Estimating friction coefficient of cold rolling mills based on lubricant parameters using a numerical method

Today, cold rolling is considered one of the most important industries of any advanced country. Increasing inproduction rate has always been one of the main concerns of every growing industry. These industries usuallyencounter some obstacles which can be solved by scientific methods; although, there have been differentlimitations for this aim. Modeling cold rolling considering lubrication parameters is a complicatedphenomenon, such that even the few presented models are suffering in the practical perspective due to thecomplexity and the time-consuming nature of the model. On the other hand, there have been many fast andcapable models that simulate cold rolling using coulomb friction which obviously makes the analysis of thelubricant parameters impossible. In this paper, as an effort to make simulating cold rolling process modelsmore practical, a shear stress equivalence method between these two types of models is presented, then theequivalent friction coefficient relevant to the lubricant parameters is calculated for each of the two stands.Afterwards, utilizing a full factorial design, a data set is generated. This data set is used to fit a set of linearand non-linear regression models using least square method. The sum of square errors for these equations are14% and 5%, respectively. To evaluate the results, the predicted friction coefficients for two types of oils usedin cold rolling mills are compared to the measured experimental data in each stand, and it is shown that theresults are in good agreement.

Estimating friction coefficient of cold rolling mills based on lubricant parameters using a numerical method Keywords:

Friction , Cold Rolling , Least Square Method