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Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems
ABSTRACT: In drilling process almost seventy percent time is spent in tool switching and moving the spindle from one hole to the other. This time travel is non productive as it does not take part in actual drilling process. Therefore, this non productive time needs to be optimized. Different metaheu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857905/ https://www.ncbi.nlm.nih.gov/pubmed/36712556 http://dx.doi.org/10.1007/s42452-022-05271-x |
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author | Mehmood, Nasir Umer, Muhammad Asgher, Umer |
author_facet | Mehmood, Nasir Umer, Muhammad Asgher, Umer |
author_sort | Mehmood, Nasir |
collection | PubMed |
description | ABSTRACT: In drilling process almost seventy percent time is spent in tool switching and moving the spindle from one hole to the other. This time travel is non productive as it does not take part in actual drilling process. Therefore, this non productive time needs to be optimized. Different metaheuristic algorithms have been applied to minimize this non productive tool travel time. In this study, two metaheuristic approaches, shuffled frog leaping algorithm (SFLA) and ant colony optimization (ACO) have been hybridized. In industry, the CAM softwares are employed for minimization of non productive tool travel time and it is considered that the path obtained by using the CAM softwares is the optimized path. However this is not the case in all problems. In order to show the contribution of the SFLA-ACO algorithm and to prove that results achieved through CAM softwares are not always optimized, hybrid SFLA-ACO algorithm has been applied to two drilling problems as case studies with the main objective of minimization of non productive tool travel time. The drilling problems which are taken from the manufacturing industry include ventilator manifold problem and lift axle mounting bracket problem. The results of hybrid SFLA-ACO algorithm have been compared with the results of commercially available computer aided manufacturing (CAM) software. For comparison purpose, the CAM softwares used are Creo 6.0, Pro E, Siemens NX and Solidworks. The comparison shows that the results of proposed hybrid SFLA-ACO algorithm are better than commercially available CAM softwares in both real world manufacturing problems. ARTICLE HIGHLIGHTS: Different optimization techniques are being used for optimization of drilling tool path problems. In this paper two techniques SFLA and ACO has been combined to form a hybrid SFLA-ACO algorithm and has been applied to the real world industrial problems. Two real world problems have been taken from the local manufacturing industries. In both the problems the objective is to optimize the tool traveling time through hybrid SFLA-ACO and compare it with CAM software. Four CAM softwares have been used for comparison purpose. The problems undertaken are solved through these CAM software and compared with the results of hybrid SFLA-ACO results. As result of comparison it is found that in both the problems the performance of hybrid SFLA-ACO algorithm remains outclass. This signifies that results of CAM software in case of optimization of drilling tool path are not always optimal and these can be improved by using different optimization techniques. |
format | Online Article Text |
id | pubmed-9857905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-98579052023-01-23 Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems Mehmood, Nasir Umer, Muhammad Asgher, Umer SN Appl Sci Research Article ABSTRACT: In drilling process almost seventy percent time is spent in tool switching and moving the spindle from one hole to the other. This time travel is non productive as it does not take part in actual drilling process. Therefore, this non productive time needs to be optimized. Different metaheuristic algorithms have been applied to minimize this non productive tool travel time. In this study, two metaheuristic approaches, shuffled frog leaping algorithm (SFLA) and ant colony optimization (ACO) have been hybridized. In industry, the CAM softwares are employed for minimization of non productive tool travel time and it is considered that the path obtained by using the CAM softwares is the optimized path. However this is not the case in all problems. In order to show the contribution of the SFLA-ACO algorithm and to prove that results achieved through CAM softwares are not always optimized, hybrid SFLA-ACO algorithm has been applied to two drilling problems as case studies with the main objective of minimization of non productive tool travel time. The drilling problems which are taken from the manufacturing industry include ventilator manifold problem and lift axle mounting bracket problem. The results of hybrid SFLA-ACO algorithm have been compared with the results of commercially available computer aided manufacturing (CAM) software. For comparison purpose, the CAM softwares used are Creo 6.0, Pro E, Siemens NX and Solidworks. The comparison shows that the results of proposed hybrid SFLA-ACO algorithm are better than commercially available CAM softwares in both real world manufacturing problems. ARTICLE HIGHLIGHTS: Different optimization techniques are being used for optimization of drilling tool path problems. In this paper two techniques SFLA and ACO has been combined to form a hybrid SFLA-ACO algorithm and has been applied to the real world industrial problems. Two real world problems have been taken from the local manufacturing industries. In both the problems the objective is to optimize the tool traveling time through hybrid SFLA-ACO and compare it with CAM software. Four CAM softwares have been used for comparison purpose. The problems undertaken are solved through these CAM software and compared with the results of hybrid SFLA-ACO results. As result of comparison it is found that in both the problems the performance of hybrid SFLA-ACO algorithm remains outclass. This signifies that results of CAM software in case of optimization of drilling tool path are not always optimal and these can be improved by using different optimization techniques. Springer International Publishing 2023-01-20 2023 /pmc/articles/PMC9857905/ /pubmed/36712556 http://dx.doi.org/10.1007/s42452-022-05271-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Mehmood, Nasir Umer, Muhammad Asgher, Umer Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems |
title | Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems |
title_full | Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems |
title_fullStr | Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems |
title_full_unstemmed | Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems |
title_short | Application of hybrid SFLA-ACO algorithm and CAM softwares for optimization of drilling tool path problems |
title_sort | application of hybrid sfla-aco algorithm and cam softwares for optimization of drilling tool path problems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857905/ https://www.ncbi.nlm.nih.gov/pubmed/36712556 http://dx.doi.org/10.1007/s42452-022-05271-x |
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