This paper is aimed at developing a methodology to solve a multi-objective problem in robotic flexible assembly cells. The proposed methodology is based on three main steps: (1) scheduling of the RFACs using different common rules, (2) normalisation of the scheduling outcomes, and (3) selection of the optimal scheduling rules, using a fuzzy inference system. In this paper, four rules, namely short processing time, long processing time, earlier due date and random, are examined. Four objectives are considered simultaneously: scheduling length, total transportation time, utilisation rate and workload rate. A realistic case study is provided for demonstrating applicability of the suggested methodology. The results show that the methodology is practical and works in RFACs settings.
Published in | Automation, Control and Intelligent Systems (Volume 1, Issue 3) |
DOI | 10.11648/j.acis.20130103.11 |
Page(s) | 34-41 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2013. Published by Science Publishing Group |
Assembly Cells, Scheduling Rules, Fuzzy Logic, Robotics
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APA Style
Khalid Abd, Kazem Abhary, Romeo Marian. (2013). Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells. Automation, Control and Intelligent Systems, 1(3), 34-41. https://doi.org/10.11648/j.acis.20130103.11
ACS Style
Khalid Abd; Kazem Abhary; Romeo Marian. Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells. Autom. Control Intell. Syst. 2013, 1(3), 34-41. doi: 10.11648/j.acis.20130103.11
AMA Style
Khalid Abd, Kazem Abhary, Romeo Marian. Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells. Autom Control Intell Syst. 2013;1(3):34-41. doi: 10.11648/j.acis.20130103.11
@article{10.11648/j.acis.20130103.11, author = {Khalid Abd and Kazem Abhary and Romeo Marian}, title = {Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells}, journal = {Automation, Control and Intelligent Systems}, volume = {1}, number = {3}, pages = {34-41}, doi = {10.11648/j.acis.20130103.11}, url = {https://doi.org/10.11648/j.acis.20130103.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20130103.11}, abstract = {This paper is aimed at developing a methodology to solve a multi-objective problem in robotic flexible assembly cells. The proposed methodology is based on three main steps: (1) scheduling of the RFACs using different common rules, (2) normalisation of the scheduling outcomes, and (3) selection of the optimal scheduling rules, using a fuzzy inference system. In this paper, four rules, namely short processing time, long processing time, earlier due date and random, are examined. Four objectives are considered simultaneously: scheduling length, total transportation time, utilisation rate and workload rate. A realistic case study is provided for demonstrating applicability of the suggested methodology. The results show that the methodology is practical and works in RFACs settings.}, year = {2013} }
TY - JOUR T1 - Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells AU - Khalid Abd AU - Kazem Abhary AU - Romeo Marian Y1 - 2013/06/20 PY - 2013 N1 - https://doi.org/10.11648/j.acis.20130103.11 DO - 10.11648/j.acis.20130103.11 T2 - Automation, Control and Intelligent Systems JF - Automation, Control and Intelligent Systems JO - Automation, Control and Intelligent Systems SP - 34 EP - 41 PB - Science Publishing Group SN - 2328-5591 UR - https://doi.org/10.11648/j.acis.20130103.11 AB - This paper is aimed at developing a methodology to solve a multi-objective problem in robotic flexible assembly cells. The proposed methodology is based on three main steps: (1) scheduling of the RFACs using different common rules, (2) normalisation of the scheduling outcomes, and (3) selection of the optimal scheduling rules, using a fuzzy inference system. In this paper, four rules, namely short processing time, long processing time, earlier due date and random, are examined. Four objectives are considered simultaneously: scheduling length, total transportation time, utilisation rate and workload rate. A realistic case study is provided for demonstrating applicability of the suggested methodology. The results show that the methodology is practical and works in RFACs settings. VL - 1 IS - 3 ER -