Non-Reshuffle-Based Approach for Rescheduling of Flexible Manufacturing System
| Main Authors: | Zakaria, Zalmiyah; Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malaysia, Deris, Safaai; Faculty of Creative Technology and Heritage, Universiti Malaysia Kelantan, Karung Berkunci 01, 16300 Bachok, Kelantan, Malaysia, Othman, Muhamad Razib; Faculty of Computing, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor, Malay, Kasim, Shahreen; Soft Computing and Data Mining Centre, Faculty of Computer Science And Information Technology, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia |
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| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
International Journal on Advanced Science, Engineering and Information Technology
, 2017
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| Subjects: | |
| Online Access: |
http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/3464 http://insightsociety.org/ojaseit/index.php/ijaseit/article/view/3464/pdf_509 |
Daftar Isi:
- Scheduling and rescheduling play vital roles in ensuring the effectiveness of the production control in flexible manufacturing system (FMS). The failure of these systems may interrupt the efficiency of the production activities and thus may lessen the profit to be gained by the company. The FMS scheduling problem is considered as dynamic as new orders may get in every day. The new orders need to be immediately desegregated with the existing production schedule by preserving the efficiency and stability of the existing schedule. This research applies the non-reshuffle-based genetic match-up algorithms which admit new orders by manipulating available machine idle times to address rescheduling problem in a FMS that practises the pull strategy. The idea of the match-up approach is to update only a part of the initial schedule and genetic algorithms used to optimise the solution within the rescheduling horizon in such a way in order to preserve the efficiency and stability of the shop floor. The proposed methodology has been tested using different rescheduling parameters. The experiments show that the rescheduling method improves efficiency and stability of the new schedule.