Impact of Injection Molding Parameters on Material Acoustic Parameters

被引:0
作者
Saeedabadi, Komeil [1 ]
Lickert, Fabian [2 ]
Bruus, Henrik [2 ]
Tosello, Guido [1 ]
Calaon, Matteo [1 ]
机构
[1] DTU Construct, Prod Torvet Bldg 427, DK-2800 Lyngby, Denmark
[2] DTU Phys, Fysikvej Bldg 309, DK-2800 Lyngby, Denmark
关键词
injection molding; polymer acoustics; design of experiment; optimization; Moldex3D; RESIDUAL-STRESS; OPTIMIZATION; DESIGN;
D O I
10.3390/jmmp7060222
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Understanding the relationship between injection molding parameters and the acoustic properties of polymers is crucial for optimizing the design and performance of acoustic-based polymer devices. In this work, the impact of injection molding parameters, such as the injection velocity and packing pressure, on the acoustic parameters of polymers, namely the elastic moduli, is studied. The measurements lead to calculating material parameters, such as the Young's modulus and Poisson's ratio, that can be swiftly measured and determined thanks to this method. Polymethyl methacrylate (PMMA) was used as the molding material, and using PMMA LG IG 840, the parts were simulated and injection molded, applying a 'design of experiment' (DOE) statistical method. The results indicated a correlation between the injection molding process parameters and the acoustic characteristics, such as the elastic moduli, and a specifically decreasing trend with increase in the injection velocity. Notably, a relative decrease in the Young's modulus by 1% was observed when increasing the packing pressure from 90MPa to 120MPa. Similarly, a decrease in the Poisson's ratio of 2.9% was observed when the injection velocity was increased from 16mm/s to 40mm/s. This method can be used to fine-tune the material properties according to the needs of a given application and to facilitate the characterization of different polymer acoustic properties essential for acoustic-based polymer devices.
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页数:16
相关论文
共 41 条
[1]   Multi-objective Optimization of an Injection Molding Process [J].
Alvarado-Iniesta, Alejandro ;
Garcia-Alcaraz, Jorge L. ;
Del Valle-Carrasco, Arturo ;
Perez-Dominguez, Luis A. .
NEO 2015, 2017, 663 :391-407
[2]  
Ayun AHQ, 2022, JORDAN J MECH IND EN, V16, P319
[3]   Determination of the Complex-Valued Elastic Moduli of Polymers by Electrical-Impedance Spectroscopy for Ultrasound Applications [J].
Bode, William N. ;
Lickert, Fabian ;
Augustsson, Per ;
Bruus, Henrik .
PHYSICAL REVIEW APPLIED, 2022, 18 (06)
[4]   Design and Parametric Optimization of the Injection Molding Process Using Statistical Analysis and Numerical Simulation [J].
Chen, Jinping ;
Cui, Yanmei ;
Liu, Yuanpeng ;
Cui, Jianfeng .
PROCESSES, 2023, 11 (02)
[5]   Linear and volumetric dimensional changes of injection-molded PMMA denture base resins [J].
El Bahra, Shadi ;
Ludwig, Klaus ;
Samran, Abdulaziz ;
Freitag-Wolf, Sandra ;
Kerna, Matthias .
DENTAL MATERIALS, 2013, 29 (11) :1091-1097
[6]   Parameter optimisation of friction stir welded dissimilar polymers joints [J].
Eslami, Shayan ;
de Figueiredo, M. A. V. ;
Tavares, Paulo J. ;
Moreira, P. M. G. P. .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 94 (5-8) :1759-1770
[7]   Molding Properties of Inconel 718 Feedstocks Used in Low-Pressure Powder Injection Molding [J].
Fareh, Fouad ;
Demers, Vincent ;
Demarquette, Nicole R. ;
Turenne, Sylvain ;
Scalzo, Orlando .
ADVANCES IN MATERIALS SCIENCE AND ENGINEERING, 2016, 2016
[8]  
Giannekas N., 2018, Ph.D. Thesis, P1, DOI [10.3139/9781569906545.009, DOI 10.3139/9781569906545.009]
[9]   Investigation on Product and Process Fingerprints for Integrated Quality Assurance in Injection Molding of Microstructured Biochips [J].
Giannekas, Nikolaos ;
Zhang, Yang ;
Tosello, Guido .
JOURNAL OF MANUFACTURING AND MATERIALS PROCESSING, 2018, 2 (04)
[10]   Comparison of design of experiment methods for modeling injection molding experiments using artificial neural networks [J].
Heinisch, Julian ;
Lockner, Yannik ;
Hopmann, Christian .
JOURNAL OF MANUFACTURING PROCESSES, 2021, 61 :357-368