Papers by Author: Jium Fang

Abstract: A new approach with adaptive network-based fuzzy inference systems (ANFIS) based on experimental designs was used to model and characterize the tribological behaviors of diamond-like carbon (DLC) films deposited by a magnetron sputtering system. An orthogonal array experiment was introduced and the effects of deposited parameters on the films were systematically explored. The films were analyzed by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). In this study, a group of highly developed hillock-like textures appeared and a lower wear volume loss became visible in the DLC films. Furthermore, the predicted values and experimental results, in which the ANFIS effectively predicts the tribological behaviors of the DLC films, are similar. It was experimentally confirmed the ANFIS predictions agreed with the experiments. Therefore, the experimental results demonstrate the tribological properties on DLC multilayer films are accurately predicted by ANFIS, thereby justifying the reliability and feasibility of the approach.

Abstract: This paper presents the optimal chromium nitride (CrN) deposited performance by tuning magnetic systems on die steel in PVD. The strength of magnetic fields was controlled by adjusting the gap distance between magnet sets and target surfaces of the unbalanced magnetic field of sputtering systems. In L18 orthogonal experiments, the effect of control factors were explored such as gap distance between magnet set and target surface (GDMT), target current, argon and nitrogen flow rate, DC pulse frequency, and work distance. Hardness and wear behavior of the CrN films were analyzed using a statistical method. The wear rate was estimated by Pappus’s theorem. Among the results, the Cr2N phase with the mixture crystallographic orientations of (111) and (002) exhibited better wear resistance than CrN(200) with a single preferential orientation. In addition, variance analysis exhibited the largest percentage contribution to friction coefficient in comparison with the other two properties of friction coefficient and GDMT, which showed that GDMT is extremely sensitive to friction coefficient.