Evidence map›Paper›PMID 37388166›Full record

ArticleMethodsX2023

The human-centric Industry 5.0 collaboration architecture.

Attila Tóth, László Nagy, Roderick Kennedy, Belej Bohuš, János Abonyi, Tamás Ruppert

Abstract read
In one paragraph

Article in MethodsX, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
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

6 authors.

Attila TóthNovitech, New information technologies, Moyzesova 58 Kosice, Slovak Republic.
László NagyELKH-PE Complex Systems Monitoring Research Group, Department of Process Engineering, University of Pannonia, Egyetem u. 10, POB 158, Veszprem H-8200, Hungary.
Roderick KennedySimul Software Ltd, Studio N, Baltic Creative Digital House, 44 Simpson St, Liverpool L1 0AX, UK.
Belej BohušNovitech, New information technologies, Moyzesova 58 Kosice, Slovak Republic.
János AbonyiELKH-PE Complex Systems Monitoring Research Group, Department of Process Engineering, University of Pannonia, Egyetem u. 10, POB 158, Veszprem H-8200, Hungary.
Tamás RuppertELKH-PE Complex Systems Monitoring Research Group, Department of Process Engineering, University of Pannonia, Egyetem u. 10, POB 158, Veszprem H-8200, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the primary focus of Industry 4.0 revolves around extensive digitalization, Industry 5.0, on the other hand, seeks to integrate innovative technologies with human actors, signifying an approach that is more value-driven than technology-centric. The key objectives of the Industry 5.0 paradigm, which were not central to Industry 4.0, underscore that production should not only be digitalized but also resilient, sustainable, and human-centric. This paper is focusing on the human-centric pillar of Industry 5.0. The proposed methodology addresses the need for a human-AI collaborative process design and innovation approach to support the development and deployment of advanced AI-driven co-creation and collaboration tools. The method aims to solve the problem of integrating various innovative agents (human, AI, IoT, robot) in a plant-level collaboration process through a generic semantic definition, utilizing a time event-driven process. It also encourages the development of AI techniques for human-in-the-loop optimization, incorporating cross-checking with alternative feedback loop models. Benefits of this methodology include the Industry 5.0 collaboration architecture (I5arc), which provides new adaptable, generic frameworks, concepts, and methodologies for modern knowledge creation and sharing to enhance plant collaboration processes. •The I5arc aims to investigate and establish a truly integrated human-AI collaboration model, equipped with methods and tools for human-AI driven co-creation.•Provide a framework for the co-execution of processes and activities, with humans remaining empowered and in control.•The framework primarily targets human-AI collaboration processes and activities in industrial plants, with potential applicability to other societal contexts.

Indexed as

Artificial intelligenceCollaborationHuman-centricI5arc - Industry 5.0 collaboration architectureIndustry 4.0Industry 5.0Knowledge graphManufacturingOntology

Identifiers

PMID37388166
PMCPMC10300249

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.