Mandibular fractures are common facial lesions typically treated with titanium plate and screw systems; nevertheless, this material is associated with secondary effects. Absorbable material for implants is an alternative to titanium, but there are also problems such as incomplete screw insertion and screw breakage due to high pretension in the screw caused by the insertion torque. The purpose of this paper is to find the optimal screw pretension (SP) in absorbable plate and screw systems by means of artificial neural network (ANN) and its inverse (ANNi). This optimal SP must satisfy a desired maximum von Mises strain (MVMS). For training the ANN, a database was generated by means of a design of experiments (DOE). Each DOE configuration was solved by means of finite element method (FEM) calculations. To obtain the optimal value for (SP) in the mini absorbable screw for fracture fixation, a strategy to invert the ANN is developed. Using the ANN coefficients, a sensitive study was performed to identify the influence of the design parameters in the MVMS. The optimal SP obtained was 14.9742 N. The MVMS condition was satisfied with an error less than 1.1% in comparison with FEM and ANN results. The screw shaft length is the most influencing MVMS parameter.

The purpose of this work was to analyze the effect of the side cutting-edge angle on the surface roughness of aluminum 1350 in a turning operation. A Taguchi design L32 was used in this work; the control variables were spindlespeed, feed rate, depth of cutting and the side cutting-edge angle. Several metal cutting experiments and statistical tests provide evidence that the side cutting-edge angle significantly affects the surface roughness with a Statistical F equal to 24.96, mainly, when the side cutting-edge angle is maintained at high level; in this study, the high level was kept to 5.0 degrees. Also, when the high level condition is kept, it causes a major variation of the residual values; consequently, the surface roughness of the workpiece falls out of the specifications demanded by customers.Moreover, the best combination of the cutting parameters for a minimum surface roughness equal to 23.5 μin wasobtained. Finally, further research directions are presented.

Corrosion fatigue is an accelerated failure mechanism in metallic components and coated systems, where the effectiveness of the polymer coating is determined by the structural integrity and adhesion at the coating/substrate interface. This study investigated the corrosion fatigue interaction in AISI 410 steel with and without a poly(3-hexylthiophene)/poly (methyl methacrylate) (P3HT/PMMA) coating exposed to a 3 wt.% NaCl solution under four stress levels $\left(∆\sigma \right)$ at room temperature. Electrochemical noise (EN) was recorded during the test, the surface and interface were characterized using scanning electron microscopy (SEM), and the mechanical behavior was quantified using $da/dN$ vs. $∆K$ and $\sigma$ vs. N curves. The coated samples exhibited a wider potential range ($\approx \pm$400 mV) than the uncoated steel ($\approx \pm$200 mV), indicating localized electrochemical activity under the coating. SEM observations revealed microblisters at low stress levels and coating cracking at high stress levels, with localized substrate exposure, slip bands, and microcracks. Overall, the results showed that the corrosion fatigue is governed by electrochemical activity under the coating and cathodic delamination, which reduces adhesion, locally exposes the steel, and causes the initiation and propagation of cracks.