injection Molding by Using PMMA & PEG

2013 ◽  
Vol 315 ◽  
pp. 992-996
Author(s):  
Mohd Halim Irwan Ibrahim ◽  
Norhamidi Muhamad ◽  
A.B. Sulong
Keyword(s):  
Stainless Steel ◽  
Injection Molding ◽  
Injection Pressure ◽  
Steel Powder ◽  
Mold Temperature ◽  
Point Of View ◽  
Metal Injection Molding ◽  
Volume Percentage ◽  
Shape Retention ◽  
Injection Temperature

Due to its versatility, micro metal injection molding has become an alternative method in powder metallurgy where it can produce small part with a minimal number of waste. The success of micro MIM is greatly influenced by feedstock characteristics. This paper investigated the characterization and optimization which both of them plays an important characteristic in determining the successful of micro MIM. In this paper, stainless steel SS 316L was used with composite binder, which consists of PEG (Polyethelena Glycol), PMMA (Polymethyl Methacrilate) and SA (Stearic Acid). The rheology properties are investigated using Shimadzu Flowtester CFT-500D capillary rheometer. The geometry of water atomised stainless steel powder are irregular shape, therefore it is expected significant changes in the rheological results that can influence the microcomponent, surface quality, shape retention and resolution capabilities. From rheological characteristics, feedstock with 61.5% shows a significant value with several injection parameters were optimized through screening experiment such as injection pressure (A), injection temperature (B), mold temperature (C), injection time (D) and holding time (E). Besides that, interaction effects between injection pressure, injection temperature and mold temperature were also considered to optimize in the Taguchis orthogonal array. Result shows that 61.5%vol contributes a significant stability over a range of temperature and the best powder loading from a critical powder volume percentage (CPVP) and rheological point of view. Furthermore interaction between injection temperature and mold temperature (BxC) give highest significant factor followed by interaction between injection pressure and mold temperature (AxC).

Multi Response Optimization of the Hole Punching Process Parameters in the Leaf Spring Assembly Using the Grey Taguchi Method and Simulated Annealing Algorithm

2011 ◽  
Vol 110-116 ◽  
pp. 1691-1695
Author(s):  
Gopalsamy Gopalaramasubramaniyan ◽  
Ke Zhu
Keyword(s):  
Taguchi Method ◽  
Process Parameters ◽  
Simulated Annealing Algorithm ◽  
Leaf Spring ◽  
Experimental Procedure ◽  
Grey Relational Grade ◽  
Response Optimization ◽  
Annealing Algorithm ◽  
Punching Process ◽  
Grey Relational

This paper presents an attempt to develop an approach to predict the optimal process parameters for the Hole punching process on sheet metal. The Taguchi method is used to define the experimental procedure by its orthogonal array. The multiple responses of the Hole punching process, hole diameter and hole offset are optimised by the Grey Relational Analysis procedure. The statistical analysis of variance reveals the significant parameters which affect the process by analyzing the input parameters with the grey relational grade. The Non linear model obtained by this analysis is further processed by a Meta heuristic algorithm to obtain the optimality.

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