DocumentCode :
1930819
Title :
Prediction of Hardness in Titanium Aluminium Nitride TiA1N Coating Process: A Review
Author :
Mohamad, Muhammad A. ; Haron, Habibollah ; Ali, Nor A.
Author_Institution :
Fac. of Comput. Sci. & Inf. Syst., Univ. Teknol. Malaysia, Skudai, Malaysia
fYear :
2012
fDate :
25-27 Sept. 2012
Firstpage :
111
Lastpage :
116
Abstract :
This paper reviewed on prediction of hardness performances for Titanium Aluminium Nitride (TiA1N) coating process. A new application in predicting the hardness performances of TiA1N coatings using a method called support vector machine (SVM) is investigated. TiA1N coatings are usually used in high-speed machining due to its excellent surface hardness and wear resistance. The TiA1N coatings were produced using Physical Vapour Deposition magnetron sputtering process. The coating process parameter will be selected as the input parameters and the hardness as an output of the process. There are several coating process parameters in TiA1N coating process but for this paper only three coating process parameter will be considered. A support vector machine model will be proposed to predict the coating hardness with respect to changes in input process parameters which are substrate sputtering power, bias voltage and temperature. In this paper, a literature survey concerning the prediction technique of TiA1N coating process is conducted in order to clarify their coating process and coating process parameters. The issues and trend in prediction of hardness performances for TiA1N coating process also discussed based on various perspectives.
Keywords :
aluminium compounds; coatings; hardness; sputter deposition; titanium compounds; wear resistance; TiAlN; bias voltage; high-speed machining; physical vapour deposition magnetron sputtering; sputtering power; support vector machine; surface hardness; titanium aluminium nitride coating; wear resistance.The; Computational intelligence; Computational modeling; PVD magnetron sputtering; Support Vector Machine; TiAlN coatings; hardness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on
Conference_Location :
Kuantan
ISSN :
2166-8531
Print_ISBN :
978-1-4673-3113-5
Type :
conf
DOI :
10.1109/CIMSim.2012.63
Filename :
6338055
Link To Document :
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