Abstract: Quality function deployment (QFD) is a well-known customer-driven methodology for new dryer product development, using house of quality (HOQ) to translate customer requirements into all developing stages of dryer products. To solve the QFD problem of conventional dryers, the artificial intelligence theory is introduced in QFD to form new concept, namely intelligent QFD (IQFD). As a key to IQFD, the technology of dryers' HOQ temple automatic generation is studied in depth so as to set up a relevant model based on the radius basis function and artificial neural network (RBF-ANN). An illustrative example shows that the proposed model can convert customer requirements into corresponding engineering characteristics automatically as supported by the knowledge and date bases. As a result, the complication in application of dryers' QFD lowers and the dependence on experience and knowledge of design team is reduced, thus improving deployment efficiency and taking fully the advantage of QFD.