Moldability evaluation for molded parts, which is the basis of concurrent design, is a key design stage in injection molding design. By moldability evaluation the design problems can be found timely and an optimum pla...Moldability evaluation for molded parts, which is the basis of concurrent design, is a key design stage in injection molding design. By moldability evaluation the design problems can be found timely and an optimum plastic part design achieved. In this paper, a systematic methodology for moldability evaluation based on fuzzy logic is proposed. Firstly, fuzzy set modeling for six key design attributes of molded parts is carried out respectively. Secondly, on the basis of this, the relationship between fuzzy sets for design attributes and fuzzy sets for moldability is established by fuzzy rules that are based on domain experts’ experience and knowledge. At last the integral moldability for molded parts is obtained through fuzzy reasoning. The neural network based fuzzy reasoning approach presented in this paper can improve fuzzy reasoning efficiency greatly, especially for system having a large number of rules and complicated membership functions. An example for moldability evaluation is given to show the feasibility of this proposed methodology.展开更多
With the combination of a new theoretical formula, physical simulation experiments, the technology of artificial neural network and database, an intelligent system for the prediction of sheet metal drawing capability ...With the combination of a new theoretical formula, physical simulation experiments, the technology of artificial neural network and database, an intelligent system for the prediction of sheet metal drawing capability is constructed for the first time. A modified criterion for sheet metal drawing capability is proposed in this paper, namely, the Technological Limiting Drawing Ratio, TLDR = f(R, n, s, t, F, μ,r_d,r_p…). Based on the studies of other scholars, a new formula is derived to predict the TLDR in this paper. Then a series of orthogonal physical simulation experiments are designed to investigate the effect of technological parameters on the TLDR, and the results are analyzed in the paper. Then the predicting system is constructed with the combination of the theoretical formula, orthogonal experiments, the technology of artifocial neural network and database. The predicted results show good agreements with experimental data, so it can be used to avoid the blindness in the selection of sheet metal before stamping. The system operates under the Windows operating system, and it supports the mechanism of Client/Server as well as Intranet, so the system has high engineering value.展开更多
文摘Moldability evaluation for molded parts, which is the basis of concurrent design, is a key design stage in injection molding design. By moldability evaluation the design problems can be found timely and an optimum plastic part design achieved. In this paper, a systematic methodology for moldability evaluation based on fuzzy logic is proposed. Firstly, fuzzy set modeling for six key design attributes of molded parts is carried out respectively. Secondly, on the basis of this, the relationship between fuzzy sets for design attributes and fuzzy sets for moldability is established by fuzzy rules that are based on domain experts’ experience and knowledge. At last the integral moldability for molded parts is obtained through fuzzy reasoning. The neural network based fuzzy reasoning approach presented in this paper can improve fuzzy reasoning efficiency greatly, especially for system having a large number of rules and complicated membership functions. An example for moldability evaluation is given to show the feasibility of this proposed methodology.
文摘With the combination of a new theoretical formula, physical simulation experiments, the technology of artificial neural network and database, an intelligent system for the prediction of sheet metal drawing capability is constructed for the first time. A modified criterion for sheet metal drawing capability is proposed in this paper, namely, the Technological Limiting Drawing Ratio, TLDR = f(R, n, s, t, F, μ,r_d,r_p…). Based on the studies of other scholars, a new formula is derived to predict the TLDR in this paper. Then a series of orthogonal physical simulation experiments are designed to investigate the effect of technological parameters on the TLDR, and the results are analyzed in the paper. Then the predicting system is constructed with the combination of the theoretical formula, orthogonal experiments, the technology of artifocial neural network and database. The predicted results show good agreements with experimental data, so it can be used to avoid the blindness in the selection of sheet metal before stamping. The system operates under the Windows operating system, and it supports the mechanism of Client/Server as well as Intranet, so the system has high engineering value.
