Optimising injection moulding parameters that satisfies part qualities by using Taguchi method

For many years, injection molding is adopted as the most suitable manufacturing process in the production of complex plastic components. It is very difficult to boost the product's quality stability to attain a higher forming speed and higher automation in the injection moulding process because the process often disrupted by numerous inevitable deviations. The settings for different process parameters and machine parameters have quite a major influence on the overall product quality and its performance of the injection moulding process, which shows the final product quality as output responses. Identifying the perfect process parameter settings so that numerous responses may be optimized at almost the same time is becoming a significant research challenge these days. Smart manufacturing is at the heart of the new industrial revolution, and it will continue to be the primary means of transforming and upgrading the manufacturing industry in the upcoming decades. Melt temperature, the temperature of mould, injection pressure, and velocity of molten polymer while injection, injection time, pressure of molten polymer while holding into the mold cavity, holding time of molten polymer, and cooling time are the variety of input process parameters.  While mechanical characteristics, flaws such as warpage, volumetric or dimensional shrinkage, sink mark on outer surface, residual stress, and surface finish/roughness are examples of responses. To study and optimize the molding process, researchers have used a wide range of methods. Mathematical modeling, simulation, design of experiments, Taguchi methodology, analysis of variance - ANOVA, response surface methodology - RSM, evolutionary algorithm (EA), artificial neural networks - ANN, genetic algorithms - GA, fuzzy logic, particle swarm optimization - PSO, are examples of these techniques. This paper presents a review of the numerous strategies that used till date for optimizing the key injection moulding parameters, as well as their benefits and challenges. In the review, it is discovered that a perfect injection molding process, which takes care of overall quality control is still being researched upon. The process parameters involved in injection molding, required response, and the methodologies used for optimization of overall injection molding process are discussed throughout this paper.

The application of Taguchi method to reduce warpage in an injection moulding process is studied. The objective of this paper is to analyze the effect of injection moulding parameters, i.e., injection time, packing time, melt temperature and mould temperature, on the warpage defect in dumbbell plastics part. Optical comparator horizontal type was used to measure the difference of warpage value on each part. L9 orthogonal array with 3 replications was done with 27 totals of specimens. The result collected was optimized using Taguchi method and percentage of contribution was calculated using analysis of variance (ANOVA). According to the analysis, it is found that the significant factors affected warpage are injection time (32.01%), packing time (29.73%), mould temperature (24.39%) and melt temperature (13.87%). The optimum parameters for minimizing the warpage were injection time (1s), packing time (5s), melt temperature (270 °C) and the mould temperature (21 °C). By using Taguchi method and ANOVA analysis, optimum parameters and the percentage of contribution of parameters can be obtained. Thus, it shows that design of experiment method is the good quality tools to get the best quality for production.

Micropowder injection molding (μPIM) is a potential low-cost process for the mass production of metal or ceramic microstructures. In order to obtain good molded microstructures and to avoid molding defects, it is important to select suitable injection molding parameters. In this paper, the selection of injection molding conditions for the production of 316L stainless steel microstructures by μPIM is presented. Silicon mold inserts with 24 × 24 microcavities were injection molded on a conventional injection molding machine. The dimensions of each microcavity were Φ 100 μ m × depth 200 μm, giving an aspect ratio of 2. The distance between each microcavity was 200 μm. Five sets of experiments were conducted by varying one injection molding parameter at a time. The parameters included injection pressure, holding pressure, holding time, mold temperature, and melt temperature. Higher injection pressure and holding pressure were required during the injection molding process due to the small dimensions of the microcavities and the large number of microcavities (576 microcavities). High mold temperature was required for complete filling of the microcavities. Molded microstructures without visual defects were obtained using appropriate injection molding parameters. Catalytic debinding and sintering of the 316L stainless steel microstructures were successfully conducted.

This Paper Presents the Optimization of Injection Molding Conditions to Minimize the Warpage and Volumetric Shrinkage Using Design of Experiments and Taguchi Optimization Method. Considering the Process Parameters such as Injection Time, Packing Pressure, Packing Pressure Time, and Cooling Time, a Series of Mold Analysis are Performed. Orthogonal Arrays of Taguchi, the Signal-to-Noise(S/N) and Analysis of Variance (ANOVA) are Utilized to Determine the Optimization Parameter Levels and to Find out Principal Processing Parameters on Warpage and Volumetric Shrinkage. from the Results it is Clear that Warpage and Volumetric Shrinkage are Reduced. also, the Dominant Parameters were Cooling Time and Packing Time for Warpage, on the other Hand, the most Important Factor for Shrinkage was Injection Time. from this, it can be Concluded that Taguchi Method is very Suitable to Solve the Warpage and Volumetric Shrinkage Problems in Injection Molding Parts.

This study optimized the influence of process parameters on the mechanical properties during injection molding (IM) of PC/ABS blend. The Taguchi method of design of experiments (DOE) was employed to optimize the process parameters and to increase the tensile strength and the elasticity module. Taguchi’s L9 (34) orthogonal array design was employed for the experimental plan. Process parameters of the injection molding such as material temperature, injection pressure, holding time, and mold temperature were studied with three levels. The Signal to noise (S/N) ratio for mechanical properties of PC/ABS blend using the Taguchi method was calculated. Taguchi’s results proposed two sets of optimal injection parameters conditions to achieve the best mechanical characteristics (σ, E). The (S/N) ratio results proved that the injection pressure was the more prominent than the other IM process parameters for the tensile strength, and the material temperature was the more prominent for the elasticity module.

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.

In this study, a mold is designed in single and dual type of gate in order to investigate the deflection of warpage for thick component in injection molding process. Autodesk Moldflow Insight software was used as a medium for experimental tested. Nessei NEX 1000 injection molding machine and P20 mold material details were entered in this study to get more accurate data on top of Acrylonitrile Butadiene Styrene (ABS) as a molded thermoplastic material. Taguchi orthogonal array, analysis of Signal to Noise (S/N) ratio and Analysis of Variance (ANOVA) were implemented to get the best combination of parameter and significant factor that affect the warpage problem for both types of gates. Coolant inlet temperature, melt temperature, packing pressure and packing time are the selected parameter that used in this study. A conformation test is conducted to verify the combination parameters optimized. From the result, multi gates used was founded that can decrease the deflection of warpage for thick product. From ANOVA, the most significant factor is melt temperature for single gate, and coolant inlet temperature for multi gate. Packing pressure and packing time were slightly influence on warpage problem for both studies.

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.

Multi Response optimization of injection moulding Process parameters to reduce cycle time and warpage

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.

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.

Todays, there are various of optimisation methods that have been studied by many researchers in order to find the appropriate combination of processing parameters setting in the injection moulding process. From the previous literatures, the optimisation works have been proven will improve the moulded part quality. In this study, the application of optimisation work to improve warpage of front panel housing has been explored. By selecting cooling time, coolant temperature, packing pressure and melt temperature as the variable parameters, design of experiment (DOE) have been constructed by using the rotatable central composite design (CCD) approach. Response Surface Methodology (RSM) was performed in order to define the optimal processing parameters setting which will optimise the warpage condition. Based on the results, melt temperature is the most significant factor contribute to the warpage condition and warpage have optimised by 47.1% after optimisation. The findings show that the application of optimisation work offers the best quality of moulded part produced.

For the installation of a fuel cell stack to convert chemical energy into electricity it is common to apply bipolar plates to separate and distribute reaction gases and cooling agents. For reducing manufacturing costs of bipolar plates a fully automated injection molding process is examined. The high performance thermoplastic matrix material, polyphenylene sulfide (PPS), defies against the chemical setting and the operation temperature up to 200 °C. To adjust also high electrical and thermal conductivity, PPS is highly filled with various carbon fillers up to an amount of 65 percentage by volume. In the first step two different structural plates (one-sided) with three different gate heights and molds are designed according to the characteristics of a bipolar plate. To cope with the approach that this plate should be producible on standard injection molding machines with variothermal mold temperature control, injection molding simulation is used. Additionally, the simulation should allow to formulate a quality prediction model, which is transferrable to bipolar plates. Obviously, the basis for a precise simulation output is an accurate description of the material properties and behavior of the highly filled compound. This, the design of the structural plate and mold and the optimization via simulation is presented, as well. The influence of the injection molding process parameters, e.g. injection time, cycle times, packing pressure, mold temperature, and melt temperature on the form filling have been simulated to determine optimal process conditions. With the aid of the simulation and the variothermal mold temperature control it was possible to reduce the required melt temperature below the decomposition temperature of PPS. Thereby, hazardous decomposition products as hydrogen sulfide are obviated. Thus, the health of the processor, the longevity of the injection molding machine as well as the material and product properties can be protected.

Grey-based taguchi method for multi-weld quality optimization of gas metal arc dissimilar joining of mild steel and 316 stainless steel

Defect minimization is important in any injection molding process in order to ensure the quality of the injected part or product. The aims of the present study are to determine the optimum processing parameters and to identify the most significant factor during the injection molding process for the lamp holder via Taguchi method. The numerical simulation analysis of injection molding process was carried out by software. The set of numerical simulation for different parameters was designed by L18 Orthogonal array. Six process parameters were considered, which are melting temperature, injection time, cooling time, filling time, injection pressure and filling pressure. The main response of the study is volumetric shrinkage. Main effect and ANOVA analysis were also highlighted in this study. Filling pressure and melting temperature are the most significant factor in the injection molding process of the lamp holder. The present study revealed the setting of process parameters (i.e., 334 °C melting temperature, 0.16 s of injection time, cooling time with 50, 20 s of filling time, 18.65 MPa of injection pressure and 90 MPa of filling pressure) yield the optimum quality of the lamp holder.KeywordsSimulation and modelingInjection moldingTaguchi method