Identification, for control, of the process parameters influencing tertiary scale formation at the hot strip mill using a binary choice model

Scale is highly detrimental to the surface quality of tinplate products and this problem is created during the hot rolling process. In this paper, a statistical analysis is carried out to both quantify the influence of hot mill process parameters on tertiary scale formation and to use this information to identify how to optimise the running conditions at the hot mill. That is, to identify what base chemistries to use and what temperatures to run the hot mill at so that the percentage of coils produced with significant scale formation is kept as low as is required for meeting customer requirements. Principal component analysis is used to reduce the dimensionality of the dataset whilst retaining the majority of the variability in the process variables. It was found that a Logit model containing these components was consistent with the process data and it was further determined from this model that the most significant variables were the temperature at which the steel strip was entering the finishing mill, together with the percentage of phosphorus, copper and nickel present within the strip. More importantly, for process control it was found that at low levels of phosphorus (<0.011%) there is a less than 10% chance of significant scale formation when the other hot mill variables are kept at their average values. It was also found that to keep the rate of defective coils below 10%, the maximum rougher mill temperature should be kept at 1040°C or less. The Logit model was capable of identifying many other optimal running conditions for the hot mill.