Future research directions in the machining of Inconel 718

Inconel 718 is the most popular nickel-based superalloy, extensively used in aerospace, automotive and energy industries owing to its extraordinary thermomechanical properties. It is also notoriously a difficult-to-cut material, due to its short tool life and low productivity in machining operations. Despite significant progress in cutting tool technologies, the machining of Inconel 718 is still considered a grand challenge. This paper provides a comprehensive review of recent advances in machining Inconel 718. The progress in cutting tools' materials, coatings, geometries and surface texturing for machining Inconel 718 is reviewed. The investigation is focused on the most adopted tool materials for machining of Inconel 718, namely Cubic Boron Nitrides (CBNs), ceramics and coated carbides. The thermal conductivity of cutting tool materials has been identified as a major parameter of interest. Process control, based on sensor data for monitoring the machining of Inconel 718 alloy and detecting surface anomalies and tool wear are reviewed and discussed. This has been identified as the major step towards realising real-time control for machining safety critical Inconel 718 components. Recent advances in various processes, e.g. turning, milling and drilling for machining Inconel 718 are investigated and discussed. Recent studies related to machining additively manufactured Inconel 718 are also discussed and compared with the wrought alloy. Finally, the state of current research is established, and future research directions proposed.

Automated summary

Inconel 718 is a popular nickel-based superalloy extensively used in aerospace, automotive, and energy industries. However, machining of Inconel 718 remains challenging due to its short tool life and low productivity. Recent advances in cutting tool materials, coatings, geometries, and surface texturing for machining Inconel 718 have been reviewed, with a focus on the thermal conductivity of cutting tool materials. Process control based on sensor data for monitoring machining and detecting anomalies has been identified as crucial for machining safety critical components.