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A novel framework for storage assignment optimization inspired by finite element method
Considering necessary fundamental and structural changes in the production and manufacturing industries to fulfill the industry 4.0 paradigm, the proposal of new ideas and frameworks for operations management of production and manufacturing system is inevitable. This research focuses on traditional...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959603/ https://www.ncbi.nlm.nih.gov/pubmed/33817025 http://dx.doi.org/10.7717/peerj-cs.378 |
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author | Tabatabaei, Seyed-Kourosh Fatahi Valilai, Omid Abedian, Ali Khalilzadeh, Mohammad |
author_facet | Tabatabaei, Seyed-Kourosh Fatahi Valilai, Omid Abedian, Ali Khalilzadeh, Mohammad |
author_sort | Tabatabaei, Seyed-Kourosh |
collection | PubMed |
description | Considering necessary fundamental and structural changes in the production and manufacturing industries to fulfill the industry 4.0 paradigm, the proposal of new ideas and frameworks for operations management of production and manufacturing system is inevitable. This research focuses on traditional methods proposed for storage assignment problem and struggles for new methods and definitions for industry 4.0 based storage assignment concepts. At the first step, the paper proposes a new definition of storage assignment and layout problem for fulfilling storage mechanism agility in terms of automated store and retrieval process (AS/RS) in modern inventories. Then considering the shortcomings of traditional algorithms for storage assignment problem, the paper contributes a new algorithm called SAO/FEM (storage assignment optimization technique), inspired from mechanical engineering discipline for analysis and optimization of storage assignment problem. The proposed new algorithm about stress distribution analogy, and the help of the Finite Element Method and minimum total potential energy theory, proposes a new model for storage assignment optimization. The efficiency of the proposed algorithm in terms of calculation time and the best answer investigated through numerical examples. The article has developed an application for SAO/FEM algorithm as a value creation module and applied new optimized storage positioning in the warehouses. |
format | Online Article Text |
id | pubmed-7959603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79596032021-04-02 A novel framework for storage assignment optimization inspired by finite element method Tabatabaei, Seyed-Kourosh Fatahi Valilai, Omid Abedian, Ali Khalilzadeh, Mohammad PeerJ Comput Sci Algorithms and Analysis of Algorithms Considering necessary fundamental and structural changes in the production and manufacturing industries to fulfill the industry 4.0 paradigm, the proposal of new ideas and frameworks for operations management of production and manufacturing system is inevitable. This research focuses on traditional methods proposed for storage assignment problem and struggles for new methods and definitions for industry 4.0 based storage assignment concepts. At the first step, the paper proposes a new definition of storage assignment and layout problem for fulfilling storage mechanism agility in terms of automated store and retrieval process (AS/RS) in modern inventories. Then considering the shortcomings of traditional algorithms for storage assignment problem, the paper contributes a new algorithm called SAO/FEM (storage assignment optimization technique), inspired from mechanical engineering discipline for analysis and optimization of storage assignment problem. The proposed new algorithm about stress distribution analogy, and the help of the Finite Element Method and minimum total potential energy theory, proposes a new model for storage assignment optimization. The efficiency of the proposed algorithm in terms of calculation time and the best answer investigated through numerical examples. The article has developed an application for SAO/FEM algorithm as a value creation module and applied new optimized storage positioning in the warehouses. PeerJ Inc. 2021-02-16 /pmc/articles/PMC7959603/ /pubmed/33817025 http://dx.doi.org/10.7717/peerj-cs.378 Text en ©2021 Tabatabaei et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Tabatabaei, Seyed-Kourosh Fatahi Valilai, Omid Abedian, Ali Khalilzadeh, Mohammad A novel framework for storage assignment optimization inspired by finite element method |
title | A novel framework for storage assignment optimization inspired by finite element method |
title_full | A novel framework for storage assignment optimization inspired by finite element method |
title_fullStr | A novel framework for storage assignment optimization inspired by finite element method |
title_full_unstemmed | A novel framework for storage assignment optimization inspired by finite element method |
title_short | A novel framework for storage assignment optimization inspired by finite element method |
title_sort | novel framework for storage assignment optimization inspired by finite element method |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7959603/ https://www.ncbi.nlm.nih.gov/pubmed/33817025 http://dx.doi.org/10.7717/peerj-cs.378 |
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