TY - JFULL AU - S. Raissi and R- Eslami Farsani PY - 2009/4/ TI - Statistical Process Optimization Through Multi-Response Surface Methodology T2 - International Journal of Mathematical and Computational Sciences SP - 196 EP - 201 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/14692 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 27, 2009 N2 - In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages. ER -