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Patterns for Visual Management in Industry 4.0

The technologies of Industry 4.0 provide an opportunity to improve the effectiveness of Visual Management in manufacturing. The opportunity of improvement is twofold. From one side, Visual Management theory and practice can inspire the design of new software tools suitable for Industry 4.0; on the o...

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Detalles Bibliográficos
Autores principales: Fenza, Giuseppe, Loia, Vincenzo, Nota, Giancarlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512411/
https://www.ncbi.nlm.nih.gov/pubmed/34640760
http://dx.doi.org/10.3390/s21196440
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author Fenza, Giuseppe
Loia, Vincenzo
Nota, Giancarlo
author_facet Fenza, Giuseppe
Loia, Vincenzo
Nota, Giancarlo
author_sort Fenza, Giuseppe
collection PubMed
description The technologies of Industry 4.0 provide an opportunity to improve the effectiveness of Visual Management in manufacturing. The opportunity of improvement is twofold. From one side, Visual Management theory and practice can inspire the design of new software tools suitable for Industry 4.0; on the other side, the technology of Industry 4.0 can be used to increase the effectiveness of visual software tools. The paper first explores how the theoretical result on Visual Management can be used as a guideline to improve human-computer interaction, then a methodology is proposed for the design of visual patterns for manufacturing. Four visual patterns are presented that contribute to the solution of problems frequently encountered in discrete manufacturing industries; these patterns help to solve planning and control problems thus providing support to various management functions. Positive implications of this research concern people engagement and empowerment as well as improved problem solving, decision-making and management of manufacturing processes.
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spelling pubmed-85124112021-10-14 Patterns for Visual Management in Industry 4.0 Fenza, Giuseppe Loia, Vincenzo Nota, Giancarlo Sensors (Basel) Article The technologies of Industry 4.0 provide an opportunity to improve the effectiveness of Visual Management in manufacturing. The opportunity of improvement is twofold. From one side, Visual Management theory and practice can inspire the design of new software tools suitable for Industry 4.0; on the other side, the technology of Industry 4.0 can be used to increase the effectiveness of visual software tools. The paper first explores how the theoretical result on Visual Management can be used as a guideline to improve human-computer interaction, then a methodology is proposed for the design of visual patterns for manufacturing. Four visual patterns are presented that contribute to the solution of problems frequently encountered in discrete manufacturing industries; these patterns help to solve planning and control problems thus providing support to various management functions. Positive implications of this research concern people engagement and empowerment as well as improved problem solving, decision-making and management of manufacturing processes. MDPI 2021-09-27 /pmc/articles/PMC8512411/ /pubmed/34640760 http://dx.doi.org/10.3390/s21196440 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fenza, Giuseppe
Loia, Vincenzo
Nota, Giancarlo
Patterns for Visual Management in Industry 4.0
title Patterns for Visual Management in Industry 4.0
title_full Patterns for Visual Management in Industry 4.0
title_fullStr Patterns for Visual Management in Industry 4.0
title_full_unstemmed Patterns for Visual Management in Industry 4.0
title_short Patterns for Visual Management in Industry 4.0
title_sort patterns for visual management in industry 4.0
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512411/
https://www.ncbi.nlm.nih.gov/pubmed/34640760
http://dx.doi.org/10.3390/s21196440
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