Evidence map›Paper›PMID 36743208›Full record

ArticleProcedia CIRP2022

Required parameters for modelling heterogeneous geographically dispersed manufacturing systems.

Mark Goudswaard, Chris Snider, Martins Obi, Lorenzo Giunta, Kautsar Ramli, Jennifer Johns, Ben Hicks, James Gopsill

Abstract read
In one paragraph

Article in Procedia CIRP, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Mark GoudswaardUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Chris SniderUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Martins ObiUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Lorenzo GiuntaUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Kautsar RamliUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Jennifer JohnsUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
Ben HicksUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.
James GopsillUniversity of Bristol, Queen's Building, University Walk, BS8 1TR, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 and global crises/events are driving governments to rethink their national manufacturing strategies. The drastic change of societal conditions has exposed our reliance on a constrained set of production practices. Furthermore, the future manufacturing landscape indicates - supply chain crises, trade agreements and natural disasters - a high level of volatility which requires a response that is far from being achieved. While these emergent challenges have called the efficacy of established practices into question, new manufacturing technologies, such as Additive Manufacturing (AM), present the capability to provide a solution. One proposal is agent-based brokering of AM which could be a method for tackling local, regional, national, and international production needs. However, to achieve the reality of brokered AM, it is imperative that the diversity of AM capability is considered. Diversity that existing homogeneous modelling of AM and manufacturing systems rarely consider or capture. This paper conceptualizes the reality of AM systems and elucidates parameters that are necessary for successful modelling and subsequent co-ordination. Having presented the required parameters the paper continues to discuss requisite levels of abstraction, suitable performance metrics and the role of humans in agent-based manufacturing systems.

Indexed as

Additive ManufacturingAgent-Based ManufacturingBrokering

Identifiers

PMID36743208
PMCPMC9883052

What OpenQuestion holds

Textmetadata
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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.