Flexible Manufacturing Process with Scheduling Algorithm Based on Distributed Fuzzy Control System Design Using MATLAB
Control Science and Engineering
Volume 4, Issue 1, June 2020, Pages: 1-7
Received: Apr. 18, 2020; Accepted: May 8, 2020; Published: May 21, 2020
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Authors
Hsu Myat Tin Swe, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Hla Myo Tun, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Maung Maung Latt, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar; Department of Electronic Engineering, Technological University (Taungoo), Taungoo, Myanmar
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Abstract
The paper mainly focuses on the development the flexible manufacturing process with scheduling algorithm based on distributed fuzzy control system design using MATLAB. The research problem in this study is to find the scheduling algorithm for autonomous control system for modern industries based on flexible manufacturing process. The solution for the main research problems is to utilize the fuzzy logic controller design for scheduling algorithm based on distributed situation. The objective of this research could be fulfilled to observe the flexible manufacturing process for modern industries. In this paper, an Individual fuzzy logic controller is designed for the DFC control of the Manufacturing Process. With the use of Distributed Fuzzy Control in the manufacturing, the result is more benefit in scheduling policies, resource management and on-time delivery and processing of work. The Fuzzy Logic Controller for each machine is constructed first and the FMP is demonstrated by using a sequence control and processing of three machines equipped with the design fuzzy logic controller. The main advantage is automatic scheduling of the system (fully intelligent). The high Flexibility of controller and Good resource management confirm that the Less Human intervention in real world application. The results in this analyses confirm that the developed scheduling algorithm would be applied in real world applications because the performance of the control system was met the outcomes from the experimental studies.
Keywords
Distributed Fuzzy Control (DFC), Flexible Manufacturing Process (FMP), Flexibility, Fuzzy Logic, Scheduling of Manufacturing System
To cite this article
Hsu Myat Tin Swe, Hla Myo Tun, Maung Maung Latt, Flexible Manufacturing Process with Scheduling Algorithm Based on Distributed Fuzzy Control System Design Using MATLAB, Control Science and Engineering. Vol. 4, No. 1, 2020, pp. 1-7. doi: 10.11648/j.cse.20200401.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Hamesh babu Nanvala, Use of Fuzzy Logic Approaches in Scheduling of FMS: A Review, 2011.
[2]
Anonymous, FMS and FMP. April 2008, http://www.wikipedia.com/History.html.
[3]
S. N. Sivanandam, S. Sumathi and S. N. Deepa, Introduction to Fuzzy Logic using MATLAB, 2007.
[4]
H. K. Shivanand, Flexible Manufacturing System, 2006.
[5]
Tsourveloudis, Fuzzy Surplus Based Distributed Control of Manufacturing System, 2006.
[6]
Steven. T. Karris, Introduction to Simulink® with Engineering Applications, 2006.
[7]
Dr. Fernando Gonzalez, Real-Time Control of Distributed Large Scale Flexible Manufacturing Systems, 2004.
[8]
Pramot Srinoi, A/Prof. Ebrahim Shayan, Dr. Fatemeh Ghotb, School of Mathematical Sciences, Scheduling of Flexible Manufacturing Systems Using Fuzzy Logic, 2008.
[9]
Anonymous, King Saud University, Distributed Control Systems, 2002.
[10]
J. J. A. Bakker. “DFMS: Architecture and implementation of a distribiited control system for FMS”, 1999.
[11]
Paolo Dadone, Fuzzy Control of Flexible Manufacturing Systems, 1997.
[12]
Anthony Angsana, Kevin M. Passino Member IEEE, Distributed Fuzzy Control of Flexible Manufacturing System, 1994.
[13]
Zhou Binghat, Xi Lifeng & Cat Jianguo, Knowledge-based decision support system for tool management in flexible manufacturing system, Journal of Systems Engineering and Electronics, Vol. 15, No. 4, 2004, pp. 537-541.
[14]
TUNG-KUAN LIU, YEH-PENG CHEN, AND JYH-HORNG CHOU, Solving Distributed and Flexible Job-Shop Scheduling Problems for a Real-World Fastener Manufacturer, IEEE Access, VOLUME 2, 2014, Digital Object Identifier 10.1109/ACCESS.2015.2388486.
[15]
XIAOGANG ZHANG, YULONG LI, YAN RAN, AND GENBAO ZHANG, A Hybrid Multilevel FTA-FMEA Method for a Flexible Manufacturing Cell Based on Meta-Action and TOPSIS, IEEE Access, VOLUME 7, 2019, Digital Object Identifier 10.1109/ACCESS.2019.2934189.
[16]
GAIYUN LIU, LINGCHUN ZHANG, YUTING LIU, YUFENG CHEN, ZHIWU LI, AND NAIQI WU, Robust Deadlock Control for Automated Manufacturing Systems Based on the Max-Controllability of Siphons, IEEE Access, VOLUME 7, 2019, Digital Object Identifier 10.1109/ACCESS.2019.2924021.
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