Since rolled metal strip is used in many applications requiring strict adherence to tolerances, such as in the aerospace, automotive, construction, container, and appliance industries, it necessary to optimized rolling parameter in order to obtain productivity and quality metals. Various Process models for cold rolling mills have been intensively developed in the last years, hoping to increase quality of steel strip and productivity of rolling processes. Nevertheless, characteristics are only achieved using process sufficiently to be robust. The availability of robust & accurate models is associated for cold rolling process optimization has been intensely explored in the literature. Rolling Parameter generation or pass schedule is an important aspect in the operation of Single stand reversing cold rolling mills.
Taguchi methods to quality control have been used to optimize the process parameters of engineering experiments [3]. This approach has been unique and powerful quality improvement discipline that differs from traditional practices. The Taguchi approac has successfully applied in several industrial applications. Parameter design to determine levels that produces the best performance of product/ process under study. The optimal condition is selected so that the influence of uncontrollable factors (Noise factor) causes minimum variation of system performance. Noise factor of process variability that are used to indentify control factors and the combined optimal level which minimizes that variability. Signal to noise ratio ( S/N Ratio) are also used to measure the effect of Noise on the system. A Robust (Insensitive) system will have a high S/N ratio.
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