Skip to main content
Log in

A novel strategy for multi-part production in additive manufacturing

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

In this paper, a novel strategy for multi-part additive manufacturing (AM) production is proposed in order to reduce the total fabrication time. Traditionally, in a multi-part production process, parts are positioned on the print platform and then are sliced into layers from the bottom to the top. In this manner, the time for moving the print nozzle from one part to another in each layer can be excessive. In fact, it is possible to fabricate some more layers (instead of one layer) in the same part first, before moving to another part to start printing. Based on this idea, parts need to be positioned on the platform optimally. The best positions are determined by considering and calculating the total fabrication time. An eight-step novel strategy is proposed in this paper to obtain parts’ optimal positions and nozzle travel paths. A case study was carried out to demonstrate that this strategy can save fabrication time for multi-part manufacturing in AM, compared with normal multi-part fabrication method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Fu Y-F, Rolfe B, Chiu LNS, Wang Y, Huang X, Ghabraie K (2020) Parametric studies and manufacturability experiments on smooth self-supporting topologies. Virtual Phys Prototyp 15:22–34. https://doi.org/10.1080/17452759.2019.1644185

    Article  Google Scholar 

  2. ISO (2015) Additive manufacturing — General principles — Terminology. Iso/Astm 52900:1–26. https://doi.org/10.1520/F2792-12A.2

    Article  Google Scholar 

  3. Rane K, Strano M (2019) A comprehensive review of extrusion-based additive manufacturing processes for rapid production of metallic and ceramic parts. Adv Manuf 155–173 https://doi.org/10.1007/s40436-019-00253-6

  4. Bourell D, Kruth JP, Leu M, Levy G, Rosen D, Beese AM, Clare A (2017) Materials for additive manufacturing. CIRP Ann - Manuf Technol 66:659–681. https://doi.org/10.1016/j.cirp.2017.05.009

    Article  Google Scholar 

  5. Yu C, Jiang J (2020) A perspective on using machine learning in 3D bioprinting. Int J Bioprinting 6:4–11. https://doi.org/10.18063/ijb.v6i1.253

    Article  Google Scholar 

  6. Jiang J, Xu X, Stringer J (2018) A new support strategy for reducing waste in additive manufacturing. In: The 48th International Conference on Computers and Industrial Engineering (CIE 48). Auckland, pp 1–7

  7. Hao L, Mellor S, Seaman O, Henderson J, Sewell N, Sloan M (2010) Material characterisation and process development for chocolate additive layer manufacturing. Virtual Phys Prototyp 5:57–64. https://doi.org/10.1080/17452751003753212

    Article  Google Scholar 

  8. Bos F, Wolfs R, Ahmed Z, Salet T (2016) Additive manufacturing of concrete in construction: potentials and challenges of 3D concrete printing. Virtual Phys Prototyp 11:209–225. https://doi.org/10.1080/17452759.2016.1209867

    Article  Google Scholar 

  9. Zocca A, Colombo P, Gomes CM, Günster J (2015) Additive manufacturing of ceramics: issues, potentialities, and opportunities. J Am Ceram Soc 98:1983–2001. https://doi.org/10.1111/jace.13700

    Article  Google Scholar 

  10. Jiang J, Hu G, Li X, Xu X, Zheng P, Stringer J (2019) Analysis and prediction of printable bridge length in fused deposition modelling based on back propagation neural network. Virtual Phys Prototyp 14:253–266. https://doi.org/10.1080/17452759.2019.1576010

    Article  Google Scholar 

  11. Jiang J, Lou J, Hu G (2019) Effect of support on printed properties in fused deposition modelling processes. Virtual Phys Prototyp 14:308–315. https://doi.org/10.1080/17452759.2019.1568835

    Article  Google Scholar 

  12. Ding D, Pan Z, Cuiuri D, Li H (2015) A practical path planning methodology for wire and arc additive manufacturing of thin-walled structures. Robot Comput Integr Manuf 34:8–19. https://doi.org/10.1016/j.rcim.2015.01.003

    Article  Google Scholar 

  13. An JY, He Y, Zhong FJ et al (2014) Optimization of tool-path generation for material extrusion-based additive manufacturing technology. Addit Manuf 1:32–47. https://doi.org/10.1016/j.addma.2014.08.004

    Article  Google Scholar 

  14. Jin Y, He Y, Fu G, Zhang A, du J (2017) A non-retraction path planning approach for extrusion-based additive manufacturing. Robot Comput Integr Manuf 48:132–144. https://doi.org/10.1016/j.rcim.2017.03.008

    Article  Google Scholar 

  15. Muller P, Hascoet JY, Mognol P (2014) Toolpaths for additive manufacturing of functionally graded materials (FGM) parts. Rapid Prototyp J 20:511–522. https://doi.org/10.1108/RPJ-01-2013-0011

    Article  Google Scholar 

  16. Ozbolat IT, Khoda AKMB (2014) Design of a new parametric path plan for additive manufacturing of hollow porous structures with functionally graded materials. J Comput Inf Sci Eng 14:14. https://doi.org/10.1115/1.4028418

    Article  Google Scholar 

  17. Liu J, Ma Y, Qureshi AJ, Ahmad R (2018) Light-weight shape and topology optimization with hybrid deposition path planning for FDM parts. Int J Adv Manuf Technol 97:1123–1135. https://doi.org/10.1007/s00170-018-1955-4

    Article  Google Scholar 

  18. Coupek D, Friedrich J, Battran D, Riedel O (2018) Reduction of support structures and building time by optimized path planning algorithms in multi-axis additive manufacturing. Procedia CIRP 67:221–226. https://doi.org/10.1016/j.procir.2017.12.203

    Article  Google Scholar 

  19. Jiang J, Stringer J, Xu X (2019) Support optimization for flat features via path planning in additive manufacturing. 3D Print Addit Manuf 6:171–179. https://doi.org/10.1089/3dp.2017.0124

    Article  Google Scholar 

  20. Jiang J, Xu X, Stringer J (2019) Optimization of process planning for reducing material waste in extrusion based additive manufacturing. Robot Comput Integr Manuf 59:317–325. https://doi.org/10.1016/j.rcim.2019.05.007

    Article  Google Scholar 

  21. Jiang J, Weng F, Gao S, Stringer J, Xu X, Guo P (2019) A support interface method for easy part removal in direct metal deposition. Manuf Lett 20:30–33. https://doi.org/10.1016/j.mfglet.2019.04.002

    Article  Google Scholar 

  22. Zhang Y, Bernard A, Harik R, Karunakaran KP (2017) Build orientation optimization for multi-part production in additive manufacturing. J Intell Manuf 28:1393–1407. https://doi.org/10.1007/s10845-015-1057-1

    Article  Google Scholar 

  23. Jiang J, Xu X, Stringer J (2019) Optimisation of multi-part production in additive manufacturing for reducing support waste. Virtual Phys Prototyp 14:219–228. https://doi.org/10.1080/17452759.2019.1585555

    Article  Google Scholar 

  24. Yang Y, Fuh JYH, Loh HT, Wong YS (2003) Multi-orientational deposition to minimize support in the layered manufacturing process. J Manuf Syst 22:116–129

    Article  Google Scholar 

  25. Thrimurthulu K, Pandey PM, Reddy NV, Venkata Reddy N (2004) Optimum part deposition orientation in fused deposition modeling. Int J Mach Tools Manuf 44:585–594

    Article  Google Scholar 

  26. Zhao J (2005) Determination of optimal build orientation based on satisfactory degree theory for RPT. In: Proceedings - Ninth International Conference on Computer Aided Design and Computer Graphics, CAD/CG 2005. pp 225–230

  27. Das P, Chandran R, Samant R, Anand S (2015) Optimum part build orientation in additive manufacturing for minimizing part errors and support structures. Procedia Manuf 1:343–354. https://doi.org/10.1016/j.promfg.2015.09.041

    Article  Google Scholar 

  28. Luo Z, Yang F, Dong G et al (2016) Orientation optimization in layer-based additive manufacturing process. Proc ASME Des Eng Tech Conf 1A–2016:1–10. https://doi.org/10.1115/DETC2016-59969

    Article  Google Scholar 

  29. Jiang J, Stringer J, Xu X, Zhong RY (2018) Investigation of printable threshold overhang angle in extrusion-based additive manufacturing for reducing support waste. Int J Comput Integr Manuf 31:961–969. https://doi.org/10.1080/0951192X.2018.1466398

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jingchao Jiang.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, J., Xu, X., Xiong, Y. et al. A novel strategy for multi-part production in additive manufacturing. Int J Adv Manuf Technol 109, 1237–1248 (2020). https://doi.org/10.1007/s00170-020-05734-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-020-05734-8

Keywords

Navigation