T.H. Hejazi - PhD Candidate, Department of Industrial Engineering and management Systems, Amirkabir University of Technology
M. Ramezani - PhD Candidate, Department of Industrial Engineering and management Systems, Amirkabir University of Technology
M.M. Seyyed-Esfahani - Associate Professor, Department of Industrial Engineering and management Systems, Amirkabir University of Technology,
A.M. Kimiagari - Associate Professor, Department of Industrial Engineering and management Systems, Amirkabir University of Technology,

The control of production processes in an industrial environment needs the correct setting of input factors, so that output products with desirable characteristics will be resulted at minimum cost. Moreover, such systems have to meet set of quality character is tics to satisfy customer requirements. Identifying the most effective factors in design of the process which support continuous and continual improvement is recently discussed from different view points. In this study, we examined the quality engineering problems in which several characteristics and factors are to be analyzed through a simultaneous equations system. Besides, the several probabilistic covariates can be included to the proposed model. The main purpose of this model is to identify interrelations among exogenous and endogenous variables, which give important insight for systematic improvements of quality. At the end, the proposed approach is described analytically by a numerical example.

Design of experiments, Multiple Response Optimization (MRO), Robust design, Probabilistic covariate, System regression