Performance evaluation of warping characteristic of fused deposition modelling process

被引:1
作者
Biranchi N. Panda
K. Shankhwar
Akhil Garg
Zhang Jian
机构
[1] Universidade de Lisboa,IDMEC, Instituto Superior Técnico
[2] Kalinga Institute of Industrial Technology,Department of Mechanical Engineering
[3] Shantou University,Department of Mechatronics Engineering
来源
The International Journal of Advanced Manufacturing Technology | 2017年 / 88卷
关键词
3-D printing; Fused deposition modelling; Warp deformation; Dimensional error; Modelling;
D O I
暂无
中图分类号
学科分类号
摘要
In recent years, fused deposition modelling (FDM) is gaining more popularity due to its distinct advantages in terms of cost-effectiveness, lower build times, and flexibility. Compared to other 3-D printing processes such as SLS, this process does not use any kind of high-intensity laser power to build functional parts out of CAD models and, hence, makes the process much simpler, cheaper, and adaptable. Past studies reveal that productivity of the FDM process can be further increased by effectively controlling its process parameters such as layer thickness, part orientation, extrusion temperature, and so on. In this regard, many authors have investigated the optimal parameter settings for improving part strength, surface finish, wear, and fatigue properties of FDM made prototypes. However, warping performance behavior has got very recent attention due to complex heat transfer mechanism involved during this process. Experimental investigations are necessary to understand the deformation behavior of prototypes. In addition, the quantification and optimization of warp deformation along with dimensional error poses a challenging multi-objective optimization problem. Therefore, this work proposes an evolutionary system identification (SI) approach to explicitly quantify the warp deformation and dimensional error based on the four inputs such as line width compensation, extrusion velocity, filling velocity, and layer thickness of FDM prototypes. The two models’ performance analysis comprising of error metrics evaluation, cross-validation, and hypothesis tests is performed to validate its robustness. The analysis concluded that the layer thickness and extrusion velocity influence the warp deformation and, while filling velocity and line width compensation, influences the dimensional error the most.
引用
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页码:1799 / 1811
页数:12
相关论文
共 38 条
  • [1] Mahapatra SS(2013)Benchmarking of rapid prototyping systems using grey relational analysis International Journal of Services and Operations Management 16 460-477
  • [2] Panda BN(2007)Fabrication direction optimization to minimize post-machining in layered manufacturing International Journal of Machine Tools and Manufacture 47 593-606
  • [3] Ahn D(2004)Development of new metal/polymer materials for rapid tooling using fused deposition modeling Mater Des 25 587-594
  • [4] Kim H(2011)Thermo-mechanical properties of a highly filled polymeric composites for fused deposition modeling Mater Des 32 3448-3456
  • [5] Lee S(2015)Identification of non-minimum phase processes with time delay in the presence of measurement noise ISA transactions 57 245-253
  • [6] Mastoid SH(2015)Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data ISA transactions 58 186-195
  • [7] Song WQ(1995)Nonlinear black-box modeling in system identification: a unified overview Automatica 31 1691-1724
  • [8] Nikzad M(2015)A general regression neural network approach for the evaluation of compressive strength of FDM prototypes Neural Computing and Applications 26 1129-1136
  • [9] Masood SH(2015)Process characterisation of 3D-printed FDM components using improved evolutionary computational approach The International Journal of Advanced Manufacturing Technology 78 781-793
  • [10] Sbarski I(2016)Empirical investigation of environmental characteristic of 3-D additive manufacturing process based on slice thickness and part orientation Measurement 86 293-300