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Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers

With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for im...

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Detalles Bibliográficos
Autores principales: Li, Chen, Bian, Shijie, Wu, Tongzi, Donovan, Richard P., Li, Bingbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414792/
https://www.ncbi.nlm.nih.gov/pubmed/36016006
http://dx.doi.org/10.3390/s22166246
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author Li, Chen
Bian, Shijie
Wu, Tongzi
Donovan, Richard P.
Li, Bingbing
author_facet Li, Chen
Bian, Shijie
Wu, Tongzi
Donovan, Richard P.
Li, Bingbing
author_sort Li, Chen
collection PubMed
description With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for improved energy efficiency, equipment reliability, quality, safety, and productivity. This challenges capital cost and complexity for many small and medium-sized manufacturers (SMMs) who heavily rely on people to supervise manufacturing processes and facilities. This research aims to create an affordable, scalable, accessible, and portable (ASAP) solution to automate the supervision of manufacturing processes. The proposed approach seeks to reduce the cost and complexity of smart manufacturing deployment for SMMs through the deployment of consumer-grade electronics and a novel AI development methodology. The proposed system, AI-assisted Machine Supervision (AIMS), provides SMMs with two major subsystems: direct machine monitoring (DMM) and human-machine interaction monitoring (HIM). The AIMS system was evaluated and validated with a case study in 3D printing through the affordable AI accelerator solution of the vision processing unit (VPU).
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spelling pubmed-94147922022-08-27 Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers Li, Chen Bian, Shijie Wu, Tongzi Donovan, Richard P. Li, Bingbing Sensors (Basel) Article With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to optimize manufacturing workflow and processes for improved energy efficiency, equipment reliability, quality, safety, and productivity. This challenges capital cost and complexity for many small and medium-sized manufacturers (SMMs) who heavily rely on people to supervise manufacturing processes and facilities. This research aims to create an affordable, scalable, accessible, and portable (ASAP) solution to automate the supervision of manufacturing processes. The proposed approach seeks to reduce the cost and complexity of smart manufacturing deployment for SMMs through the deployment of consumer-grade electronics and a novel AI development methodology. The proposed system, AI-assisted Machine Supervision (AIMS), provides SMMs with two major subsystems: direct machine monitoring (DMM) and human-machine interaction monitoring (HIM). The AIMS system was evaluated and validated with a case study in 3D printing through the affordable AI accelerator solution of the vision processing unit (VPU). MDPI 2022-08-19 /pmc/articles/PMC9414792/ /pubmed/36016006 http://dx.doi.org/10.3390/s22166246 Text en © 2022 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
Li, Chen
Bian, Shijie
Wu, Tongzi
Donovan, Richard P.
Li, Bingbing
Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers
title Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers
title_full Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers
title_fullStr Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers
title_full_unstemmed Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers
title_short Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers
title_sort affordable artificial intelligence-assisted machine supervision system for the small and medium-sized manufacturers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9414792/
https://www.ncbi.nlm.nih.gov/pubmed/36016006
http://dx.doi.org/10.3390/s22166246
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