The proper choices of a process parameter design (PPD) decision problem are studied in a noisy environment of a grease position process in an electronic industry. The process responses consist of the mean of parts between failures on left and right processes.A multi-response surface optimization problemis then proposed to maximize these dual process responses. The conventional modified simplex method and its hybridizations of the stochastic operators from the hunting search and ant colony optimization methods are applied to determine the proper levels of controllable design parameters affecting the quality performances.A numerical example demonstrates the feasibility of applying the proposed model to the PPD problem via two iterative methods. Its advantages are also discussed. Numerical results demonstrate that the hybridization based on the hunting searchmethod seems to besuperior when compared. In this study, the mean of parts between failuresis improved by 27.04%, approximately. All experimental data presented in this research have been normalized to disguise actual performance measures as raw data are considered to be confidential. © (2012) Trans Tech Publications, Switzerland