Khairur Rijal Jamaludin

Parameter Optimization towards Highest Micro MIM Density by Using Taguchi Method

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.

Parameter optimization of injection molding Ti-6Al-4V powder and palm stearin binder system for highest green density using Taguchi method

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.

Rheological Investigation of Water Atomized Metal Injection Molding (MIM) Feedstock for Processibility Prediction

This paper presents the rheological properties of SS316L water atomized MIM feedstock. Coarse and fine SS316L water atomized powder is mixed with a composite binder consisting of PMMA and PEG to form a homogenous paste, termed as feedstock. The feedstock is loaded with SS316L water atomized powder ranging 62 v/o, 62.5 v/o, 63 v/o, 63.5 v/o and 64 v/o. However, due to the morphology of the water atomized powder which is not spherical compared to the gas atomized ones, fine powder feedstock is unable to produce any significant rheological result due to the powder loading being more than 63.5 v/o. Results show that the fine powder feedstock demonstrates a higher viscosity if compared to the coarse powder feedstock. It can be established that binder separations are likely to occur in the coarse powder feedstock, especially, at high temperatures. The investigation concludes that the fine powder feedstock has its best rheological properties at 62 v/o while the coarse powder feedstock lies between 63 v/o and 63.5 v/o.

A hybrid methodology for the mahalanobis-taguchi system using random binary search-based feature selection

The Mahalanobis-Taguchi system (MTS) is a relatively new statistical methodology combining various mathematical concepts and is used in the field of diagnosis and classification in multidimensional systems. MTS is a very efficient method and has already been applied to a wide range of disciplines. However, its feature selection phase (optimization stage), which uses experimental designs (orthogonal array, OA), is susceptible to improvement. In MTS, selection of important features or variables to improve classification accuracy is done using signal-to- noise (S/N) ratios and OA. OA has been noted for limitations in handling a large number of variables. Therefore, in this research, we propose the use of a random binary search (RBS) algorithm incorporated within MTS for optimizing the procedure for selecting the most useful variables. Ensemble is a powerful technique to achieve improvement in the accuracy of predictive models, whereby individual methods, which are not consistently the best performers in different problems and datasets, are brought together to provide predictions which are more accurate than those made by individual methods.

Design of ultrasonic compaction tool for powder metallurgy

The current study is presented into the investigation of the application of ultrasonic vibration on the lower punch during compaction process of powder metallurgy material. The lower punch is specifically designed of ultrasonic horn which has been tuned at frequency of 20 kHz and vibrates in longitudinal mode. Finite Element modeling was used to assist the design process of the lower punch or horn. The horn was fabricated using high grade aluminium alloy and mounted onto the ultrasonic system test rig and subsequently tested prior the experimental process begins. Various static and ultrasonic compaction procedures have been carried out to confirm the capability of the tool to operate. The compaction force was reduced significantly at the onset of ultrasonic vibration applied compared to without ultrasonic.

Injection molding parameter optimization of Ti-6Al-V powder mix with palm stearin and polyethylene for highest green strength using taguchi method

Taguchi method of L27 (313) orthogonal array is used in this paper as a tool in optimization of Metal injection molding (MIM) parameters for the highest green strength. 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 metal powder of Ti‐6Al‐4V is mixed with binder 60wt% of palm stearin and 40wt% of polyethylene successfully injected at optimum parameter condition: 350 bar of injection pressure, 140° C of injection temperature, 65vol% of powder loading, 50° C of mold temperature, 600 bar of holding pressure, and 10 ccm/s of the injection rate. Analysis of variance (ANOVA) for the best signal to noise ratio (S/N) presents the contribution of the parameters to the quality characteristic (green strength). Results show that the mold temperature has highest significant percentage (27.59%) followed by powder...

Characterisation of titanium alloy feedstock for metal injection moulding using palm stearin binder system

Metal injection moulding (MIM) is a cost-effective technique for producing small, complex, precision parts in high volume. Each step in MIM process plays a vital role in order to achieve high quality final product. To have a good understanding of the MIM process and successful in manufacturing, characterisation of the material feedstock is essential. This paper presents the characterization of MIM feedstock consisting titanium alloy (Ti-6Al-4V) powder mix with binder 60 wt% of palm stearin and 40 wt% polyethylene. The characterisation of Ti-6Al-4V alloy powder, binders and feedstock includes scanning electron micrograph (SEM), thermo gravimetric analysis (TGA), differential scanning calorimeter (DCS) and rheological test were established. Rheological results exhibited pseudoplastic or shear thinning flow behaviour, where its viscosity decreased with increasing shear rate. The feedstock viscosity also decreased with increasing temperature and was found to be suitable for moulding.

Finite element modelling in ultrasonic sheet metal forming

Finite element (FE) model of die necking process of an aluminium hollow thin cylinder has been developed. The input parameters of material properties and coefficient of friction, µ for the model have been deducted from our previous experimental study. Later the models have been validated against experimental data as reported in the previous studies. For the die necking process, the FE model has successfully to predict how much the original diameter of the aluminium hollow cylinder can be maximised necked with and without applying ultrasonic vibration. FE models showed that the application of ultrasonic vibration during the necking process has reduced buckling of the cylinder body if compared to the necking process without ultrasonic. The benefit of applying ultrasonic vibration in sheet metal forming process has been related to the reduction of interface friction between die and specimen.

Ball Milling of WC-Co Powder as Injection Molding Feedstock

In this paper, an attempt has been made to mill constituent of WC and Co powder towards achieving volumetric percentage of WC (91%) and Co (9%). The ball milling technique was conducted under dry and wet condition using various milling parameters, rotation speed, time and ethanol as milling medium. Electron dispersive spectrometer (EDS) detected the elemental distribution, whilst SEM and particle size analysis was done to study the effect of changes in particle morphology and reduction of particle size. As a conclusion, powder milled by parameter of wet milling by ethanol, speed of rotation at 250 rpm and 90 minutes of milling time exhibits best results in term of volumetric percentage of 91%WC and 9%Co and particle size reduction.

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

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%.