Characterization and prediction of overheating during milling of Al7050 alloy
摘要
Overheating of age-hardened 7xxx aluminum alloys may occur during machining and induce local microstructural modifications, leading to reductions in hardness and potentially affecting component integrity. Although such thermal degradation has been reported in several manufacturing processes, the occurrence and consequences of overheating during milling remain poorly documented. This study proposes a Process Signature-based methodology to characterize, understand, and model overheating phenomena in Al7050-T7451. The approach combines two complementary experimental campaigns and numerical simulations to reconstruct the causal chain linking process loading, internal thermal state, and resulting material modifications. First, controlled friction-heating tests were conducted to generate a wide range of thermal exposures. Through inverse thermal identification and post-mortem characterization, the relationship between thermal state and resulting hardness and electrical conductivity was established. Results show that maximum subsurface temperature is a relevant indicator of overheating, and that temperatures exceeding 225 °C lead to measurable softening and conductivity variations. A second campaign based on instrumented helical milling was performed to characterize thermo-mechanical loadings during machining, with particular attention to chip clogging, identified as an aggravating factor increasing thermal power transmitted to the workpiece. The measured loadings were used as inputs to a simplified finite element model to estimate thermal fields and predict material modifications. Good agreement was obtained between predicted and experimental hardness and conductivity. The proposed hybrid experimental–numerical framework demonstrates the ability of the Process Signature methodology to reproduce overheating-induced material modifications during milling and provides a basis for predictive models dedicated to overheating risk assessment and process optimization.