Identificazione mediante metodo inverso e analisi dei dati delle leggi di comportamento meccanico dedicate alla simulazione numerica in condizioni di lavorazione. = Identification by inverse method and data analysis of mechanical behaviour laws dedicated to the numerical simulation under machining conditions.

This research study develops and validates an inverse identification algorithm framework that couples Python automation with Abaqus finite-element simulations and a Levenberg-Marquardt (LM) optimizer to optimize the material behaviour parameters (Johnson-Cook (J-C) constitutive law and the Taylor-Quinney (T-Q) heat fraction) for orthogonal cutting of PH martensitic stainless steels. The algorithm loop perturbs parameters, builds finite-difference sensitivities, updates with LM, and rewrites the input automatically, resulting in four machining output conditions across five undeformed chip thicknesses of Href = 0.10–0.25 millimetres (mm) for the chip thickness, tool-chip contact length, cutting force, and penetration force. In the absence of 15-5PH experimental machining data, validation was performed using 17-4PH numerical datasets with similar properties. The baseline (pre-optimized) simulation exhibits large residual error on average: 21.94% (chip thickness), 41.20% (contact length), 40.21% (cutting force), and 28.37% (penetration force), demonstrating that uncalibrated parameters are non-predictive for precision machining analysis. After optimization, mean errors for the chip thickness, tool-chip contact length, cutting force, and penetration force were drastically reduced to 0.49%, 4.35%, 0.34%, and 0.14%, respectively, with rapid, monotonic convergence of ≤5 iterations across all undeformed Chip Thickness (Hrefs). The best and worst residual errors were 0.053% for the 0.10 mm Href and 4.77% for the 0.25 mm Href. The resulting single parameter set generalizes from the 2D orthogonal configuration of different cut sections to a 3D validation, indicating readiness for predictive simulation that requires robust force and chip geometry, which is relevant for industrial purposes.