Evidence map›Paper›PMID 30986959›Full record

ArticleSensors (Basel, Switzerland)2019

New Approaches to Implementing the SmartJacket into Industry 4.0

Petr Marcon, Jakub Arm, Tomas Benesl, Frantisek Zezulka, Christian Diedrich, Tizian Schröder, Alexander Belyaev, Premysl Dohnal, Tomas Kriz, Zdenek Bradac

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

10 authors.

Petr MarconBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. marcon@feec.vutbr.cz.ORCID 0000-0001-7349-8426
Jakub ArmBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. xarmja00@vutbr.cz.
Tomas BeneslBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. xbenes23@vutbr.cz.
Frantisek ZezulkaBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. zezulka@feec.vutbr.cz.
Christian DiedrichInstitute for Automation Engineering, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany. christian.diedrich@ovgu.de.
Tizian SchröderInstitute for Automation Engineering, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany. tizian.schroeder@ovgu.de.
Alexander BelyaevInstitute for Automation Engineering, Otto von Guericke University Magdeburg, 39106 Magdeburg, Germany. alexander.belyaev@ovgu.de.
Premysl DohnalBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. dohnalp@feec.vutbr.cz.
Tomas KrizBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. krizt@feec.vutbr.cz.
Zdenek BradacBrno University of Technology, Faculty of Electrical Engineering and Communication, 61600 Brno, Czech Republic. bradac@feec.vutbr.cz.

Funding

Technologická Agentura České Republiky TF04000074
6 · The paper itself

Abstract

The paper discusses the possibilities of incorporating sensors and indicators into the environment of an Industry 4.0 digital factory. The concept of Industry 4.0 (I4.0) is characterized via a brief description of the RAMI 4.0 and I4.0 component model. In this context, the article outlines the structure of an I4.0 production component, interpreting such an item as a body integrating the asset and its electronic form, namely, the Asset Administration Shell (AAS). The formation of the AAS sub-models from the perspectives of identification, communication, configuration, safety, and condition monitoring is also described to complete the main analysis. Importantly, the authors utilize concrete use cases to demonstrate the roles of the given I4.0 component model and relevant SW technologies in creating the AAS. In this context, the use cases embody applications where an operator wearing a SmartJacket equipped with sensors and indicators ensures systematic data collection by passing through the manufacturing process. The set of collected information then enables the operator and the system server to monitor and intervene in the production cycle. The advantages and disadvantages of the individual scenarios are summarized to support relevant analysis of the entire problem.

Indexed as

Asset Administration Shell (AAS)Industry 4.0Internet of Things (IoT)LPWANMQTTOPC UARAMI 4.0SmartJacketWiFi

Identifiers

PMID30986959
PMCPMC6479368

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.