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.

Parameter Optimization towards Highest Micro MIM Density by Using Taguchi Method

2010 ◽  
Vol 443 ◽  
pp. 705-710 ◽  
Author(s):  
Mohd Halim Irwan Ibrahim ◽  
Norhamidi Muhamad ◽  
Abu Bakar Sulong ◽  
Khairur Rijal Jamaludin ◽  
Nor Hafiez Mohamad Nor ◽  
...  
Keyword(s):  
Taguchi Method ◽  
Signal To Noise Ratio ◽  
Injection Pressure ◽  
Mold Temperature ◽  
Metal Injection Molding ◽  
Small Scale ◽  
Injection Time ◽  
Green Strength ◽  
Minimum Number ◽  
Injection Temperature

Nowadays, micro metal injection molding has become among the promising method in powder metallurgy research to produce small-scale intricate part at an effective process and competitive cost for mass production. This paper investigated the optimization of highest green strength which plays an important characteristic in determining the successful of micro MIM. In this paper, stainless steel SS 316L with D50 = 5.96µm was used with composite binder, which consists of PEG (Polyethelena Glycol), PMMA (Polymethyl Methacrilate) and SA (Stearic Acid). Feedstock with 61.5% with several injection parameters were optimized which highly significant 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 Taguchi’s orthogonal array. Analysis of variance (ANOVA) in terms of signal-to-noise ratio (S/N-larger is better) for green density 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 mold temperature(AxC). Single factor that also contributes to significant optimization are mold temperature(C) and injection time(D). This study shows that Taguchi method would be among the best method to solve the problem with minimum number of trials.

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).

Optimization of Injection Parameters Using 16µm Stainless Steel Powder (SS316L) at 63 Vol. %, 63.5 Vol. % and 64 Vol. % Powder Loading by Taguchi Method for Metal Injection Molding

2011 ◽  
Vol 471-472 ◽  
pp. 558-562 ◽  
Author(s):  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Norhamidi Muhamad ◽  
Mohd Fazuri Abdullah ◽  
Che Hassan Che Haron
Keyword(s):  
Stainless Steel ◽  
Injection Molding ◽  
Surface Quality ◽  
Injection Pressure ◽  
Steel Powder ◽  
Mold Temperature ◽  
Stainless Steel Powder ◽  
Holding Time ◽  
Metal Injection Molding ◽  
Injection Temperature

In this paper, injection molding parameters are optimized using the L18 Taguchi orthogonal array for mechanical strength and surface quality of the green part. The feedstock used consists of stainless steel powder (SS316L) with the powder loading of 63 vol. %, 63.5 vol. % & 64 vol. %. The binder compositions used are polyethelene glycol (PEG-73 wt.%), polymethyl methacrilate (PMMA-25 wt.%) and stearic acid (4 wt.%). Mould temperature, injection temperature, injection pressure, injection time, holding time and powder loading ware selected as signal factors using Taghuci’s method based on literature, where these parameters were significant in MIM. Results showed that the optimum parameters are: mold temperature at 650C, injection temperature at1450C, injection pressure at 650 bar, injection flow rate at 20 m3/s, holding time at 5 s and powder loading of 64 vol.%. Analysis of Variance (ANOVA) result shown that mold temperature is the most influence in order to produce good green part’s surface quality while powder loading give the best result for green part’s strength.

Parameter Optimization of Injection Molding Ti-6Al-4V Powder and Palm Stearin Binder System for Highest Green Density Using Taguchi Method

2010 ◽  
Vol 443 ◽  
pp. 69-74 ◽  
Author(s):  
Nor Hafiez Mohamad Nor ◽  
Norhamidi Muhamad ◽  
Sufizar Ahmad ◽  
Mohd Halim Irwan Ibrahim ◽  
Mohd Ruzi Harun ◽  
...  
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Injection Pressure ◽  
Palm Stearin ◽  
Quality Characteristic ◽  
Metal Injection Molding ◽  
Green Density ◽  
Injection Speed ◽  
Pressure Injection ◽  
Injection Temperature

In this paper, the titanium alloy powder of Ti-6Al-4V is mixed with binder 60wt% of palm stearin and 40wt% of polyethylene for metal injection molding (MIM) process. Injection molding parameters has been optimized using Taguchi method of L27 (313) orthogonal array. Highest green density has been identified as the green part quality characteristic or as an output for this study. Parameters optimized are the injection pressure, injection temperature, powder loading, mold temperature, holding pressure and injection speed. Besides those, interaction of the injection pressure, injection temperature and powder loading were studied. The analysis of variance (ANOVA) is employed to determine the significant levels (α) and contributions of the variables to the green density. Results show that the injection pressure has highest significant percentage followed by injection temperature, powder loading and holding pressure.

Optimization of 67% Powder Loading Co-30Cr-6Mo µMIM Part by Taguchi Method

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
Azizah Wahi ◽  
Norhamidi Muhamad ◽  
Hafizawati Zakaria
Keyword(s):  
Taguchi Method ◽  
Injection Moulding ◽  
Injection Pressure ◽  
Palm Stearin ◽  
Mold Temperature ◽  
Powder Injection ◽  
Injection Time ◽  
Powder Injection Moulding ◽  
Micro Parts ◽  
Injection Temperature

This research studies the effect of injection moulding parameters on the density of green body of Cobalt-30Chromium-6Molybdenum (Co-30Cr-6Mo) for powder injection moulding (PIM) feedstock. In this paper 20 micron Co-Cr-Mo powder was mixed with a palm stearin and polyethylene binder system. L18 orthogonal array by Taguchi Method was used to optimize and predict the future performance. Several injection parameters were optimized such as injection temperature, holding pressure, injection temperature, and mould temperature and injection time. The result shows that the optimum combination of these parameters will produce higher density micro parts. The optimum parameters for 67% powder loading of 20µm Co-30Cr-6Mo powder is 180oC injection temperature, while injection pressure, mold temperature, packing time and injection time are 10 bar, 100oC, 5 s and 7 s respectively.

scholarly journals Green Strength Optimization in Metal Injection Molding Applicable with a Taguchi Method L9 (3)4

2015 ◽  
Vol 773-774 ◽  
pp. 115-117 ◽  
Author(s):  
N. Mustafa ◽  
Mohd Halim Irwan Ibrahim ◽  
Rosli Asmawi ◽  
Azriszul Mohd Amin ◽  
S.R. Masrol
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Complex Geometry ◽  
Signal To Noise Ratio ◽  
Injection Pressure ◽  
Cost Effective ◽  
Metal Injection Molding ◽  
Injection Molding Process ◽  
Molding Process ◽  
Green Strength

Recently Metal injection molding is selected as a vital process in producing large amount of small part with complex geometry and intricate shape. This process is lead to solve cost effective issue in manufacturing fields. Feedstock composition behavior categorized as one of impact factor in determines the victories in metal injection molding process. Thus this paper is focused on optimizing the strength of green part by applied Taguchi Method L9 (34) as optimization tools during injection process. The composition of feedstock is 55% powder loading (PL) were injected by injection molding machine .Several injection parameter were optimized such as injection temperature (A), barrel temperature (B), injection pressure (C) and Speed (D) The results analyzed by using Signal to Noise Ratio (S/N ratio) terms. The highest green strength is A2, B2, C2, and D2

scholarly journals Optimization of Process Parameters for Vertical-Faced Polypropylene Bottle Injection Molding

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Youmin Wang ◽  
Zhichao Yan ◽  
Xuejun Shan
Keyword(s):  
Injection Molding ◽  
Process Parameters ◽  
Dwell Time ◽  
Optimization Problem ◽  
Injection Pressure ◽  
Mold Temperature ◽  
Orthogonal Test ◽  
Injection Molding Process ◽  
Injection Time ◽  
Melt Temperature

In order to obtain the optimal combination of process parameters for vertical-faced polypropylene bottle injection molding, with UG, the model of the bottle was drawn, and then, one module and sixteen-cavity injection molding system was established and analyzed using Moldflow. For filling and maintaining pressure during the process of infusion bottle injection molding, the orthogonal test table L25 (56) using CAE was designed for injection molding of the bottle, with six parameters such as melt temperature, mold temperature, injection pressure, injection time, dwell pressure, and dwell time as orthogonal test factors. By finding the best combination of process parameters, the orthogonal experiment was completed, the results were analyzed by range analysis, and the order of influence of each process parameter on each direction of optimization was obtained. The prediction dates of the infusion bottle were gained under various parameters, a comprehensive quality evaluation index of the bottle was formulated, and the multiobjective optimization problem of injection molding process was transformed into a single-objective optimization problem by the integrated weighted score method. The bottle parameters were optimized by analyzing the range date of the weighted scoring method, and the best parameter combination such as melt temperature 200°C, mold temperature 80°C, injection pressure 40 MPa, injection time 2.1 S, dwell pressure 40 MPa, and dwell time 40 S was gained.

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%.

Optimizing Injection Parameters of Kenaf Filler Polypropylene Composite by Taguchi Method

2017 ◽  
Vol 894 ◽  
pp. 81-84 ◽  
Author(s):  
Mohd Khairul Fadzly Md Radzi ◽  
Norhamidi Muhamad ◽  
Abu Bakar Sulong ◽  
Zakaria Razak
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Process Condition ◽  
Injection Pressure ◽  
Poor Quality ◽  
Injection Molding Process ◽  
Molding Process ◽  
Injection Parameters ◽  
Pp Composites ◽  
Injection Temperature

Optimization of injection molding parameters provided a solution to achieve strength improvement of kenaf filler polypropylene composites. Since, molded polymers composites possibility being effected by machine parameters and other process condition that may cause poor quality of composites product. Thus in this study, composite of kenal filler reinforced with thermoplastic polypropylene (PP) were prepared using a sigma blade mixer, followed by an injection molding process. To determine the optimal processing of injection parameters, Taguchi method with L27 orthogonal array was used on statistical analysis of tensile properties of kenaf/PP composites. The results obtained the optimum parameters which were injection temperature 190°C, injection pressure 1300 bar, holding pressure 1900 bar and injection rate 20cm3/s. From the analysis of variance (ANOVA), both flow rate and injection temperature give highest contribution factor to the mechanical properties of the kenaf/PP composites.

Application of Taguchi Method to Improve Resistance Quality of Graphene/Polypropylene Composites

2019 ◽  
Vol 818 ◽  
pp. 118-122
Author(s):  
Ching Been Yang ◽  
Wei Chang Peng ◽  
Yan Wen Huang ◽  
Hsiu Lu Chiang
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Optimal Parameter ◽  
Impact Resistance ◽  
Injection Pressure ◽  
High Impact ◽  
Polypropylene Composites ◽  
Injection Temperature ◽  
New Generation

Polypropylene is a widely used thermoplastic with high impact resistance and strong mechanical properties. Graphene has exhibited in a new generation of electronic component materials owing to its high thermal conductivity and low resistivity. In this study, a composite of graphene and polypropylene for injection molding purposes was created. In Taguchi method, an L9 orthogonal array for injection molding experiments was adopted. The process parameters included injection temperature (A), holding time (B), injection pressure (C), and graphene ratio (D). Optimal parameter combinations were determined according to resistivity, and the results were A3B2C1D3: 2956.333 MΩ by original and A1B2C1D3: 2802 MΩ Taguchi analysis, respectively, where the improvement was 5.2%.

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