Coupling Taguchi experimental designs with deep adaptive learning enhanced AI process models for experimental cost savings in manufacturing process development.

The Aluminum alloy AA7075 workpiece material is observed under dry finishing turning operation. This work is an investigation reporting promising potential of deep adaptive learning enhanced artificial intelligence process models for L (63) Taguchi orthogonal array experiments and major cost saving potential in machining process optimization. Six different tool inserts are used as categorical parameter along with three continuous operational parameters i.

Fracture Toughness Characteristics of Stacked Bilayer Graphene via Far-Field Displacement Measurements.

Mechanical properties of graphene, e.g., strength, modulus, and fracture toughness are extremely sensitive to flaws.