Increasing demand for micro fabrication of parts and products in the electronics, computer, and biomedical industrial sectors has created the need to minimize conventional manufacturing systems and machine tools such as milling, turning, and grinding machines corresponding to their fabrication targets. Among existing micro-machining technologies, mechanical solid tool machining with miniaturized manufacturing systems is one of the important processing methods, and has a number of inherent advantages. These advantages include: significant reduction of required space and energy consumption for machine drive and atmosphere; the improvement of machine robustness against external error sources due to increasing thermal, static, and dynamic stabilities; increased accuracy due to decreased overall machine size; and a greater freedom in the selection of workpiece materials, the complexity of the product geometry, and the cost of investment. However, the miniaturization of manufacturing machines unavoidably reduces the available work volume, so there are limits to the possible reduction of machine size per each machine tool configuration. Therefore, optimizing the configuration and size selection is important in order to address competing issues at the functionality level of machine tools. In this research, an effective design strategy to ensure good microscale machine performance and to provide the proper dimensions of the miniaturized manufacturing systems without resorting to exhaustive prototyping was proposed. This systematic design strategy includes the formulation and optimization of machine form shape function in the context of positioning accuracy, machine thermal error, static error, dynamic error, and work volume for various configuration candidates. The sensitivity of the optimal machine size to the relative weighing of penalty function parameters is discussed in the context of a case study. The results of this work can quantitatively support the design, configuration, fabrication, and utilization of microscale manufacturing systems in achieving precision and work volume specifications.

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