Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems

Manufacturing industry is now moving forward rapidly towards reconfigurability and reliability to meet the hard-to-predict global business market, especially job-shop production. However, even there is a proper planned schedule for production, and there is also technique for scheduling in Reconfigur...

Full description

Saved in:

Bibliographic Details
Main Author:	Tan, Joe Yee
Format:	Thesis
Language:	English English
Published:	2022
Subjects:	T Technology (General) TS Manufactures
Online Access:	http://eprints.utem.edu.my/id/eprint/26973/1/Optimization-based%20simulation%20algorithm%20for%20predictive-reactive%20job-shop%20scheduling%20of%20reconfigurable%20manufacturing%20systems.pdf http://eprints.utem.edu.my/id/eprint/26973/2/Optimization-based%20simulation%20algorithm%20for%20predictive-reactive%20job-shop%20scheduling%20of%20reconfigurable%20manufacturing%20systems.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utem-ep.26973
record_format	uketd_dc
spelling	my-utem-ep.269732024-01-16T11:37:23Z Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems 2022 Tan, Joe Yee T Technology (General) TS Manufactures Manufacturing industry is now moving forward rapidly towards reconfigurability and reliability to meet the hard-to-predict global business market, especially job-shop production. However, even there is a proper planned schedule for production, and there is also technique for scheduling in Reconfigurable Manufacturing System (RMS) but jobshop production will always come out with errors and disruption due to complex and uncertainty happening during the production process, hence fail to fulfill the due-date requirements. This study proposes a generic control strategy for piloting the implementation of a complex scheduling challenge in a RMS. This study is aimed to formulate an optimization-based algorithm with simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. Predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. This research also provided some results in combining the rule-based simulation with optimization: first, a feasible schedule was computed and then fine-tuned with the rule-based simulation system, then tested with RMS which is the reactive part. Simulation experiments were run using different parameters to analyze the performance of the proposed algorithm with the system. The results showed that the proposed optimizationbased algorithm had successfully reduce the throughput time of the system. In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm. 2022 Thesis http://eprints.utem.edu.my/id/eprint/26973/ http://eprints.utem.edu.my/id/eprint/26973/1/Optimization-based%20simulation%20algorithm%20for%20predictive-reactive%20job-shop%20scheduling%20of%20reconfigurable%20manufacturing%20systems.pdf text en public http://eprints.utem.edu.my/id/eprint/26973/2/Optimization-based%20simulation%20algorithm%20for%20predictive-reactive%20job-shop%20scheduling%20of%20reconfigurable%20manufacturing%20systems.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=122230 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Manufacturing Engineering Abdul Rahman, Azrul Azwan
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Abdul Rahman, Azrul Azwan
topic	T Technology (General) TS Manufactures
spellingShingle	T Technology (General) TS Manufactures Tan, Joe Yee Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
description	Manufacturing industry is now moving forward rapidly towards reconfigurability and reliability to meet the hard-to-predict global business market, especially job-shop production. However, even there is a proper planned schedule for production, and there is also technique for scheduling in Reconfigurable Manufacturing System (RMS) but jobshop production will always come out with errors and disruption due to complex and uncertainty happening during the production process, hence fail to fulfill the due-date requirements. This study proposes a generic control strategy for piloting the implementation of a complex scheduling challenge in a RMS. This study is aimed to formulate an optimization-based algorithm with simulation tool to reduce the throughput time of complex RMS, which can comply with complex product allocations and flexible routings of the system. Predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. This research also provided some results in combining the rule-based simulation with optimization: first, a feasible schedule was computed and then fine-tuned with the rule-based simulation system, then tested with RMS which is the reactive part. Simulation experiments were run using different parameters to analyze the performance of the proposed algorithm with the system. The results showed that the proposed optimizationbased algorithm had successfully reduce the throughput time of the system. In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Tan, Joe Yee
author_facet	Tan, Joe Yee
author_sort	Tan, Joe Yee
title	Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
title_short	Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
title_full	Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
title_fullStr	Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
title_full_unstemmed	Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
title_sort	optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Manufacturing Engineering
publishDate	2022
url	http://eprints.utem.edu.my/id/eprint/26973/1/Optimization-based%20simulation%20algorithm%20for%20predictive-reactive%20job-shop%20scheduling%20of%20reconfigurable%20manufacturing%20systems.pdf http://eprints.utem.edu.my/id/eprint/26973/2/Optimization-based%20simulation%20algorithm%20for%20predictive-reactive%20job-shop%20scheduling%20of%20reconfigurable%20manufacturing%20systems.pdf
_version_	1794023196777775104

Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems

Similar Items