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Research Article

Online monitoring for error detection in vat photopolymerization

ORCID Icon, , , &
Pages 1313-1330 | Received 03 Jun 2022, Accepted 14 Nov 2022, Published online: 04 Jan 2023
 

ABSTRACT

Sensor implementation together with data processing in manufacturing provides continuous measurements enabling process monitoring, optimization, and automation. Additive manufacturing (AM) technologies are shifting from one-off and prototyping production to batch, mass, and continuous production. Current AM technologies are mostly focused on small production devices, without monitoring systems. This study aims to bring AM closer to automation by proposing an online monitor system for bottom-up photopolymerization AM (VPP) systems. The sensor-generated data is used to capture the detachment error of built parts from the build platform that otherwise cannot be observed physically by the machine operator. The detachment itself will not stop the build job, which results in lost material and operating time. The online monitoring procedure consists of two phases, an offline and an online one, respectively. The offline phase is used for training a prediction model to be used in connection with a control chart for online monitoring. The monitoring control chart is advantageous as only the detachment predictions need to be recorded. The research carried out in this article brings novelty in both the vat photopolymerization set-up, as well as in an online monitoring procedure that can be easily extended to similar technologies.

Acknowledgements

The work done for this article has been carried out for the project “Research based Enterprise - Qualification & Enterprising of Soft Tooling – Re-Quest”. The authors are thanking Jakob Skov Nielsen, Nikolaos Giannekas and Andrea Luongo for their contribution.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The work was supported by the Innovation Fund Denmark [no. 8057-00031B].

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