Manufacturing cost estimation based on similarity
Fangwei Ning, Yan Shi, Xiaomeng Tong, Maolin Cai, Weiqing Xu
Abstract
Accurate and rapid estimation of manufacturing costs can improve the competitiveness of manufacturers and optimize part design. Several factors affect the cost, including the part design model, machining processing progress, and materials. Extracting a unified dataset from the manufacturing information is complicated owing to different information expressions, such as geometrical-topological, digital, text, and symbol representations. This study proposed a manufacturing cost estimation method based on similarity. The main contribution of this study is the calculation of the similarity of manufacturing factors, particularly the similarity of 3D geometrical models: ① the geometrical-topological representations of a model was transformed into point cloud data and a point cloud similarity calculation method based on the implicit shape model was developed, from which the similarity of the 3D model of the part was obtained;② the manufacturing factors were transformed into digital representations and the similarity of these factors was calculated using Euclidean distance. The weights of these factors were determined using subjective weight coefficients and the similarity of the parts was obtained based on the weights. Finally, the manufacturing cost was estimated using the smoothing index method. The accuracy of the proposed method has a state-of-the-art effect compared to other methods.