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Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module

This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segre...

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Main Authors: Koh J.S.P., Aris I.B., Ramachandaramurthy V.K., Bashi S.M., Marhaban M.H.
Other Authors: 22951210700
Format: Article
Published: 2023
Subjects:
Genetic algorithm
Multiple-head optical scanner
Artificial intelligence
Laser recording
Motion planning
Optimization
Scanning
Artificial intelligent
Comparison result
Crossover operator
Evolutionary approach
Optical scanners
Optical scanning systems
Performance optimizations
Reasoning process
Genetic algorithms
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id my.uniten.dspace-29751
record_format dspace
spelling my.uniten.dspace-297512023-12-28T16:08:43Z Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module Koh J.S.P. Aris I.B. Ramachandaramurthy V.K. Bashi S.M. Marhaban M.H. 22951210700 6603306751 6602912020 6603053704 57211599538 Genetic algorithm Multiple-head optical scanner Artificial intelligence Laser recording Motion planning Optimization Scanning Artificial intelligent Comparison result Crossover operator Evolutionary approach Optical scanners Optical scanning systems Performance optimizations Reasoning process Genetic algorithms This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. The main motivation for this study is to introduce and evaluate an advance new customized GA. Comparison results of different combinatorial operators and tests with different probability factors are shown. Also, proposed are the new modifications to existing crossover operator called DPPC (Dynamic Pre-Populated Crossover) together with modification of a simple crossover selection method, called BCS (Bi-Cycle Selection Method). The performance of the new operator called GA_INSP (GA Inspection Module) for a better evolutionary approach to the time-based problem has been discussed in the study. The representation approach has been implemented via a computer program in order to achieve optimized marking performance. This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. � 2006 Asian Network for Scientific Information. Final 2023-12-28T08:08:43Z 2023-12-28T08:08:43Z 2006 Article 10.3923/jas.2006.2201.2208 2-s2.0-33749128068 https://www.scopus.com/inward/record.uri?eid=2-s2.0-33749128068&doi=10.3923%2fjas.2006.2201.2208&partnerID=40&md5=117dbe1946f6cb225bfb3386f5cfb213 https://irepository.uniten.edu.my/handle/123456789/29751 6 10 2201 2208 All Open Access; Bronze Open Access; Green Open Access Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Genetic algorithm
Multiple-head optical scanner
Artificial intelligence
Laser recording
Motion planning
Optimization
Scanning
Artificial intelligent
Comparison result
Crossover operator
Evolutionary approach
Optical scanners
Optical scanning systems
Performance optimizations
Reasoning process
Genetic algorithms
spellingShingle Genetic algorithm
Multiple-head optical scanner
Artificial intelligence
Laser recording
Motion planning
Optimization
Scanning
Artificial intelligent
Comparison result
Crossover operator
Evolutionary approach
Optical scanners
Optical scanning systems
Performance optimizations
Reasoning process
Genetic algorithms
Koh J.S.P.
Aris I.B.
Ramachandaramurthy V.K.
Bashi S.M.
Marhaban M.H.
Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
description This research presents a new approach to optimise the performance of a multiple-beam optical scanning system in terms of its marking combinations and speed, using Genetic Algorithm (GA). The problem has been decomposed into two sub problems; task segregation, where the marking tasks need to be segregated and assigned for each scanner head and path planning where the best combinatorial paths for each scanner are determined in order to minimise the total motion of marking time. The knowledge acquired by the process is interpreted and mapped into vectors, which are kept in the database and used by the system to guide its reasoning process. The main motivation for this study is to introduce and evaluate an advance new customized GA. Comparison results of different combinatorial operators and tests with different probability factors are shown. Also, proposed are the new modifications to existing crossover operator called DPPC (Dynamic Pre-Populated Crossover) together with modification of a simple crossover selection method, called BCS (Bi-Cycle Selection Method). The performance of the new operator called GA_INSP (GA Inspection Module) for a better evolutionary approach to the time-based problem has been discussed in the study. The representation approach has been implemented via a computer program in order to achieve optimized marking performance. This algorithm has been tested and implemented successfully via a dual-beam optical scanning module. � 2006 Asian Network for Scientific Information.
author2 22951210700
author_facet 22951210700
Koh J.S.P.
Aris I.B.
Ramachandaramurthy V.K.
Bashi S.M.
Marhaban M.H.
format Article
author Koh J.S.P.
Aris I.B.
Ramachandaramurthy V.K.
Bashi S.M.
Marhaban M.H.
author_sort Koh J.S.P.
title Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_short Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_full Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_fullStr Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_full_unstemmed Design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
title_sort design, development and performance optimization of a new artificial intelligent controlled multiple-beam optical scanning module
publishDate 2023
_version_ 1806427790772273152
score 13.222552

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