Search for: All records

The rapid wear and premature failure of the cutting tool are prone to happen due to increased forces during machining difficult-to-cut materials such as Inconel 718. The application of alternative toolpath such as trochoidal milling has significantly improved tool life and reduced the overall cycle time of the process. The wear pattern of the tool has a direct impact on the cutting forces, which increases with tool deterioration. The cutting forces in milling are modeled through the mechanistic force model and can be designated through a set of force coefficients, i.e. cutting and edge representing the shearing and ploughing phenomenon of metal removal. It has been established in the literature that tool wear has a considerable effect on the value of edge force coefficients. This paper aims to determine the in-process edge force coefficients for the trochoidal toolpath and correlates them with the corresponding flank wear area. The proposed correlation will further assist in predicting the level of flank wear area based on the force values in trochoidal milling. 

Nickel-based superalloys belong to a category of material employed for extreme conditions and exhibit high strength properties at elevated temperatures that result in poor machinability. Machining such di cult-to-cut materials like Inconel 718 leads to a high rate of tool wear, and therefore trochoidal milling toolpath is used to improve productivity and tool life. The current study analyzes the evolution of the flank wear area of the tool during trochoidal milling of Inconel 718 using an image processing methodology. It is attempted by performing experimental studies until tool failure occurs at several cutting conditions. The machining is performed through several iterations on an identical cutting path, and the number of iterations to failure is recorded. The microstructural image of a flank wear area is captured upon each iteration and processed using an image processing algorithm. It is realized that the evaluation of flank wear area can be an e ective parameter to analyze tool wear. Also, the image processing methodology works e ectively and can be extended during real-time machining. 

The machining of nickel-based superalloys such as Inconel 718 still poses a great challenge. The high strength and temperature resistance of these materials lead to poor machinability, resulting in high process forces and extensive tool wear. However, this wear is stochastic when reaching a certain point and is di cult to predict. To generate consistent wear conditions, the tool wear can be decoupled from the milling process by creating artificial wear using grinding. In this paper, a multi-axis approach for decoupling tool wear is presented and analyzed. Therefore, scanning electron microscope images of di erent wear states – worn and artificially worn – are analyzed. In addition, the occurring process forces of naturally and contrived worn inserts are compared in orthogonal cutting experiments as an analogy setup. Finally, a finite element analysis using a novel methodology for segmenting relevant cutting edge sections using digital microscope images provides qualitative insights on the influence of different wear conditions.