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|Title:||Optimization of titanium nitride and chromium nitride PVD coating process for toolings||Authors:||Yim, Siu-lan||Keywords:||Hong Kong Polytechnic University -- Dissertations
|Issue Date:||2006||Publisher:||The Hong Kong Polytechnic University||Abstract:||In the last two decades, Cathodic Arc Physical Vapour Deposition (CAPVD) coating is widely used in cutting tools such as endmills, drills and cutting inserts. Many researches pointed out the advantages of using coated cutting tools for interrupting cutting. Some researches were carried out to investigate the influence of the bias voltage, arc current, and nitrogen pressure to coating structure, hardness, and surface morphology of coating for mainly cutting tool materials like tungsten carbide and high speed steel (HSS). However, no study was carried out to obtain the optimization windows for different kinds of CAPVD coating for moulds and dies. From previous researches, the optimization parameters of CAPVD were bias voltage, nitrogen pressure, acetylene pressure, coating thickness, and target composition. Two most popular coatings, titanium nitride (TiN) and chromium nitride (CrN) for Hong Kong moulds and dies industry, were selected for this study. The main apparatus was the PLATIT PL 50 of PLATIT AG cathodic arc deposition system. Ball crater was used to find the substrate coating thickness. And a surface profilometer was used for finding the mean roughness value (Ra). The Daimler-Benz Rockwell-C adhesion test method was used to investigate the adhesion of coating. After that, Scanning Electron Microscope was used to analyze the surface morphology of the coating. This study was aimed to find the optimal region for surface roughness of TiN and CrN coating. By using cause-and-effect diagram, the coating parameters that affect the coatings were identified. They are bias voltage, arc current, nitrogen pressure, and coating time. In this study, Taguchi method was used as screening experiment to find the near optimum region. For further optimization, the Response Surface Method (RSM) was used to help finding out the optimal region. First, a first-order model was determined. Then, steepest ascent experiments were used to obtain the middle point of the first-order regression model. After that a new first-order model was found. And finally, the second-order model was obtained. From Taguchi analysis of TiN coating, roughness test had been conducted for optimization. It was found that the bias voltage was the most critical factor to affect the roughness value whereas the arc current shows less interaction. For CrN coating, the nitrogen pressure was the most critical factor to affect roughness value whereas the coating time shows less interaction. From RSM analysis, for TiN coating, the optimal point was at (0.384, 0.091), where bias voltage = -115V and nitrogen pressure = 9.54 x 10E-03 mbar. And this point was a minimum point. For CrN coating, the optimal point was at (1.061, -0.063), where bias voltage = -121V and nitrogen pressure = 9.46 x 10E-03 mbar. And this was a minimum point. For future work, evolutionary solution is suggested to run RSM in a real production size and practice. Furthermore, a multi-characteristic response method using Taguchi method and utility concept together may help to find out the optimal condition when several characteristics are needed to consider at the same time.||Description:||xiv, [164, 14] leaves : ill. (some col.) ; 31 cm.
PolyU Library Call No.: [THS] LG51 .H577M ISE 2006 Yim
|URI:||http://hdl.handle.net/10397/3921||Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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