Laser bending is an incremental sheet-metal forming process that offers the advantage of requiring no hard tooling, no external forces and easy clamping systems. The main limit of this process is represented by the low process productivity resulting from a small angle produced at each pass and a long time between consecutive passes to avoid surface oxidation either material melting. The present work analyses the productivity in multi-pass laser forming. Single and multi-pass laser forming experimental tests were conducted by high power diode laser to assess the influence of the main process conditions on bending angle and temperature. An Artificial Neural Network was developed to predict the bending angle and cooling time produced with different scanning schemes, i.e. laser power, speed, sheet thickness, cooling media and number of irradiations. On such basis, the effect of the process conditions on the productivity are discussed.
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