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Proper selection of manufacturing conditions is one of the most important aspects in Ultrasonic Machining process, as these conditions determine the Material Removal Rate (MRR). In this work, two very popular mathematical models proposed by Miller and Shaw have been investigated using Monte Carlo simulation based Crystal Ball analysis tool. Effects of abrasive particle size, particle concentration, amplitude of tool vibration, tool radius and depth of hole on MRR have been analyzed for both models. Miller’s model indicates a strong positive relationship between abrasive grain size, concentration and MRR. Contrary to the literature search on experimental data, Shaw’s mathematical model indicates a negative relationship between MRR and grain size, and a very weak relationship between MRR and concentration. No definite relationship could be established between either tool radius and MRR or amplitude and MRR. A negative relationship between depth of hole and MRR was obtained for Shaw’s model.

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This work describes a strategy to reduce the cost associated with poor quality, by reducing the parts per million defects by Defining, Measuring, Analyzing, Implementing and Controlling (DMAIC) the production process. The method uses a combination of principles of Six Sigma applications, Lean Manufacturing and Shanin Strategy. The process has been used in analyzing the manufacturing lines of a brake lever at a Connecticut automotive components manufacturing company for reducing the cost associated with the production of nonconforming parts. The analysis was carried out with the help of the data collected on nonconformance parts and the application of phase change rules from DMAIC (+). Data analysis was carried out on statistical process control softwares, MINITAB and SPC XL 2000. Although, the problem of tight bushing existed on only one line of the brake lever assembly, this problem solving approach has solved the tight bushing problems on all assembly and alternates lines in a time- and cost-effective way.

A coordinate measuring machine with a suitably small probe can be used to measure micro-features such as the diameter and form of small holes (often about 100 μm in diameter). When measuring small holes, the clearance between the probe tip and the part is sometimes nearly as small as other characteristic lengths (such as probe deflection or form errors) associated with the measurement. Under these circumstances, the basic geometry of the measurement is much different than it is for the measurement of a macroscopic object. Various geometric errors are greatly magnified, and consequently sources of error that are totally irrelevant when measuring macroscopic artifacts can become important. In this article we discuss errors associated with misalignment or non-orthogonality of the probe axes, probe-tip radius compensation, and mechanical filtering.