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A narrow size distribution of irregular aluminium particles was blended into power cable insulation grade polyethylene. Some batches of the resulting material were then melt-filtered to reduce the size of particles present and narrow the distributions further. The failure statistics of the loaded polymers were then determined under AC ramped stress. density of defect can clearly be identified. In addition, for the filtered material, a minimum breakdown field can be associated with a given filter size: a result of commercial importance. Some indications exist to suggest that different modes of failure operate at high and low fields. Candidates for these modes are analysed and discussed in terms of the distributions of defects present. Local field enhancement due to the included flaws were calculated using finite-element techniques.The results are compared with a percolation model of breakdown. Predictions are found to quantify accurately the reduction in the characteristic strength of the material over the narrow range of defect concentrations examined.

Adaptive smart machining has tremendous potential to render machining processes some level of intelligence and smartness. This article presents the concept and innovative use of adaptive smart machining through the adaptive control by constraints system, based on feed rate adjustment to modify the orthogonal cutting force, measured by a smart cutting tool developed by the authors. The advantage of using a smart cutting tool encompasses not only low cost, light weight and compact size, but also within the desired force range it will enhance the cutting tool life and smart machining and hence improve productivity and reliability in adaptive machining applications.

Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo (FTS) and smart collets for ultraprecision and micro manufacturing purposes. Implementation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation techniques are presented focusing on: (a) plug-and-produce design principle and the associated smart control algorithms, (b) piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, (c) critical cutting temperature control in real-time machining, (d) inprocess calibration through machining trials, (e) FE-based design and analysis of smart cutting tools, and (f) application exemplars on adaptive smart machining.

This paper presents an innovative design of a smart cutting tool, using two surface acoustic wave (SAW) strain sensors mounted onto the top and side surface of the tool shank respectively, and its implementation and application perspectives. This surface acoustic wave -based smart cutting tool is capable of measuring the cutting force and the feed force in a real machining environment, after a calibration process under known cutting conditions. A hybrid dissimilar workpiece is then machined using the SAW -based smart cutting tool. The hybrid dissimilar material is made of two different materials, NiCu alloy (Monel) and steel, welded together to form a single bar; this can be used to simulate an abrupt change in material properties. The property transition zone is successfully detected by the tool; the sensor feedback can then be used to initiate a change in the machining parameters to compensate for the altered material properties.

The condition of a cutting tool is an important factor to ultraprecision machining processes. Tool wear has a strong influence on the cutting forces, resulting in poor surface roughness and dimensional tolerance of the workpiece, particularly in ultraprecision machining hard brittle materials. This article presents a cutting force–based analysis and correlative observations on diamond tool wear in machining of single-crystal silicon. The Daubechies wavelet (dB3, level 4) was employed to correlate standard deviation of magnitude on the decomposed cutting and radial forces with initial diamond tool wear. Moreover, the flank wear and the micro-fracture were observed using scanning electron microscopy on the respective flank face and rake face of the diamond cutting tool used. No crater wear was detected on the rake face of the diamond tool until cutting distance of up to 9 km.

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