EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion

Iñigo Flores Ituarte; Eero Huotilainen; Olli Wiikinkoski; Jukka Tuomi

doi:10.25341/D4859D

EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion

Iñigo Flores Ituarte, Eero Huotilainen, Olli Wiikinkoski, Jukka Tuomi

Department of Energy and Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

2 Citations (Scopus)

Abstract

This research explores the real-time process control of polymer flowability in Powder Bed Fusion (PBF). To do so, a novel system based on machine vision and an image-processing algorithm was developed and tested in an open hardware and software PBF system. The system has the ability to analyze the quality of the powder bed by computing a defect ratio of the powder bed after each recoating operation. Then, this ratio is used as a performance variable in three full factorial Design of Experiments (DOE). The results show that the installation of machine vision and image processing system can potentially provide a signal to repeat the recoating process and correct the defect on the powder bed. At the same time, recoating process parameters can be adjusted dynamically to guarantee an optimum quality of the powder bed and minimize possible build failures.

Original language	English
Title of host publication	Proceedings of the International Conference on Progress in Additive Manufacturing
Publisher	Nanyang Technological University
Pages	401-406
Number of pages	6
Volume	2018-May
DOIs	https://doi.org/10.25341/D4859D
Publication status	Published - 1 Jan 2018
MoE publication type	A4 Conference publication
Event	International Conference on Progress in Additive Manufacturing - Singapore, Singapore Duration: 14 May 2018 → 17 May 2018 Conference number: 3

Publication series

Name	Proceedings of the International Conference on Progress in Additive Manufacturing
ISSN (Print)	2424-8967

Conference

Conference	International Conference on Progress in Additive Manufacturing
Abbreviated title	Pro-AM
Country/Territory	Singapore
City	Singapore
Period	14/05/2018 → 17/05/2018

Keywords

Additive manufacturing
Machine vision
Powder bed fusion
Powder flowability
Process monitoring

Access to Document

10.25341/D4859D

Cite this

Ituarte, I. F., Huotilainen, E., Wiikinkoski, O., & Tuomi, J. (2018). EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion. In Proceedings of the International Conference on Progress in Additive Manufacturing (Vol. 2018-May, pp. 401-406). (Proceedings of the International Conference on Progress in Additive Manufacturing). Nanyang Technological University. https://doi.org/10.25341/D4859D

Ituarte, Iñigo Flores ; Huotilainen, Eero ; Wiikinkoski, Olli et al. / EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion. Proceedings of the International Conference on Progress in Additive Manufacturing. Vol. 2018-May Nanyang Technological University, 2018. pp. 401-406 (Proceedings of the International Conference on Progress in Additive Manufacturing).

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abstract = "This research explores the real-time process control of polymer flowability in Powder Bed Fusion (PBF). To do so, a novel system based on machine vision and an image-processing algorithm was developed and tested in an open hardware and software PBF system. The system has the ability to analyze the quality of the powder bed by computing a defect ratio of the powder bed after each recoating operation. Then, this ratio is used as a performance variable in three full factorial Design of Experiments (DOE). The results show that the installation of machine vision and image processing system can potentially provide a signal to repeat the recoating process and correct the defect on the powder bed. At the same time, recoating process parameters can be adjusted dynamically to guarantee an optimum quality of the powder bed and minimize possible build failures.",

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Ituarte, IF, Huotilainen, E, Wiikinkoski, O & Tuomi, J 2018, EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion. in Proceedings of the International Conference on Progress in Additive Manufacturing. vol. 2018-May, Proceedings of the International Conference on Progress in Additive Manufacturing, Nanyang Technological University, pp. 401-406, International Conference on Progress in Additive Manufacturing, Singapore, Singapore, 14/05/2018. https://doi.org/10.25341/D4859D

EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion. / Ituarte, Iñigo Flores; Huotilainen, Eero; Wiikinkoski, Olli et al.
Proceedings of the International Conference on Progress in Additive Manufacturing. Vol. 2018-May Nanyang Technological University, 2018. p. 401-406 (Proceedings of the International Conference on Progress in Additive Manufacturing).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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T1 - EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion

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AU - Huotilainen, Eero

AU - Wiikinkoski, Olli

AU - Tuomi, Jukka

N1 - Conference code: 3

PY - 2018/1/1

Y1 - 2018/1/1

N2 - This research explores the real-time process control of polymer flowability in Powder Bed Fusion (PBF). To do so, a novel system based on machine vision and an image-processing algorithm was developed and tested in an open hardware and software PBF system. The system has the ability to analyze the quality of the powder bed by computing a defect ratio of the powder bed after each recoating operation. Then, this ratio is used as a performance variable in three full factorial Design of Experiments (DOE). The results show that the installation of machine vision and image processing system can potentially provide a signal to repeat the recoating process and correct the defect on the powder bed. At the same time, recoating process parameters can be adjusted dynamically to guarantee an optimum quality of the powder bed and minimize possible build failures.

AB - This research explores the real-time process control of polymer flowability in Powder Bed Fusion (PBF). To do so, a novel system based on machine vision and an image-processing algorithm was developed and tested in an open hardware and software PBF system. The system has the ability to analyze the quality of the powder bed by computing a defect ratio of the powder bed after each recoating operation. Then, this ratio is used as a performance variable in three full factorial Design of Experiments (DOE). The results show that the installation of machine vision and image processing system can potentially provide a signal to repeat the recoating process and correct the defect on the powder bed. At the same time, recoating process parameters can be adjusted dynamically to guarantee an optimum quality of the powder bed and minimize possible build failures.

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KW - Machine vision

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KW - Process monitoring

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Ituarte IF, Huotilainen E, Wiikinkoski O, Tuomi J. EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion. In Proceedings of the International Conference on Progress in Additive Manufacturing. Vol. 2018-May. Nanyang Technological University. 2018. p. 401-406. (Proceedings of the International Conference on Progress in Additive Manufacturing). doi: 10.25341/D4859D

EXPERIMENTS with machine vision for polymer flowability analysis in powder bed fusion

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