Multi‐response optimization of shrinkage, clamp force, and part weight in simulated injection molding process of a dialysis micro‐filter

Heidari, Behzad Shiroud; Bappoo, Nikhilesh; Kelsey, Lachlan J.; Davachi, Seyed Mohammad; Doyle, Barry

doi:10.1002/app.51732

Cited by 7 publications

(3 citation statements)

References 25 publications

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“…[ 155 ] The simulation of injection molding via Autodesk Moldflow also finds applications in the medical area. [ 156 ] Hereby, a multi‐response optimization was performed of an injection molding process for the manufacture of high‐quality dialysis filter. In this investigation, the optimal processing parameters were found by minimizing the shrinkage, part weight, and clamping force.…”

Section: Processing and Fabricationmentioning

confidence: 99%

Application of Digital Methods in Polymer Science and Engineering

Schuett,

Endres,

Standau

et al. 2023

Adv Funct Materials

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The development of new polymer materials is an emerging field for more than 100 years. However, it is currently facing major challenges and the application of digital methods can help to develop new processes, discover new materials and, thus, contribute to the challenges of today and the future. Though, the application of digital methods in the field of polymer science is currently very limited, when compared to other classes of materials such as small molecules or inorganic high‐performance materials. Nevertheless, there are already first, very promising approaches. The current review article focuses on the application of these methods in different aspects of polymer research including polymer design, synthesis, and characterization. Furthermore, the digital discovery of polymer engineering is highlighted in detail showing the broad range of potential applications of these methods in polymer science. Finally, future possibilities and opportunities are derived from the current state‐of‐the‐art and perspectives for a potential evolution of polymer science are provided.

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Section: Processing and Fabricationmentioning

confidence: 99%

Application of Digital Methods in Polymer Science and Engineering

Schuett,

Endres,

Standau

et al. 2023

Adv Funct Materials

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show abstract

“…(Azad & Shahrajabian, 2019) employed box-Behnken design of experiments for a square wooden plastic composite to optimize warpage and volumetric shrinkage of the parts using a multiobjective optimization technique. (Shiroud Heidari et al, 2022) employed a central composite design to optimize a dialysis micro-lters simulated injection molding process to minimize the shrinkage and other response variables for part quality. (C. M. Lin & Chen, 2019) applied a robust Taguchi design methodology to determine the processing conditions, independently minimizing the warpage and residual stress of molded lens using grey optimization technique.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of experimental design techniques for modeling volumetric shrinkage in injection molding experiment using artificial intelligence

Abiodun

2022

Preprint

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The study examined two types of design of experiments (DoE) methods for injection molding of a molded part. It evaluated them using an artificial neural network (ANN) and a support vector machine (SVM) via cross-validation and holdout validation. The innovative goal is to identify the most efficient and successful ways for modeling varied DoE. The influence of four processing parameters on the volumetric shrinkage of a thin polystyrene plate sample is simulated using factorial design and orthogonal Taguchi arrays design. As measured by root mean square error (RMSE), the prediction performance revealed that DoE with eight experimental points as in \({2}^{4-1}\) for fractional factorial design and L8 for orthogonal Taguchi design is particularly efficient for this modeling simulation problem. Both design methods are beneficial and efficient because orthogonal Taguchi arrays play an essential role when the accuracy of fractional factorial designs is insufficient.

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“…The toggle mechanism is characterized by its mechanical advantages [29,30]. The mechanical performance of the toggle clamping unit can be improved by optimizing the dimensions of the clamping mechanism.…”

mentioning

confidence: 99%

The constant/variable kinematics adjustment of the crosshead and the mold’s stability management in injection molding

Zhao

Shan

et al. 2023

Int J Adv Manuf Technol

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During the clamping process in an injection-molding machine, the mold's movement is directly driven by the velocity of the crosshead. The form of the adjustment on the crosshead's kinematics can influence the final dynamics of the mold, which can contribute to the stability of the clamping duration further. This article is aimed at investigating the kinematics analysis and the stability management strategy of the mold in the early design stage for the clamping mechanism. The two different velocity-controlled forms of the crosshead, constant and variable kinematics adjustments, are applied and compared in the clamping analysis. Three factors of the crosshead, the maximum velocity, the acceleration/deceleration stage adjustment, and the multi acceleration/deceleration process, are validated for the stability control of the mold's motion in the injection molding process. The results show Article Title an extra "fast" process is detected in the constant condition when compared to the variable crosshead's kinematics adjustment. Furthermore, by the reasonable adjustment of the maximum velocity and two special positions of the crosshead during the acceleration and deceleration stages, the maximum acceleration fluctuation of the mold is decreased by more than 50%, allowing the mold to move more steadily.

show abstract

Multi‐response optimization of shrinkage, clamp force, and part weight in simulated injection molding process of a dialysis micro‐filter

Cited by 7 publications

References 25 publications

Application of Digital Methods in Polymer Science and Engineering

Application of Digital Methods in Polymer Science and Engineering

Optimization of experimental design techniques for modeling volumetric shrinkage in injection molding experiment using artificial intelligence

The constant/variable kinematics adjustment of the crosshead and the mold’s stability management in injection molding

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