At present

the planners can only arrange autoclave continuously according to the curing parameters of relevant process documents and historical data of the curing period

causing planners failure to make a detailed production scheduling plan. Now

data mining algorithm hasn’t been used to predict the curing period of autoclave. To solve the curing time of the autoclave

support vector regression（SVA） method and K–nearest neighbor （KNN） method are used to calculate. The proposed SVR and KNN comparative experiments are performed. Experimental results show that 90% of KNN prediction result is better than support vector regression prediction method

and 90% of the error is less than 0.5 hours. Meanwhile

the reasons for the prediction results of two methods are analyzed.