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Milling of thin-walled aerospace structures is a critical process due to the high flexibility of the workpiece. Current practices in the fixture design and the choice of cutting parameters rely solely on conservative guidelines and the designer’s experience. This is a result of the lack of computationally efficient dynamic models to represent the dynamic response of the workpiece during machining, and the interaction between the workpiece, fixture and the cutting forces. This paper presents a novel dynamic formulation of typical thin-walled pockets encountered in aerospace structures. It is based on an analytical description of a five-sided pocket using a plate model. An off-line calibration of the model parameters, using global and local optimization, is performed in order to match the dynamic response of the pocket structure. The developed simplified model is based on Rayleigh’s energy method. Various pocket shapes are examined under different loading conditions and compared to finite element (FE) predictions and experimental results. In both cases, the results obtained by the developed model are in excellent agreement. This proposed approach resulted in one to two orders of magnitude reduction in computational time when compared to FE models, with a prediction error less than 10%.

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Many of the aerospace components are characterized by having pocket-shaped thin-walled structures. During milling, the varying dynamics of the workpiece due to the change of thickness affects the final part quality. Available dynamic models rely on computationally prohibitive techniques that limit their use in the aerospace industry. In this paper, a new dynamic model was developed to predict the vibrations of thin-walled pocket structures during milling while taking into account the continuous change of thickness. The model is based on representing the change of thickness of a pocket-structure with a two-directional multispan plate. For the model formulation, the Rayleigh–Ritz method is used together with multispan beam models for the trial functions in both the x- and y-directions. An extensive finite element (FE) validation of the developed model was performed for different aspect ratios of rectangular and nonrectangular pockets and various change of thickness schemes. It was shown that the proposed model can accurately capture the dynamic effect of the change of thickness with prediction errors of less than 5% and at least 20 times reduction in the computation time. Experimental validation of the models was performed through the machining of thin-walled components. The predictions of the developed models were found to be in excellent agreement with the measured dynamic responses.

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Drilling of stacks poses great challenges due the heterogeneity and abrasiveness of the composites, the chip evacuation through the stack, in addition to the difference in properties between the metallic and the composite materials. The objective of this paper is to investigate the effect of drilling conditions such as tool material and geometry and lubrication mode on the hole quality as well as the tool wear in drilling of composite stacks (Carbon Fiber Reinforced Plastics CFRP-Aluminum). The thickness of each material was 19 mm. A 2-flute uncoated drill was used. Four different cooling modes were applied namely dry, minimum quantity lubrication (MQL) with low pressure (<1.5 bar) and high flow rate (400 ml/hr), MQL with high pressure (4.25 bars) and low flow rate (10 ml/hr), and finally flood cooling. The process control parameters, namely the forces and temperatures were measured using a special fixture design using a Kistler dynamometer and a reflective system with an infrared camera. The quality of the holes was compared in terms of delamination, surface roughness, circularity, concentricity, and diameter errors. The resultant cutting forces were found to be much lower than the thrust forces. The mean forces in the Aluminum were more than double those in the CFRP. Negligible tool wear was observed (less than 60 μm). No indication of thermal damage was found on the circumference of the holes in all the tested conditions. Due to the fact that the CFRP was supported by the Aluminum stack, the exit of the holes was mostly free from delamination. The dry and flood conditions produced holes free from entry delamination, while the holes drilled with MQL had delamination within 24% of the hole diameter. Both MQL cooling modes resulted in comparable temperatures, forces and hole quality.

Optimum selection of cutting conditions in high-speed and ultra-precision machining processes often poses a challenging task due to several reasons; such as the need for costly experimental setup and the limitation on the number of experiments that can be performed before tool degradation starts becoming a source of noise in the readings. Moreover, oftentimes there are several objectives to consider, some of which may be conflicting, while others may be somewhat correlated. Pareto-optimality analysis is needed for conflicting objectives; however the existence of several objectives (high-dimension Pareto space) makes the generation and interpretation of Pareto solutions difficult. The approach adopted in this paper is a modified multi-objective efficient global optimization (m-EGO). In m-EGO, sample data points from experiments are used to construct Kriging meta-models, which act as predictors for the performance objectives. Evolutionary multi-objective optimization is then conducted to spread a population of new candidate experiments towards the zones of search space that are predicted by the Kriging models to have favorable performance, as well as zones that are under-explored. New experiments are then used to update the Kriging models, and the process is repeated until termination criteria are met. Handling a large number of objectives is improved via a special selection operator based on principle component analysis (PCA) within the evolutionary optimization. PCA is used to automatically detect correlations among objectives and perform the selection within a reduced space in order to achieve a better distribution of experimental sample points on the Pareto frontier. Case studies show favorable results in ultra-precision diamond turning of Aluminum alloy as well as high-speed drilling of woven composites.