Evidence map›Paper›PMID 39066078›Full record

ReviewSensors (Basel, Switzerland)2024

Requirements and Barriers for Human-Centered SMEs.

Julia Nazarejova, Zuzana Soltysova, Tetiana Rudeichuk

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2024. 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

3 authors.

Julia NazarejovaFaculty of Manufacturing Technologies, Technical University of Kosice, 080 01 Presov, Slovakia.
Zuzana SoltysovaFaculty of Manufacturing Technologies, Technical University of Kosice, 080 01 Presov, Slovakia.ORCID 0000-0002-6678-0383
Tetiana RudeichukFaculty of Manufacturing Technologies, Technical University of Kosice, 080 01 Presov, Slovakia.ORCID 0000-0003-1332-0073

Funding

KEGA project granted by the Ministry of Education of the Slovak Republic. 044TUKE-4/2023the project SME 5.0 with funding received from the European Union's Horizon research and in-novation program under the Marie Skłodowska-Curie 101086487
6 · The paper itself

Abstract

With the advantages of new technologies and rising demand from customers, it is necessary to improve the manufacturing process. This necessity was recognized by the industry; therefore, the concept of Industry 4.0 has been implemented in various areas of manufacturing and services. The backbone and main aspect of Industry 4.0 is digitalization and the implementation of technologies into processes. While this concept helps manufacturers with the modernization and optimization of many attributes of the processes, Industry 5.0 takes a step further and brings importance to the human factor of industry practice, together with sustainability and resilience. The concept of Industry 5.0 contributes to the idea of creating a sustainable, prosperous, and human-friendly environment within companies. The main focus of the article is to analyze the existing literature regarding what is missing from the successful implementation of human centricity into industry practice, namely in small and medium-sized factories (SMEs). These findings are then presented in the form of requirements and barriers for the implementation of human centricity into SME factories, which can serve as guidelines for implementing human-centered manufacturing using axiomatic design theory in SMEs, which can serve as a roadmap for practitioners.

Indexed as

ErgonomicsHumansIndustrydigital transformationhuman-centeredIndustry 5.0resiliencesensorsSMEssustainability

Identifiers

PMID39066078
PMCPMC11281314

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.