Mold filling simulation and experimental investigation of metallic feedstock used in low-pressure powder injection molding

Azzouni, Mohamed; Demers, Vincent; Dufresne, Louis

doi:10.1007/s12289-021-01612-0

Cited by 6 publications

(6 citation statements)

References 26 publications

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“…Autodesk Moldflow Insight 2021 was used for injection molding numerical analysis [26][27][28][29]. Tetrahedral elements were used for the analysis modeling: the total number of elements is approximately 1,162,970.…”

Section: Injection Molding Analysismentioning

confidence: 99%

Optimization of Injection Molding of Automotive Plastic Horn Cover Part Using Taguchi Method and Reverse Engineering

Lee¹,

Cho²,

Han³

2022

Mater. Plast.

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The aim of the paper consisted in the development of an injection mold for plastic horn cover parts in commercial vehicles. Three mold types were designed in anticipation of the structure and quality of molds, and injection molding numerical analyses were conducted for the three types of molds. One mold type was selected in consideration of the resin flow patterns inside the mold, surface quality, and final deflection amount of the horn cover. To perform optimal injection molding using the selected mold, optimization of injection molding parameters was performed using the Taguchi method, one of the designs of experiment (DOE) and ANOVA methods. As a result, it was confirmed that the deflection amount of the molding under optimal molding parameters decreased by about 34.3% compared to the deflection amount before optimization of the molding parameters. Based on these encouraging results, the previously selected mold type was actually manufactured. The horn cover was molded using the obtained optimal injection molding parameters to the manufactured mold. To verify the precision of the molded horn cover, the deflection amount of the molding was measured with a 3D scanner. The deflection amount of the horn cover was estimated to be about 11% to 43% larger for each measurement position than the deflection amounts in the analysis results. The manufactured mold was revised to solve the problem that the deflection amount of the actual molding is larger than the deflection amount predicted by injection molding analysis. The dimensions and surface quality of the horn cover with a revised mold were satisfactory.

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Section: Injection Molding Analysismentioning

confidence: 99%

Optimization of Injection Molding of Automotive Plastic Horn Cover Part Using Taguchi Method and Reverse Engineering

Lee¹,

Cho²,

Han³

2022

Mater. Plast.

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“…Simulations of mold filling, including jetting, filling time, and pressure distribution, were primarily done for ceramic-based feedstocks [85,177] in the LPIM process. However, few numerical models describing the injection stage for metallic-based LPIM feedstocks have been identified in the literature [111,116]. Utilizing injection molding at a temperature of 80 • C and a pressure of 0.6 MPa produced the best results.…”

Section: Simulationmentioning

confidence: 99%

“…However, computational models did not accurately anticipate the halo-shaped segregation pattern evident in the cross-section of the injected parts. In another study for metals, Azzouni et al [111] examined the feasibility of simulating the mold-filling behavior of a 17-4PH stainless steel feedstock with the LPIM using the commercial program Autodesk Moldflow Synergy 2019. Since actual and simulated injections were conducted at a constant volumetric flow, the injected length and melt front velocity were not affected by the feedstock temperature but rather by the geometry of the mold cavity.…”

Section: Simulationmentioning

confidence: 99%

Research Progress on Low-Pressure Powder Injection Molding

et al. 2022

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Powder injection molding (PIM) is a well-known technique to manufacture net-shaped, complicated, macro or micro parts employing a wide range of materials and alloys. Depending on the pressure applied to inject the feedstock, this process can be separated into low-pressure (LPIM) and high-pressure (HPIM) injection molding. Although the LPIM and HPIM processes are theoretically similar, all steps have substantial differences, particularly feedstock preparation, injection, and debinding. After decades of focusing on HPIM, low-viscosity feedstocks with improved flowability have recently been produced utilizing low-molecular-weight polymers for LPIM. It has been proven that LPIM can be used for making parts in low quantities or mass production. Compared to HPIM, which could only be used for the mass production of metallic and ceramic components, LPIM can give an outstanding opportunity to cover applications in low or large batch production rates. Due to the use of low-cost equipment, LPIM also provides several economic benefits. However, establishing an optimal binder system for all powders that should be injected at extremely low pressures (below 1 MPa) is challenging. Therefore, various defects may occur throughout the mixing, injection, debinding, and sintering stages. Since all steps in the process are interrelated, it is important to have a general picture of the whole process which needs a scientific overview. This paper reviews the potential of LPIM and the characteristics of all steps. A complete academic and research background survey on the applications, challenges, and prospects has been indicated. It can be concluded that although many challenges of LPIM have been solved, it could be a proper solution to use this process and materials in developing new applications for technologies such as additive manufacturing and processing of sensitive alloys.

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“…The study demonstrated that the melt front location and filling completion predicted by the numerical model at different short shots were in good agreement with experimental observations. An experimental validation of very low-pressure values simulated from an LPIM feedstock was performed for the first time by Azzouni et al [28] in two simple shape 2D mold cavities. However, an in-situ validation of the pressure values developed within more complex shape mold cavities was never confirmed for such low-viscosity ceramic- or metallic-based feedstocks.…”

Section: Introductionmentioning

confidence: 99%

Mold filling behaviour of LPIM feedstocks using numerical simulations and real-scale injections

Haghniaz,

Delbergue,

Côté

et al. 2023

Powder Metallurgy

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This study aims to compare the flow patterns and in-cavity pressures obtained experimentally and numerically for different conditions. Four feedstocks based on 17-4PH stainless steel powder were fully characterised and implemented as material laws in an Autodesk Moldflow package before to obtain numerical simulations that were then validated using real-scale injections. The flow patterns obtained numerically for the different flat bar mold geometries were in good agreement with the experimental flow patterns, showing an almost perfect fit, whereas for the flow patterns of the complex mold geometry, there were some minor discrepancies. The simulated pressure profiles obtained for different mold geometries, feedstock temperatures, mold temperatures and solid loadings were in good agreement with the experimental pressure profiles in terms of trend and pressure values, with maximum relative differences varying from 30 to 64% depending on particular feedstocks and process parameters.

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Mold filling simulation and experimental investigation of metallic feedstock used in low-pressure powder injection molding

Cited by 6 publications

References 26 publications

Optimization of Injection Molding of Automotive Plastic Horn Cover Part Using Taguchi Method and Reverse Engineering

Optimization of Injection Molding of Automotive Plastic Horn Cover Part Using Taguchi Method and Reverse Engineering

Research Progress on Low-Pressure Powder Injection Molding

Mold filling behaviour of LPIM feedstocks using numerical simulations and real-scale injections

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