Although RTP(rapid thermal processing) has gained popularity recently in the semi-conductor industry due a difficult problem. In this study, as an open-loop control technique for RTP temperature distribution, we propose to use Q-ILC(quadratic criterion-based iterative learning control), which can asymptotically attains the minimum achievable control error even under a significant model error, and investigate the performance with an 8-inch silicon wafer RTP model. The time-varying linear model required in the design of Q-ILC was derived by combining the time-invariant linear models identified using the subspace method at each temperature zone. In addition, in order to reduce the heavy computational burden, a reduced-order Q-ILC algorithm was designed and its performance was compared with that of full-order algorithm.