Metal injection molding (MIM) is a novel process classified in powder metallurgy. This process can produce complex metallic parts with high rate of production and consists of four stages, including mixing, injection, debinding, and sintering, where the properties of the final part highly depends on the parameters of each of these stages. In this study, the parameters of injection pressure, injection and mold temperature, holding pressure, holding time, injection speed, and cooling time on the density, strength, and hardness of the final MIM compact have been investigated. By the design of experiments and response surface methodology (RSM) method, 50 samples have been injected using different parameters. In order to measure the density, tensile strength, ad hardness of the samples, the debinding and sintering procedures have been done on the injected samples. The results show that the injection pressure, injection temperature, and mold temperature have the highest effect on the strength and density of the final part, respectively, and on the other hand, holding pressure, holding time, and cooling time have a negligible effect. Within the measured properties, density and strength are more affected by the injection parameters compared to hardness. Finally, the optimum injection parameters for samples made of 4605 low alloy steel include injection pressure of 133 bar, injection temperature of 158oC, mold temperature of 60oC, the holding pressure of 70 bar, holding time of 8 second, injection speed of 112 mm/min, and cooling cycle of 17 second.

Extrusion, injection molding, calendaring, and thermoforming are just a few of the processing techniques utilized in the plastics industry. Gas-assist injection molding plays a crucial role in this equipment. The advancement of standard injection molding is represented by this apparatus. Parts with thin wall thickness and hollow sections can be manufactured using this method. Use this strategy to save between 30% and 35% of the material. In this procedure, gas is first introduced after a brief shot of material is injected. The remaining portion of the cavity is filled in by injecting gas. The hollow section is described in detail by the gas core. In gas-assist injection molding, the geometry of the gas channel design is also very important. There is a wide variety of materials available for polymeric applications. Different polyamide materials, including polypropylene, polycarbonate, high-impact polystyrene, and polyethylene terephthalate (PET), can be processed using gas-assisted injection molding. Talc-filled polypropylene has been chosen for this study's simulation and experimental work. For simulation purposes, Moldflow plastic insight is utilized. Moldflow plastic insight was used to simulate the tensile samples, and gas-assist injection molding was used to create the experimental models. Simulation and experimental results are used to measure the wall thickness and gas penetration depth. The validation was then checked by comparing these results.

Product quality for plastic injection molding process is highly related with the settings for its process parameters. Additionally, the product quality is not simply based on a single quality index, but multiple interrelated quality indices. To find the settings for the process parameters such that the multiple quality indices can be simultaneously optimized is becoming a research issue and is now known as finding the efficient frontier of the process parameters. This study considers three quality indices in the plastic injection molding: war page, shrinkage, and volumetric shrinkage at ejection. A digital camera thin cover is taken as an investigation example to show the method of finding the efficient frontier. Solidworks and Moldflow are utilized to create the part’s geometry and to simulate the injection molding process, respectively. Nine process parameters are considered in this research: injection time, injection pressure, packing time, packing pressure, cooling time, cooling temperature, mold open time, melt temperature, and mold temperature. Taguchi's orthogonal array L27 is applied to run the experiments, and analysis of variance is then used to find the significant process factors with the significant level 0.05. In the example case, four process factors are found significant. The four significant factors are further used to generate 34 experiments by complete experimental design. Each of the experiments is run in Moldflow. The collected experimental data with three quality indices and four process factors are further used to generate three multiple regression equations for the three quality indices, respectively. Then, the three multiple regression equations are applied to generate 1,225 theoretical datasets. Finally, data envelopment analysis is adopted to find the efficient frontier of the 1,225 theoretical datasets. The found datasets on the efficient frontier are with the optimal quality. The process parameters of the efficient frontier are further validated by Moldflow. This study demonstrates that the developed procedure has proved a useful optimization procedure that can be applied in practice to the injection molding process.

The present work reports and discusses the results of a 3D simulation of the injection molding process of a rubber compound that includes the mold filling stage and material curing, using the computer code is developed in "UDF" part of the Fluent 6.3 CAE software. The data obtained from a rheometer (MDR 2000) is used to characterize the rubber material in order to find the cure model parameters which exist in curing model. Because of non-newtonian behavior of rubber, in this work the non-newtonian model for viscosity was used and viscosity parameters were computed by mean of viscometry test by RPA. After calculation of the physical and curing properties, vulcanization process was simulated for a complex rubber article with non-uniform thickness by solving the continuity, momentum, energy and curing process equations. Predicted filling and curing time in a complex and 3D rubber part is compared with experimentally measured data which confirmed the accuracy and applicability of the method.

Statement of Problem: Despite the fact that polymethyl methacrylate is the most popular material in denture base construction, one of its main defects is the polymerization shrinkage that frequently leads in time consuming clinical problems. Several ways have been suggested to solve this problem; among them is "injection molding method".Purpose: The purpose of this study was the assessment of dimensional accuracy of the two acrylic resins cured by injection molding method.Materials and Method: In this experimental study, the dimensional accuracy of two acrylic resins after curing by injection molding method (Unipress system) was assessed by profile projector measurement. Twenty master casts were made of a master dye simulating both maxillary and mandibular edentulous arch. They were divided in two groups, each group containing 10 casts used for making denture bases. Three reference points were determined, one in the central incisor region and the other two symmetrical points in the posterior region in molar area. Three measurements were made: 1. on the master cast, 2. on the denture base just after removing the denture base from the master cast, and 3. after immersion in water for one week. The measurements were analyzed using Friedman and Mann- Whitney tests.Results: All the denture bases in both groups, revealed significant shrinkage after removing from casts (p<0.05). After immersion in water, there was no significant dimensional change (p>0.05) in any of the groups. Statistical analysis revealed no significant difference between the two acrylic resins too.Conclusion: Since there was no significant difference between dimensional accuracy of the two acrylic resins, it could be conclude that using Bayer acrylic resin with Unipress injection molding system would lead in acceptable results concerning dimensional accuracy.

Objective: Acrylic resin denture bases undergo dimensional changes during polymerization. Injection molding techniques are reported to reduce these changes and thereby improve physical properties of denture bases. The aim of this study was to compare dimensional changes of specimens processed by conventional and injection-molding techniques.Materials and Methods: SR-Ivocap Triplex Hot resin was used for conventional pressure-packed and SR-Ivocap High Impact was used for injection-molding techniques. After processing, all the specimens were stored in distilled water at room temperature until measured. For dimensional accuracy evaluation, measurements were recorded at 24-hour, 48-hour and 12-day intervals using a digital caliper with an accuracy of 0.01 mm. Statistical analysis was carried out by SPSS (SPSS Inc., Chicago, IL, USA) using t-test and repeated-measures ANOVA. Statistical significance was defined at P<0.05.Results: After each water storage period, the acrylic specimens produced by injection exhibited less dimensional changes compared to those produced by the conventional technique. Curing shrinkage was compensated by water sorption with an increase in wa-ter storage time decreasing dimensional changes.Conclusion: Within the limitations of this study, dimensional changes of acrylic resin specimens were influenced by the molding technique used and SR-Ivocap injection procedure exhibited higher dimensional accuracy compared to conventional molding.

In injection molding manufacturing, selection of the optimal machine from various alternatives is a crucial strategy for enhancing productivity, cost-effectiveness, and maintaining performance standards. This article presents an approach that combines two techniques to make the best choice from three presented options. Firstly, it employs the Analytic Hierarchy Process method to determine the weights of five main criteria and eleven sub-criteria, considering both cost and performance. Secondly, it utilizes the Technique for Order Preference by Similarity to Ideal Solution to rank the three machines by comparing each machine's performance against ideal and anti-ideal solutions to determine their relative suitability. The final model is validated through three distinct scenarios, illustrating how key criteria such as cost breakdown and scrap rate can influence the ultimate selection ranking. Through a presented numerical example, the paper provides decision-makers with a scientifically robust decision support system, aiding in strategic and complex decision-making processes for selecting the most suitable machine.

In this article, Low-Pressure Injection Molding (LPIM) method was investigated as a method for forming zirconia (zirconium oxide) parts. It is one of the methods used for manufacturing engineering ceramics with complex shapes & high dimensional accuracy. In this method, a binder composition (paraffin & industrial waxes) is used as the plasticizing agent to shape zirconia particles. Different parameters such as temperature, pressure & injection time, mold temperature, etc. have been found to be effective in shaping the ceramic parts based on this method. Throughout this research, these parameters were examined, & their optimal values were obtained. The optimal injection temperature was in the range of 80-90 Celsius degree, injection pressure in the range of 3-5 bar, & injection time in the range of 10-15 seconds to form a crucible with the size of 130×85×75 mm (height×internal diameter×external diameter). This study also examined the FESEM images of the microstructure of parts in the injected, debonded, & sintered bodies. According to the findings, the zirconia crucible in this article shows notable similarity with the crucible made by Zircoa company with the code 3001 in terms of physical properties such as bulk density & apparent porosity.