Abstract
Processing accuracy is an important area studied in rapid prototyping (RP) research. It is mainly dependent on the processing parameters, material characteristics and many other factors. Studies on processing accuracy can be divided into two categories: in-plane processing accuracy and vertical processing accuracy (that determines the staircase on the surfaces of prototypes). This work focuses on the in-plane processing accuracy. Similar to laminated object manufacturing (LOM) process, slicing solid manufacturing (SSM) uses paper and CO2 laser as material and energy source, respectively. This paper introduces an integrated method that combines orthogonal experimental design and analysis, and neural network analysis to determine the optimal processing conditions. The key processing parameters and their degree of influences on the processing accuracy, and the quantitative relations between input parameters and output accuracy will be investigated. This method of experimental design and analysis is not only effective for the SSM process, but also applicable to other RP processes that use the principle of 3D layered manufacture.
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