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In this study, we sought to enhance the cutting properties of the various blades by coating them with Zr- and Fe-based thin film metallic glasses (TFMGs) to a thickness of 234–255 nm via sputter deposition. In oil-repellency/sliding tests on kitchen blades, the sliding angle and friction forces were as follows: bare blades (31.6°) and (35 µN), Ti-coated blades (20.3°) and (23.7 µN), and Z-TFMG coated blades (16.2°) and (19.2 µN). Comparisons were conducted with bare blades and those with a Teflon coating (a low-friction material commonly used for the coating of microtome blades). We also found that the Teflon coating reduced the cutting forces of an uncoated microtome blade by ~80%, whereas the proposed Z-TFMG achieved a ~51% reduction. The Z-TFMG presented no indications of delamination after being used 30 times for cutting; however, the Teflon coating proved highly susceptible to peeling and the bare blade was affected by surface staining. These results demonstrate the efficacy of the TFMG coating in terms of low friction, non-stick performance, and substrate adhesion. The performance of Z-TFMG and F-TFMG was also evaluated in split-thickness skin graft surgery using dermatome blades aimed at elucidating the influence of TFMG coatings on the healing of surgical incisions. When tested repeatedly on hairless skin, the surface roughness of uncoated blades increased by approximately 70%, whereas the surface roughness of TFMG-coated blades increases by only 8.6%. In the presence of hair, the surface roughness of uncoated blades increased by approximately ~108%, whereas the surface roughness of TFMG-coated blades increases by only ~23%. By Day 7, the wounds produced using TFMG-coated blades were noticeably smaller than those produced using uncoated blades, and these effects were particularly evident in hairy samples. This is a clear demonstration of the efficacy of TFMG surface coatings in preserving the cutting quality of surgical instruments.

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Skilled welders can estimate and control the weld penetration based on weld pool observation. This implies that an advanced control system could be developed to control the penetration by emulating the decision making process of the human welder. In this paper a nonlinear dynamic model is established to correlate the process inputs (welding current and traveling speed) and weld penetration in Gas Tungsten Arc Welding (GTAW). An innovative 3D vision sensing system capable of measuring the weld pool characteristic parameters in real-time is utilized. Dynamic experiments are conducted under various welding conditions. Dynamic linear model is first constructed and the results are analyzed. The linear model is then improved by incorporating a nonlinear operating point modeled by Adaptive Neuro Fuzzy Inference System (ANFIS). It is found that the penetration state can be better modeled by the proposed ANFIS model.

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