Aiming at the problem that the prominent features of hesitancy and fuzziness of decision information and it′s difficult to use the traditional method to determine the varieties of spare parts for new equipment of small scale, a method of determining the varieties of spare parts based on hesitating fuzzy rough sets was proposed. The risk preference coefficient was used to extend the incomplete hesitancy information, which laid a foundation for establishing the hesitancy information system for different risk preference. Considering the influence of the score function and the numerical continuation boundary, an improved inclusion degree formula was given and proved on the basis of the definition of inclusion degree. The reduction condition and rule acquisition method of spare parts varieties decision attribute based on the improved inclusion calculation were given, which realized the depth mining and effective utilization of hesitancy and decision information. The results show that this method can deal with hesitancy and decision information effectively, and obtain a simplified and practical decision rule set of spare parts varieties, and the feasibility of the method was verified.