At some cutting conditions chips formed during high-speed face turning of nickel based alloys are re-bonded to the machined workpiece surface, even when coolant is applied. Unfortunately, chip-rebonding reduces surface quality, which leads to a shorter fatigue lives for machined parts. Although several researchers have documented this phenomenon and its effects, the root causes of this phenomenon is currently unknown. In order to determine the root causes of chip rebonding, past test samples exhibiting chip rebonding were first analyzed. Metallographic analysis revealed that the chip rebonding material is the same as the workpiece material and that the bonding is mechanically driven. Next, screening design of experiments (DOE) were completed to reliably reproduce chip rebonding in dry cutting cases. Chip rebonding detection and severity were measured using multiple equally spaced surface roughness measurements (Rt parameter). In addition, in-process cutting forces and tool wear measurements were recorded and compared. Finally Taguchi methods were applied to identify the key variables their influence on chip-rebonding. In dry cutting tests it was found that decreasing feed-rate while cutting at a constant cutting speed is the most influential factor in obtaining chip rebonding. High-speed video revealed that at lower feed-rates the chip curls back to the surface of workpiece, while at higher feed-rates the chip flows away from the cutting region with minimal curl. Additional testing performed verifies this theory.

The objective of this study is to examine the relationship between microstructure and material content at critical locations of used WC-Co ball-end mills. The performance of three similar tools was tested at identical cutting conditions. From each tool, three samples were cut from the same positions on the WC-Co ball-end mills at key locations. Scanning Electron Microscopy (SEM) was used for observation of the microstructure of material and three methods were used to determine the chemical compositions of each tool. The first method used to examine the chemical composition was Energy Dispersive Spectrometry (EDS). Higher accuracy chemical analysis using Wave Dispersive Spectrometry (Microprobe) techniques and Slice-Averaged Wet Chemistry (ICP) results were also completed to verify trends and chemical contents. The results of this study showed that the microstructure is closely related to the cobalt content. Moreover, cobalt losses resulting from the machining process as well as phenomena resulting in microstructure defects in the manufacturing stage of the carbide were evident in worse performing tools. Furthermore, differing grain-growth inhibitor contents of each tool might have led to additional performance differences.

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This paper presents a novel technique to estimate the temperature distribution of a milling tool during machining. In this study, heat generation during the machining process is estimated using cutting forces. We consider the heat to be time-dependent heat flux into the tool. In the proposed model, we discretize each rake face on a mill into several elements; each experiences time-dependent heat flux. Second, we calculate the time-dependent heat flux as several constant heat input starts at different time. Finally, we sum the temperature rise from each heat flux to obtain the overall temperature change. A similar concept is applied on the flank surface, where the flank wear area is modeled as an additional heat generation zone. Experimental results are presented to validate the developed model.