Wear monitoring of metal sheet stamping process driven by acoustic emission data

Abstract. The study addresses limitations related to mold wear during the stamping process, which impairs part quality due to the low predictability of wear, leading to increased production scrap and unreliable production schedules. To tackle these issues, a tool condition monitoring strategy driven by Acoustic Emission (AE) data is proposed for assessing the wear state of stamping molds. An integrated model for decomposing AE signals, employing the rolling decomposition method, is developed. This model eliminates the reliance on future data to avoid information leakage and is capable of monitoring critical wear indicators in stamping molds. The experimental phase, conducted in an industrial-grade stamping process setting, involved collecting degradation signals from healthy to fatigued states to verify the effectiveness of the proposed method. The outcomes indicate that the data-driven approach, utilizing AE signals, is efficient in monitoring stamping mold wear.