Papers by Author: Yan Qun Huang

Abstract: Variant design is the main form of most manufacturing enterprises. In this paper, an extensible modular method is proposed to enable better and faster design. The structure module is set size inner-related, and then when the user requirements change, the key structural variables can be adjusted followed by the alterations of the driven sizes, also these alterations can be verified by the engineering analysis. Therefore, the product variant design process can be preceded effectively with the extensible modules.

Abstract: To enhance the ability and reliability of product variant design, an object-oriented framework was constructed using an extensible module/product class for setting up a modular design model. A module/product in a class was identified as an object by encapsulating the involved information as properties and the transforming or interaction activities as operations. This extensible object was gradually optimized through communications with other objects and integrations of design knowledge in five domains. These include Customer, Functional, Physical, Process and Engineering, which is a new domain introduced in this paper. The programmatic framework was implemented and successfully demonstrated using some typical machine tool products.

Abstract: To effectively determine the key parameters of a model for complex mechanical products like hydraulic forging press (HFP), design cases were analyzed, user requirements (URs) quantified, and important mechanical structural variables (SVs) addressed to identify the underlying relationships between URs and SVs. By including experts’ experiences, empirical models were mathematically built and verified basing on the linear regression theory, and then applied to estimate practical variable values. The programmatic framework presented for the preliminary design of a product was implemented and successfully demonstrated on the preliminary design of an HFP company.

Abstract: On the basis of thermal error experiment in CNC, the paper reaches a conclusion that at different sampling time, the thermal error model is different from each other. Therefore, this paper proposes a Stepped Approximation Modeling(SAM) Method on thermal error by improving the Multivariable Regression Analysis Modeling Method. The model examples are calculated and compared with presented experiments data. The results show that the SAM has a high accuracy in the thermal error modeling of CNC.