Integrated control mechanism of electrical discharge machining system for higher material removal rate

A servo control system in Electrical Discharge Machining (EDM) system is a control system with an appropriate control algorithm to position electrode on a particular distance from workpiece during machining process. The gap between the electrode and the workpiece is in the range of 10 – 50 μm. This...

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Main Author:	Andromeda, Trias
Format:	Thesis
Language:	English
Published:	2015
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/77960/1/TriasAndromedaPFKE2015.pdf
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id	my-utm-ep.77960
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spelling	my-utm-ep.779602018-07-18T07:38:17Z Integrated control mechanism of electrical discharge machining system for higher material removal rate 2015-05 Andromeda, Trias TK Electrical engineering. Electronics Nuclear engineering A servo control system in Electrical Discharge Machining (EDM) system is a control system with an appropriate control algorithm to position electrode on a particular distance from workpiece during machining process. The gap between the electrode and the workpiece is in the range of 10 – 50 μm. This ideal gap is achieved by applying an appropriate control algorithm to the servo control system of the EDM, and maintaining this gap will improve the Material Removal Rate (MRR) during the machining process. A considerable number of unique methods were proposed in the control algorithm in order to bring the electrode to the optimum position. This research proposes a new method called Integrated Control Mechanism (ICM) to improve the MRR of the EDM system. A rotary encoder is used as an additional mechanical sensor for the feedback control system in order to limit the electrode movement. Modelling of EDM is further investigated to predict the MRR parameter and optimization of electrode control position. A Neural Network system is used to predict MRR where Particle Swarm Optimization (PSO) and Differential Evolution (DE) are studied and simulated to optimize the Proportional Integral Derivative (PID) control parameters for the EDM system. Research conducted shows that the proposed Feed Forward Artificial Neural Network improves the accuracy of prediction in determining MRR by 2.92% and PID parameter optimization is successfully applied either using PSO or DE. The ICM is successfully implemented and the result shows that MRR is higher when compared to the normal machining process. 2015-05 Thesis http://eprints.utm.my/id/eprint/77960/ http://eprints.utm.my/id/eprint/77960/1/TriasAndromedaPFKE2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:97174 phd doctoral Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Andromeda, Trias Integrated control mechanism of electrical discharge machining system for higher material removal rate
description	A servo control system in Electrical Discharge Machining (EDM) system is a control system with an appropriate control algorithm to position electrode on a particular distance from workpiece during machining process. The gap between the electrode and the workpiece is in the range of 10 – 50 μm. This ideal gap is achieved by applying an appropriate control algorithm to the servo control system of the EDM, and maintaining this gap will improve the Material Removal Rate (MRR) during the machining process. A considerable number of unique methods were proposed in the control algorithm in order to bring the electrode to the optimum position. This research proposes a new method called Integrated Control Mechanism (ICM) to improve the MRR of the EDM system. A rotary encoder is used as an additional mechanical sensor for the feedback control system in order to limit the electrode movement. Modelling of EDM is further investigated to predict the MRR parameter and optimization of electrode control position. A Neural Network system is used to predict MRR where Particle Swarm Optimization (PSO) and Differential Evolution (DE) are studied and simulated to optimize the Proportional Integral Derivative (PID) control parameters for the EDM system. Research conducted shows that the proposed Feed Forward Artificial Neural Network improves the accuracy of prediction in determining MRR by 2.92% and PID parameter optimization is successfully applied either using PSO or DE. The ICM is successfully implemented and the result shows that MRR is higher when compared to the normal machining process.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Andromeda, Trias
author_facet	Andromeda, Trias
author_sort	Andromeda, Trias
title	Integrated control mechanism of electrical discharge machining system for higher material removal rate
title_short	Integrated control mechanism of electrical discharge machining system for higher material removal rate
title_full	Integrated control mechanism of electrical discharge machining system for higher material removal rate
title_fullStr	Integrated control mechanism of electrical discharge machining system for higher material removal rate
title_full_unstemmed	Integrated control mechanism of electrical discharge machining system for higher material removal rate
title_sort	integrated control mechanism of electrical discharge machining system for higher material removal rate
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2015
url	http://eprints.utm.my/id/eprint/77960/1/TriasAndromedaPFKE2015.pdf
_version_	1747817873039949824

Integrated control mechanism of electrical discharge machining system for higher material removal rate

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