A novel real-time fuzzy-based diagnostic system of roll eccentricity influence in finishing hot strip mills

This paper proposes a method for the diagnosis of the influence of roll eccentricity on the strip thickness at the exit of a finishing hot strip mill (FHSM). Each strip thickness defect on exit is related to a roll of the FHSM, allowing the implementation of an optimal policy for the substitution and maintenance of the rolls, thereby maintaining the required quality level of the strip. This policy allows the minimization of roll changes and the concentration of several changes at the same time, reducing production costs. Fuzzy logic is used to compare spectra, looking for common patterns, which allows for a totally automated diagnostic system. Moreover, an innovative estimate of roll eccentricity based on a least-squares algorithm has been developed, which provides higher accuracy than classical algorithms, as well as a drastic reduction in the time required to perform eccentricity tests.