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This paper describes an automated procedure developed for the identification of Johnson-Cook (JC) law material parameters and Coulomb friction coefficient at the tool-chip interface, in the specific case of metal cutting FE analysis. The procedure has been developed in iSight environment, through the integration between AdvantEdge metal cutting FE code and an appropriately selected optimization algorithm. The identification of JC and friction parameters, in fact, has been performed considering it as an optimization problem, in which the objective function is the numerical/experimental error function minimization (in the specific case, it is related to the forces and temperatures responses). The calibration and validation phases have been performed using forces and temperatures experimental data, collected in orthogonal cutting test on SAF2507 superduplex steel.

Nowadays achieving overall sustainability in industrial activities is the natural consequence of diminishing non-renewable resources and stricter regulations related to environment and occupational safety/health.In industrial sector, CO2 emissions derive both from direct and indirect emissions. The second type is due to the use of electricity and currently represents more than thirty percent of global amount. For this reason energy consumption reduction is critical aspect in several industrial environments. Power consumption reduction is possible by modifying manufacturing conditions, utilizing alternative technologies and increasing resource utilization rate.The current market demand is characterized by request of small lots with different characteristics, which requires a complex management of the manufacturing production flow.Production planning and scheduling models, arising in flexible manufacturing environments, allows to combine several aspects such as: technological questions (e.g.: minimize manufacturing times and costs) economic criteria (e.g.: maximize production rate) and environmental prospective (e.g.: emissions reduction). A good manufacturing scheduling allows to saturate the system, avoiding bottlenecks, by means of the adaptation of the plant productivity to the request one.In this paper, authors describe an optimization framework focused on the minimization of energy and production costs by means of an intelligent production scheduling. In order to assess the performances, different real case production scenarios, in which the manufacturing activity is mainly based on machining operations, have been analyzed. In this work, several technologies, with various capabilities, have been taken into account in order to perform production activities. In addition, the scheduling has the possibility of using production technologies with low environmental impact and lower productivity, where the increase of the activity duration does not deteriorate the system performance. In this way several production schedules are feasible and the main scheduling aim focuses in obtaining the required productivity to fulfill demand and minimize energy consumption.

Different parameters are used to evaluate the machined surface quality; roughness, residual stress and white layer are the most common factors that affect the surface integrity. Residual stress, in addition, are one of the main factors that influence the component fatigue life. Superficial residual stresses depend on different factors, such as cutting parameters and tool geometry. This article describes the development of an automated optimization procedure that allows the matching of a residual stress Target Profile by varying process parameters and tool geometry for a typical aeronautic superalloy, such as Waspaloy, for which a reliable numerical model has been developed for comparison to experimental data. The objective of this procedure is to maximize the Material Removal Rate under physical constraints represented by appropriate limits assigned to: Cutting Force, Thrust Force, Tool Rake Temperature and residual stress Target Profile. The developed optimization procedure has shown its effectiveness to match a given residual stress profile in accordance to process responses numerically evaluated.

Nowadays the main target in the automotive field is the realization of lightweight and safe components. In this way it is possible to reduce costs and improve fuel consumption and, at the same time, enhance passenger safety. The use of tailored blanks has increased considerably in the automotive industry. Tailored blanks are a combination of different thicknesses or different materials, obtained by welding together two or more blanks, used in particular in car body panels. A new requirement in the automotive sector is the application of aluminum tailored blanks. The main target of this paper is the development of accurate numerical models for bending tailored blanks made from thin aluminum sheets, joined by laser welding, without filler metal. The FE bending simulations have been carried out using an explicit solver. The accuracy of the numerical models has been estimated and improved through a comparison with the results from an experimental study. The experimental tests have been performed using bending testing equipment, designed and developed by the authors. Three different bending radii have been tested. Tailored blanks, used as specimens, have been made by laser welding of thin Al6061 sheets. The considered outputs, used for the numerical-experimental comparison, are the punch force and the bending angle. The experimental results have been compared with the numerical ones in order to verify the accuracy of the FE model related to thickness and radius variations.