Evidence map›Paper›PMID 38317777›Full record

ArticleThe International journal, advanced manufacturing technology2024

Embedding a surface acoustic wave sensor and venting into a metal additively manufactured injection mould tool for targeted temperature monitoring.

Rokas Šakalys, Christopher O'Hara, Mandana Kariminejad, Albert Weinert, Mohammadreza Kadivar, Bruno Zluhan, Marion McAfee, Gerard McGranaghan, David Tormey, Ramesh Raghavendra

Abstract read
In one paragraph

Article in The International journal, advanced manufacturing technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Rokas ŠakalysI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Christopher O'HaraI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Mandana KariminejadI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Albert WeinertI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Mohammadreza KadivarI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Bruno ZluhanSouth Eastern Applied Materials Research Centre (SEAM), South East Technological University, Waterford, X91TX03 Ireland.
Marion McAfeeI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Gerard McGranaghanI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
David TormeyI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.
Ramesh RaghavendraI-Form, the SFI Research Centre for Advanced Manufacturing, University College Dublin, Room L0.13, CSCB Building, O'Brien Centre for Science (East), Belfield, Dublin 4, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Injection moulding (IM) tools with embedded sensors can significantly improve the process efficiency and quality of the fabricated parts through real-time monitoring and control of key process parameters such as temperature, pressure and injection speed. However, traditional mould tool fabrication technologies do not enable the fabrication of complex internal geometries. Complex internal geometries are necessary for technical applications such as sensor embedding and conformal cooling which yield benefits for process control and improved cycle times. With traditional fabrication techniques, only simple bore-based sensor embedding or external sensor attachment is possible. Externally attached sensors may compromise the functionality of the injection mould tool, with limitations such as the acquired data not reflecting the processes inside the part. The design freedom of additive manufacturing (AM) enables the fabrication of complex internal geometries, making it an excellent candidate for fabricating injection mould tools with such internal geometries. Therefore, embedding sensors in a desired location for targeted monitoring of critical mould tool regions is easier to achieve with AM. This research paper focuses on embedding a wireless surface acoustic wave (SAW) temperature sensor into an injection mould tool that was additively manufactured from stainless steel 316L. The laser powder bed fusion (L-PBF) "stop-and-go" approach was applied to embed the wireless SAW sensor. After embedding, the sensor demonstrated full functionality by recording real-time temperature data, which can further enhance process control. In addition, the concept of novel print-in-place venting design, applying the same L-PBF stop-and-go approach, for vent embedding was successfully implemented, enabling the IM of defectless parts at faster injection rates, whereas cavities designed and tested without venting resulted in parts with burn marks.

Indexed as

Additively manufactured injection mould toolsInjection mouldingIn-mould sensorsPrint-in-place ventingWireless sensor embedding

Identifiers

PMID38317777
PMCPMC10838231

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.