Automated Tool Condition Monitoring (TCM) often relies on additional sensors sensitive to tool wear to achieve robust machining processes. The need of additional sensors could impede the implementation of tool monitoring systems in industry due to the cost and retrofitting difficulties. This paper has investigated the use of existing position encoder signals to monitor a special face turning process with constant feed per revolution and machining speed. A signal processing method by converting encoder signals into a complex-valued form and a new vibration signature extraction method based on phase function were developed to analyze the encoder signals in the frequency domain. The cumulative spectrum indicated that the spectral energy would shift from the lower to the higher frequency band with increasing cutting load. The embedded vibration signatures extracted from the encoder signals provided additional detectability of the machining condition with distinguishable spectral modes. This paper confirms the sensitivity of the encoder signals and more signatures could be extracted for tool wear detection in the future work.

Automated Tool Condition Monitoring (TCM) often relies on additional sensors sensitive to tool wear to achieve robust machining processes. The need of additional sensors could impede the implementation of tool monitoring systems in industry due to the cost and retrofitting difficulties. This paper has investigated the use of existing position encoder signals to monitor a special face turning process with constant feed per revolution and machining speed. A signal processing method by converting encoder signals into a complex-valued form and a new vibration signature extraction method based on phase function were developed to analyze the encoder signals in the frequency domain. The cumulative spectrum indicated that the spectral energy would shift from the lower to the higher frequency band with increasing cutting load. The embedded vibration signatures extracted from the encoder signals provided real-time detectability of the machining condition with distinguishable spectral modes. The embedded vibration signatures extracted from the encoder signals provided additional detectability of the machining condition with distinguishable spectral modes. In particular, tool chipping manifested itself as significant amplitude changes at a specific frequency band 20-30 Hz in the extracted vibration signatures. A new monitoring metric based on the XY-plane modulations combined with statistical process control charts was proposed and shown to be a robust tool wear and tool wear rate indicator. The results show that when tool chipping occurred, it could be detected in real-time when this this tool wear rate value jumped in combination with breach of the control limits. This confirms that internal encoder signals, together with the proposed metric, could be a robust in-process tool wear monitor.

Although it is generally agreed that carbon is not wetted by liquid copper, the degree of rejection for a Single Wall Carbon Nanotube (SWCNT) has not been quantified. This paper presents Molecular Dynamics (MD) simulations to quantify the magnitude of resistance liquid copper imposes on a (5,5) SWCNT under static and dynamic intrusion scenarios. Two new sets of coefficients for the Morse potential model are proposed that better predict interfacial behavior between liquid copper and carbon. The proposed models, after being validated using empirically observed contact angle data for liquid copper and carbon, are used to investigate the wettability of a (5,5) single-walled carbon nanotube in liquid copper. It was found that the force required to submerge an initially un-wetted SWCNT into liquid copper under static conditions is higher than the expected force calculated from macro-scale fluid dynamic theory. The results indicate that a perturbation in the liquid copper surface reduces the force required for the SWCNTs to become incorporated in the liquid copper.

A new wet process, denoted as Laser Surface Implanting (LSI), has been developed to synthesize a Copper-Single Wall Carbon NanoTube (Cu-SWCNT) metal nanocomposite by dispersing SWCNTs into molten copper, followed by rapid and non-equilibrium solidification to form the Cu-SWCNT nanocomposite such that dispersed SWCNTs could locked in positions without agglomerating into large clusters. However, the nanometer sizes of the SWCNT clusters inside this nanocomposite make it extremely difficult to obtain TEM images with discernable SWCNT clusters in the copper matrix. In this paper, TEM images and their diffraction patterns for annealed pure copper, quenched pure copper (by the same synthesis process without introducing SWCNTs), and Cu-SWCNT nanocomposite are compared. It is concluded that TEM images with discernable SWCNT clusters are rare. Therefore, diffraction patterns are better tools to identify SWCNTs within the copper matrix. The indexed diffraction patterns confirm that the copper fcc lattice is preserved. However, the Cu-SWCNT nanocomposite samples also exhibit ordered diffuse scattering, consisting of at least two polyhedra of diffuse-scattering bounded by the 110* and 200* family of reciprocal lattice planes, respectively. In addition several samples exhibit super-lattice Bragg diffraction indicative expanded unit cells. It thus appears that the SWCNTs are incorporated into the Cu matrix with precise arrangements commensurate with specific Cu lattice planes. 

A copper-single-walled carbon nanotube (Cu-SWCNT) metal nanocomposite could be an ideal material if it can substantially improve the strength of copper while preserving the metal’s excellent thermal and electrical properties. However, synthesis of such a nanocomposite is highly challenging, because copper and SWCNTs do not form intermetallic compounds and are insoluble; as a result, there are serious issues regarding wettability and fine dispersion of SWCNTs within the copper matrix. In this paper we present a novel wet process, called the laser surface implantation process (LSI), to synthesize Cu-SWCNT nanocomposites by mixing SWCNTs into molten copper. The LSI process includes drilling several microholes on a copper substrate, filling the microholes with SWCNTs suspended in solution, and melting the copper substrate to create a micro-well of molten copper. The molten copper advances radially outward to engulf the microholes with pre-deposited SWCNTs to form the Cu-SWCNT implant upon solidification. Rapid and non-equilibrium solidification is achieved due to copper’s excellent heat conductivity, so that SWCNTs are locked in position within the copper matrix without agglomerating into large clusters. This wet process is very different from the typical dry processes used in powder metallurgy. Very high hardness improvement, up to 527% over pure copper, was achieved, confirmed by micro-indentation tests, with only a 0.23% SWCNT volume fraction. The nanostructure of the nanocomposite was characterized by TEM imaging, energy-dispersive x-ray spectroscopy mapping and spectroscopy measurements. The SWCNTs were found to be finely dispersed within the copper matrix with cluster sizes in the range of nanometers, achieving the goal of molecular-level mixing.