Advanced high strength steels are being increasingly used in the automotive industry to reduce weight and improve fuel economy. However, due to increased physical properties and chemistry of high strength steels, it is difficult to directly substitute these materials into production processes currently designed for mild steels. New process parameters and process-related issues must be developed and understood for high strength steels. Among all issues, endurance of the electrode cap is the most important. In this paper, electrode wear characteristics of hot-dipped galvanized dual-phase (DP600) steels and the effect on weld quality are firstly analysed. An electrode displacement curve which can monitor electrode wear was measured by a developing experimental system using a servo gun. A neuro-fuzzy inference system based on the electrode displacement curve is developed for minimizing the effect of a worn electrode on weld quality by adaptively adjusting input variables based on the measured electrode displacement curve when electrode wear occurs. A modified current curve is implemented to reduce the effects of electrode wear on weld quality using a developed neuro-fuzzy system.
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