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Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †

Dental laboratories require manpower resources for manufacturing prostheses and inventory management. In this paper, we developed an automated inventory management system for dental laboratories to improve the production efficiency. A sensing system was developed based on the framework of Internet o...

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Detalles Bibliográficos
Autores principales: Yang, Cheng-Jung, Chen, Ming-Huang, Lin, Keng-Pei, Cheng, Yu-Jie, Cheng, Fu-Chi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602064/
https://www.ncbi.nlm.nih.gov/pubmed/33066246
http://dx.doi.org/10.3390/s20205791
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author Yang, Cheng-Jung
Chen, Ming-Huang
Lin, Keng-Pei
Cheng, Yu-Jie
Cheng, Fu-Chi
author_facet Yang, Cheng-Jung
Chen, Ming-Huang
Lin, Keng-Pei
Cheng, Yu-Jie
Cheng, Fu-Chi
author_sort Yang, Cheng-Jung
collection PubMed
description Dental laboratories require manpower resources for manufacturing prostheses and inventory management. In this paper, we developed an automated inventory management system for dental laboratories to improve the production efficiency. A sensing system was developed based on the framework of Internet of things to collect the information of cobalt-chromium disks both in the storage room and manufacturing area, and an expert system was developed to automatically conduct inventory management based on the established rules. The proposed system can reduce the time of recording data and also assist the manager in configuring and managing material orders. The experimental results showed that a large amount of working time is reduced, resulting in the benefits of saving money and improving efficiency in dental manufacturing.
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spelling pubmed-76020642020-11-01 Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories † Yang, Cheng-Jung Chen, Ming-Huang Lin, Keng-Pei Cheng, Yu-Jie Cheng, Fu-Chi Sensors (Basel) Article Dental laboratories require manpower resources for manufacturing prostheses and inventory management. In this paper, we developed an automated inventory management system for dental laboratories to improve the production efficiency. A sensing system was developed based on the framework of Internet of things to collect the information of cobalt-chromium disks both in the storage room and manufacturing area, and an expert system was developed to automatically conduct inventory management based on the established rules. The proposed system can reduce the time of recording data and also assist the manager in configuring and managing material orders. The experimental results showed that a large amount of working time is reduced, resulting in the benefits of saving money and improving efficiency in dental manufacturing. MDPI 2020-10-13 /pmc/articles/PMC7602064/ /pubmed/33066246 http://dx.doi.org/10.3390/s20205791 Text en © 2020 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yang, Cheng-Jung
Chen, Ming-Huang
Lin, Keng-Pei
Cheng, Yu-Jie
Cheng, Fu-Chi
Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †
title Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †
title_full Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †
title_fullStr Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †
title_full_unstemmed Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †
title_short Importing Automated Management System to Improve the Process Efficiency of Dental Laboratories †
title_sort importing automated management system to improve the process efficiency of dental laboratories †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602064/
https://www.ncbi.nlm.nih.gov/pubmed/33066246
http://dx.doi.org/10.3390/s20205791
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