dc.contributor.author | Low Zen Shiang | |
dc.date.accessioned | 2008-09-05T01:00:41Z | |
dc.date.available | 2008-09-05T01:00:41Z | |
dc.date.issued | 2008-04 | |
dc.identifier.uri | http://dspace.unimap.edu.my/123456789/1948 | |
dc.description.abstract | The process of plasma enhanced chemical vapor deposition silicon nitride film which is used as barrier layer for the doped oxide in premetal dielectric (PMD) application and optimized using Design of Experiment (DOE) approach. Design of Experiment (DOE) is a technique for optimizing process which has controllable inputs and measurable outputs. The input parameters selected are as RF powers, Pressure, 5 % SiH4/Ar gas ratio, and Nitrogen (N2) flow rates; while the output parameters are deposition rate and refractive index. The data were simulated in statistical software which is “Design Expert” to obtain the optimum combination of parameters with an acceptable deposition rates of 250Å and achieved refractive index in the range of 1.8 to 2.2. The optimum parameter of PECVD nitride process generated using DOE software which is Design Expert are, 5% SiH4/Ar gas ratio of 80 sccm, nitrogen (N2) flow rates of 310 sccm, pressure of 1000 mTorr and RF power of 60 Watt. Lastly, there is slightly difference between the actual experiments with the prediction of software of optimum parameter. Since the percentage of difference is considered low, therefore it is useful to
improve the productivity in semiconductor process with the approach of Design of
Experiment (DOE) using Taguchi Method. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Perlis | en_US |
dc.subject | Silicon | en_US |
dc.subject | Silicon nitride | en_US |
dc.subject | Microelectronics -- Materials | en_US |
dc.subject | Chemical Vapor Deposition (CVD) | en_US |
dc.subject | Taguchi method | en_US |
dc.subject | Semiconductors | en_US |
dc.title | Optimization of Nitride deposition process using Taguchi method | en_US |
dc.type | Learning Object | en_US |
dc.contributor.advisor | Noraini Othman (Advisor) | en_US |
dc.publisher.department | School Of Microelectronic Engineering | en_US |