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Abstract Tool wear plays a decisive role in achieving the required surface quality and dimensional accuracy during the machining of Inconel 718-based products. The highly stochastic phenomenon of tool wear, particularly in later stages, results in difficulty in predicting the failure point of the tool. The present research work aims to study this late-stage wear of the tool by generating consistent wear conditions and thereby decoupling the late-stage wear from the wear history. To do so, a multi-axis grinding operation is employed to create artificial tool wear that replicates the topology of natural wear occurring in the process. In order to evaluate the imitating ability of the proposed methodology, microscopic images in different wear states of naturally and contrived worn tools were analyzed. The methodology was validated by comparing the resulting process forces measured during end milling with the natural and contrived worn tool for different path strategies. Finally, a qualitative finite element (FE) analysis was conducted, and specific force coefficients for worn tool segments were determined through simulation. 

The overall quality of a machined part relies heavily on the tool path that is used. Several methods of toolpath generation are currently employed. A more recently developed toolpath method is known as trochoidal milling, which is also known by several other terms, such as adaptive milling. This type of path benefits the machining process by attempting to reduce chip thickness on entry and exit to the workpiece. In doing so, utilization of this type of path can reduce tool wear and enables higher feed rates, thus improving machining efficiency.\par Another advantage of the trochoidal approach is that it often creates paths which are relatively more smooth compared to traditionally designed paths. In order to follow the contours of the final geometry, the path can yield a significant number of direction changes which result in constantly changing forces directions on the tool. Chatter, or self-excited vibration that occurs in the tool or workpiece, can therefore be mitigated or avoided since resonance does not have time to increase the vibration’s amplitude. The trochoidal milling tool path strategy typically operates on the XY plane. The operator will assign a step-down value, which defines the Z-depth at each pass. This strategy can create issues during freeform milling: because of this step-down effect, the trochoidal path may only be able to perform clearing and not finishing. This is due to the excess material left on the workpiece when a large step-down value is used. A significant and randomized variation range of the trochoidal path is tested in this research. Using this new proposed method, stochastic behavior of the toolpath is implemented. The toolpath consists entirely of circular arcs which drive the tool in a pseudo-random fashion. As the tool nears completion of the pass, the generator will give heavier probabilistic weight to points which have not yet been machined, thereby improving the efficiency of the process. It is hypothesized that this toolpath can generate the same chip-inhibiting properties of the trochoidal path while granting the ability to perform finishing cuts. The stability of such a path is determined in this work. A key parameter of this path is the allowable radius range of the circular arcs. For example, short, tight arcs or long, relatively straight arcs can be used. The influence of these arcs is analyzed against several different metrics, such as generation time, path efficiency, and chatter. The stability lobes for several radii parameters were determined. It was found that the most efficient path utilized a median parameter value, signifying a negative parabolic relationship between path efficiency and tool path radius. It was also discovered that smaller arcs result in decreased chatter. Future studies will explore the behaviors of this path when milling 3D surfaces. 

Tool wear in machining is generally observed as early and late stage tool wear. During early stage tool wear, the tool is rapidly worn during a break-in period, followed by a stable region of tool wear. After machining more material, the tool reaches late stage tool wear. At this point, tool wear becomes unstable; tool failure occurs quickly or it may take some time. Therefore, late stage tool wear represents a bifurcation point, making it difficult to predict tool wear past this point. Tool wear is well known to be stochastically influenced. Due to this effect, it is difficult to perform studies on late stage tool wear since machining tools will be affected differently up to this point, introducing unknown variables. A novel method is presented in this research which utilized artificial wear to reach late stage tool wear. This method, termed contrived tool wear, may be capable of reducing the stochastic tool wear that occurs during early stage tool wear. As an initial investigation, machining tool inserts were worn by taking several passes over a grinding wheel with the tool rotating in reverse. Several parameters were tested in attempt to match the natural worn state as close as possible. Subsequent to artificial wear, the inserts were used to machine IN718. The presented method of contrived wear was found to be a good approach, but could not sufficiently replicate the tool wear typically produced in IN718 machining. Future work should aim at implementing a multi-axis approach to enable grinding at various angles to the rake face of the insert. 

Abstract Tool wear in machining is generally observed as early and late stage tool wear. During early stage tool wear, the tool is rapidly worn during a break-in period, followed by a stable region of tool wear. After machining more material, the tool reaches late stage tool wear. At this point, tool wear becomes unstable; tool failure occurs quickly or it may take some time. Therefore, late stage tool wear represents a bifurcation point, making it difficult to predict tool wear past this point. Tool wear is well known to be stochastically influenced. Due to this effect, it is difficult to perform studies on late stage tool wear since machining tools will be affected differently up to this point, introducing unknown variables. A novel method is presented in this research which utilized artificial wear to reach late stage tool wear. This method, termed contrived tool wear, may be capable of reducing the stochastic tool wear that occurs during early stage tool wear. As an initial investigation, machining tool inserts were worn by taking several passes over a grinding wheel with the tool rotating in reverse. Several parameters were tested in an attempt to match the natural worn state as close as possible. Subsequent to artificial wear, the inserts were used to machine IN718. The presented method of contrived wear was found to be a good approach, but could not sufficiently replicate the tool wear typically produced in IN718 machining. Future work should aim at implementing a multi-axis approach to enable grinding at various angles to the rake face of the insert.