Research on tool wear modeling of superalloy based on evolutionary cluster analysis

The utilization of the nickel-based superalloy GH4169 in the manufacturing of heat-resistant parts, such as aero-engine casings, blades and blisks, is prevalent due to its exceptional thermal fatigue strength, oxidation resistance and corrosion resistance. In spite of these favourable properties, GH4169 still poses challenges in machining, primarily due to its difficult-to-cut characteristics, which results in rapid tool wear and complex tool wear processes. Existing research efforts in the field of tool wear have mainly focused on establishing tool wear models based on wear mechanisms, field empirical or mathematical derivation to describe the tool wear process. Despite these efforts, the accuracy of the existing models in fitting the actual tool wear trend remains a challenge. This paper proposes a novel evolutionary cluster analysis method to analyse the evolution of tool wear, which serves as the theoretical basis for a more accurate tool wear model. Based on the evolution law of different stages of tool wear obtained by evolutionary cluster analysis, this paper establishes a tool wear model that reflects the characteristics of the distribution of tool wear values and accurately fits the actual tool wear trend. The proposed model is experimentally validated on the GH4169 tool wear data, and the results show that the proposed model has advantages over existing models in machining GH4169.