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Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities
Nowadays, the implementation of cloud manufacturing technologies epitomizes the avant-garde in production systems. This affects several aspects of the management of these production systems, in particular scheduling activities, due to the possibility provided by cloud manufacturing of having real-ti...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279427/ http://dx.doi.org/10.1007/978-3-030-43177-8_5 |
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author | Sgarbossa, Fabio Peron, Mirco Fragapane, Giuseppe |
author_facet | Sgarbossa, Fabio Peron, Mirco Fragapane, Giuseppe |
author_sort | Sgarbossa, Fabio |
collection | PubMed |
description | Nowadays, the implementation of cloud manufacturing technologies epitomizes the avant-garde in production systems. This affects several aspects of the management of these production systems, in particular scheduling activities, due to the possibility provided by cloud manufacturing of having real-time information about the stages of a product life cycle and about the status of all services. However, so far, cloud manufacturing has mainly focused on machines, with limited interest in material handling systems. This shortfall has been addressed in this study, where a new material-handling paradigm, called Cloud Material Handling System (CMHS) and developed in the Logistics 4.0 Lab at NTNU (Norway), has been introduced. With CMHS, the scheduling of the Material Handling Modules (MHMs) can be optimized, increasing the flexibility and productivity of the overall manufacturing system. To achieve this, the integration of advanced industry 4.0 technologies such as Internet of Things (IoT), and in particular Indoor Positioning Technologies (IPT), Cloud Computing, Machine Learning (ML), and Artificial Intelligence (AI), is required. In fact, based on the relevant information provided on the cloud platform by IPT and IoT for each product, called Smart Object (SO) (position, physical characteristics and so on), an Intelligent Cognitive Engine (ICE) can use ML and AI to decide, in real time, which MHM is most suitable for carrying out the tasks required by these products based on a compatibility matrix, on their attributes, and on the defined scheduling procedure. |
format | Online Article Text |
id | pubmed-7279427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72794272020-06-09 Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities Sgarbossa, Fabio Peron, Mirco Fragapane, Giuseppe Scheduling in Industry 4.0 and Cloud Manufacturing Article Nowadays, the implementation of cloud manufacturing technologies epitomizes the avant-garde in production systems. This affects several aspects of the management of these production systems, in particular scheduling activities, due to the possibility provided by cloud manufacturing of having real-time information about the stages of a product life cycle and about the status of all services. However, so far, cloud manufacturing has mainly focused on machines, with limited interest in material handling systems. This shortfall has been addressed in this study, where a new material-handling paradigm, called Cloud Material Handling System (CMHS) and developed in the Logistics 4.0 Lab at NTNU (Norway), has been introduced. With CMHS, the scheduling of the Material Handling Modules (MHMs) can be optimized, increasing the flexibility and productivity of the overall manufacturing system. To achieve this, the integration of advanced industry 4.0 technologies such as Internet of Things (IoT), and in particular Indoor Positioning Technologies (IPT), Cloud Computing, Machine Learning (ML), and Artificial Intelligence (AI), is required. In fact, based on the relevant information provided on the cloud platform by IPT and IoT for each product, called Smart Object (SO) (position, physical characteristics and so on), an Intelligent Cognitive Engine (ICE) can use ML and AI to decide, in real time, which MHM is most suitable for carrying out the tasks required by these products based on a compatibility matrix, on their attributes, and on the defined scheduling procedure. 2020-06-09 /pmc/articles/PMC7279427/ http://dx.doi.org/10.1007/978-3-030-43177-8_5 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Sgarbossa, Fabio Peron, Mirco Fragapane, Giuseppe Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities |
title | Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities |
title_full | Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities |
title_fullStr | Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities |
title_full_unstemmed | Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities |
title_short | Cloud Material Handling Systems: Conceptual Model and Cloud-Based Scheduling of Handling Activities |
title_sort | cloud material handling systems: conceptual model and cloud-based scheduling of handling activities |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279427/ http://dx.doi.org/10.1007/978-3-030-43177-8_5 |
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