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Thin-wall machining of monolithic parts allows better quality parts to be manufactured in less time. This brings advantages, particularly in inventory management and manufacturing efficiency. However, due to poor stiffness of thin-wall parts, deformation is more likely to occur in the machining process, which results in dimensional form errors. This paper describes a new methodology for prediction of wall deflection during machining thin-wall features with reduced analysis time from weeks to hours. The prediction methodology is based on a combination of the finite-element method and statistical analysis. It consists of a feature-based approach to parts creation, finite-element analysis of material removal, and statistical regression analysis of deflection associated with cutting parameters and component attributes. The prediction values have been validated by machining tests on titanium parts and show good agreement between simulation model and experimental data.

Metal matrix composite (MMC) is a combination of two or more materials in a metal matrix, and is being widely used nowadays due to its excellent properties. This paper presents the surface integrity of LM6 aluminum MMC when machined with two different cutting tools; high speed steel (HSS) and uncoated carbide. The experiments were carried out with a constant cutting speed, feed rate and axial depth of cut, but differ in the radial depth of cut under dry cutting conditions. Results indicated that machining LM6 with uncoated carbide cutting tools provides a lower surface roughness and fine surface profile compared to HSS cutting tools, due to its edge stability. A lower radial depth of cut produced a fine surface finish and vice versa. Most of the machined surface was dominated by the feed mark effect due to path overlap from the cutting tool. This study is expected to provide a database of suitable cutting tools and cutting parameters for machining MMC based materials.

Accuracy of machined component is one of the challenging tasks for manufacturer. In the aerospace industry, machining process is widely used for fabrication of unitized-monolithic component that contains a thin-walled structure. During machining, the cutting forces cause deflection to the thin-wall section, leading to dimensional form errors that cause the finished part to be out of specification or failure. Most of the existing research for machining thin-wall component only concentrated on the process planning and the effects of cutter geometric feature is often neglected. Tool geometric feature has a direct influence on the cutting performance and should not be neglected in the machining consideration. This paper reports on the effect of helix angle on the magnitude of wall deflection. The established effects will be used for the development of high performance cutting tool for specifically machining thin-wall component.

In an attempt to decrease weight, new commercial and military aircraft are designs with unitised monolithic metal structural components which contains of thinner ribs (i.e., walls) and webs (i.e., floors). Most of the unitised monolithic metal structural components are machined from solid plate or forgings with the start-to-finish weight ratio of 20:1. The resulting thin-walled structure often suffers a deformation which causes a dimensional surface error due to the action of the cutting force generated during the machining process. To alleviate the resulting surface errors, current practices rely on machining through repetitive feeding several times and manual calibration which resulting in long cycle times, low productivity and high operating cost. A finite element analysis (FEA) machining model is developed in this project to specifically predict the distortion or deflection of the part during end milling process. The model aims to provide an input for downstream decision making on error compensation strategy when machining a thin-wall unitised monolithic metal structural components. A set of machining tests have been done in order to validate the accuracy of the model and the results between simulation and experiment are found in a good agreement.

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