Comparative study of experimental thermographic data and finite element analysis on temperature evolution of PET-G layer deposition during additive manufacturing process

被引:0
|
作者
Kowalski, Lukasz [1 ]
Bembenek, Michal [1 ]
Uhrynski, Andrzej [2 ]
Bajda, Szymon [3 ]
机构
[1] AGH Univ Krakow, Fac Mech Engn & Robot, Dept Mfg Syst, Al Adama Mickiewicza 30, PL-30059 Krakow, Poland
[2] AGH Univ Sci & Technol, Fac Mech Engn & Robot, Dept Machine Design & Operat, Al Adama Mickiewicza 30, PL-30059 Krakow, Poland
[3] AGH Univ Sci & Technol, Fac Met Engn & Ind Comp Sci, Al A Mickiewicza 30, PL-30059 Krakow, Poland
关键词
FDM; 3D printing; Thermography; FEA; INFRARED THERMOGRAPHY; FDM; BEHAVIOR; SHRINKAGE;
D O I
10.24425/bpasts.2023.147926
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Additive manufacturing (AM) technologies gain popularity in recent years due to patent releases - and in effect - better accessibility of the technology. One of most popular AM technologies is fused deposition modeling (FDM) which is used to manufacture products out of thermoplastic polymers in a layer - by - layer manner. Due to the specificity of the method, parts manufactured this way tend to have non-isotropic properties. One of the factors influencing the part's mechanical behavior and quality is the thermoplastic material's bonding mechanism correlated with the processing temperature, as well as thermal shrinkage during processing. In this research authors verified the suitability of finite element method (FEM) analysis for determining PET-G thermal evolution during process, by creating layer transient heat transfer model, and comparing the obtained modelling results with ones registered during real-time process recorded with FLIR T1020 thermal imaging camera. Our model is a valuable resource for providing thermal conditions in existing numerical models that connect heat transfer, mesostructure, and AM product strength, especially when experimental data is lacking. Presented FE model reached maximum sample-specific error of 11.3%, while arithmetic mean percentage error for all samples and layer heights is equal to 4.3% which authors consider satisfactory. Model-to-experiment error is partially caused by glass transition of the material, which can be observed on experimental cooling rate curve after processing the temperature signal.
引用
收藏
页数:8
相关论文
共 17 条
  • [1] Finite Element Analysis of Additive Manufacturing Based on Fused Deposition Modeling: Distortions Prediction and Comparison With Experimental Data
    Cattenone, Alberto
    Morganti, Simone
    Alaimo, Gianluca
    Auricchio, Ferdinando
    JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, 2019, 141 (01):
  • [2] A three-dimensional finite element analysis of the temperature field during laser melting of metal powders in additive layer manufacturing
    Roberts, I. A.
    Wang, C. J.
    Esterlein, R.
    Stanford, M.
    Mynors, D. J.
    INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, 2009, 49 (12-13): : 916 - 923
  • [3] Finite element analysis of thermo-mechanical behavior of a multi-layer laser additive manufacturing process
    Khanafer, Khalil
    Alshuraiaan, Bader
    Al-Masri, Ali
    Aithal, Shashi
    Deiab, Ibrahim
    International Journal on Interactive Design and Manufacturing, 2022, 16 (03) : 893 - 911
  • [4] Finite element analysis of thermo-mechanical behavior of a multi-layer laser additive manufacturing process
    Khalil Khanafer
    Bader Alshuraiaan
    Ali Al-Masri
    Shashi Aithal
    Ibrahim Deiab
    International Journal on Interactive Design and Manufacturing (IJIDeM), 2022, 16 : 893 - 911
  • [5] Finite element analysis of thermo-mechanical behavior of a multi-layer laser additive manufacturing process
    Khanafer, Khalil
    Alshuraiaan, Bader
    Al-Masri, Ali
    Aithal, Shashi
    Deiab, Ibrahim
    INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2022, 16 (03): : 893 - 911
  • [6] In situ process monitoring of multi-layer deposition in wire arc additive manufacturing (WAAM) process with acoustic data analysis and machine learning
    Rahman, Md Arifur
    Jamal, Suhaima
    Cruz, Meenalosini Vimal
    Silwal, Bishal
    Taheri, Hossein
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2024, 132 (9-10): : 5087 - 5101
  • [7] A Comparative Analysis of Laser Additive Manufacturing of High Layer Thickness Pure Ti and Inconel 718 Alloy Materials Using Finite Element Method
    Singh, Sapam Ningthemba
    Chowdhury, Sohini
    Nirsanametla, Yadaiah
    Deepati, Anil Kumar
    Prakash, Chander
    Singh, Sunpreet
    Wu, Linda Yongling
    Zheng, Hongyu Y.
    Pruncu, Catalin
    MATERIALS, 2021, 14 (04) : 1 - 19
  • [8] Developing the AM G-code based thermomechanical finite element platform for the analysis of thermal deformation and stress in metal additive manufacturing process
    Mashhood, Muhammad
    Peters, Bernhard
    Zilian, Andreas
    Baroli, Davide
    Wyart, Eric
    JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2023, 37 (03) : 1103 - 1112
  • [9] Developing the AM G-code based thermomechanical finite element platform for the analysis of thermal deformation and stress in metal additive manufacturing process
    Muhammad Mashhood
    Bernhard Peters
    Andreas Zilian
    Davide Baroli
    Eric Wyart
    Journal of Mechanical Science and Technology, 2023, 37 : 1103 - 1112
  • [10] Study of workpiece temperature distribution in the contact zone during robotic grinding process using finite element analysis
    Tahvilian, A. M.
    Champliaud, H.
    Liu, Z.
    Hazel, B.
    EIGHTH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING, 2013, 12 : 205 - 210