| Title | An Efficient Fuzzy Logic Modelling of TiN Coating Thickness |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Abu-Khadrah, Ahmed |
| Conference Name | 2022 International Conference on Business Analytics for Technology and Security (ICBATS) |
| Keywords | Analytical models, CCD, Coating Thickness, cutting tools, Fuzzy logic, Metrics, Physical vapor deposition, Predictive models, pubcrawl, PVD, resilience, Resiliency, security, Tin, Titanium |
| Abstract | In this paper, fuzzy logic was implemented as a proposed approach for modelling of Thickness as an output response of thin film layer in Titanium Nitrite (TiN). The layer was deposited using Physical Vapor Deposition (PVD) process that uses a sputtering technique to coat insert cutting tools with TiN. Central cubic design (CCD) was used for designing the optimal points of the experiment. In order to develop the fuzzy rules, the experimental data that collected by PVD was used. Triangular membership functions (Trimf) were used to develop the fuzzy prediction model. Residual error (e) and prediction accuracy (A) were used for validating the result of the proposed fuzzy model. The result of the developed fuzzy model with triangular membership function revealed that the average residual error of 0.2 is low and acceptable. Furthermore, the model obtained high prediction accuracy with 90.04%. The result revealed that the rule-based model of fuzzy logic could be an efficient approach to predict coatings layer thickness in the TiN. |
| DOI | 10.1109/ICBATS54253.2022.9759094 |
| Citation Key | abu-khadrah_efficient_2022 |
An Efficient Fuzzy Logic Modelling of TiN Coating Thickness